Dean Abbott is Co-Founder and Chief Data Scientist of Smarter Remarketer, Inc., and President of Abbott Analytics, Inc. in San Diego, California. Mr. Abbott is an internationally recognized data mining and predictive analytics expert with over two decades experience applying advanced data mining algorithms, data preparation techniques, and data visualization methods to real-world problems, including fraud detection, risk modeling, text mining, personality assessment, response modeling, survey analysis, planned giving, and predictive toxicology.

Mr. Abbott is the author of Applied Predictive Analytics (Wiley, 2014) and co-author of IBM SPSS Modeler Cookbook (Packt Publishing, 2013). He is a highly-regarded and popular speaker at Predictive Analytics and Data Mining conferences and meetups, and is on the Advisory Boards for the UC/Irvine Predictive Analytics Certificate as well as the UCSD Data Mining Certificate programs.

He has a B.S. in Mathematics of Computation from Rensselaer (1985) and a Master of Applied Mathematics from the University of Virginia (1987).

Cal Al-Dhubaib is a globally recognized data scientist, entrepreneur, and innovator in trustworthy artificial intelligence. He is the founder and CEO of Pandata, a consulting company that helps organizations operating in regulated industries design and develop AI-powered solutions to complex business problems. Cal's commitment to diversity and ethics is centered at the heart of his work.

He has gone on to be featured in multiple noteworthy publications, including Forbes,

Ohiox, Cleveland.com, the Marketing AI Institute, and Open Data Science. Cal has also received recognition in Crain's Cleveland Twenty in their 20s and Notable Immigrant Leaders, and Smart Business's Technology Awards and Smart 50 Awards. Most recently, he was named as a Cleveland 2021 Notable Entrepreneur .

Joel works at CNA Insurance where he leads a data science team.  He has been working in the insurance industry for 25 years, doing a variety of data science work to support several business functions.  During this time, he has been involved in numerous discussions where he's seen how different people can reach different conclusions using the same data.  He will draw on these experiences to discuss a number of potential issues in analytics projects with examples from the public domain.

Vladimir Barash is Director Graphika Labs. He has received his Ph.D. from Cornell University, where he studied Information Science and wrote his thesis on the flow of rumors and virally marketed products through social networks. At Graphika, Vladimir's research focuses on deep learning applications of network analysis, detection and deterrence of disinformation operations on networks, and causal mechanisms of large-scale social behavior.

In addition to his research duties, Vladimir has a decade's experience working with big data, from scientific computing (Matlab, scipy) to parallel processing technologies (Hadoop / Hive) to data storage and pipelining (Redis, mongodb, MYSQL) at the terabyte scale. At Graphika, Vladimir has co-designed and implemented systems that process tens of millions every six hours to deliver timely information on influencers and conversation leaders in online communities tailored to client interests. Vladimir is proficient in over a dozen programming languages and frameworks and has designed production-ready systems for every stage of big data analysis, from collection to client-facing presentation via web, spreadsheet or graphic visualization.

Vladimir has been active in the Social Media Research Foundation (SMRF) and the NodeXL project, helping build a network analysis package that brings relational data analysis at scale to the fingertips of any interested user, without requiring specialized knowledge or technical training beyond familiarity with Microsoft Excel. NodeXL has enabled users in academia, industry and the general public to analyze tens of thousands of social networks, from networks of politicians voting on bills to networks of motorcycle enthusiasts working together. As part of his work with SMRF and the NodeXL team, Vladimir has contributed a chapter on Twitter analysis to Analyzing Social Media Networks with NodeXL: Insights from a Connected World.

Vladimir's work has received awards at the International Conference for Weblogs in Social Media and Bits on Our Minds. He has presented his research at academic and industrial campuses all over North America and Europe, including: Xerox/PARC, Microsoft, Colgate University, Northeastern University, UMCP and Oxford University (Oxford Internet Institute). He currently resides in Somerville, MA.

Leo Betthauser works at Microsoft Research in Redmond, Wash. Leo has a Ph.D. in mathematics from the University of Florida where he studied applied algebraic topology. Leo is currently exploring the application of deep neural techniques to cyber security. In his spare time, Leo enjoys traveling, cooking, and skiing.

Clinton Brownley, Ph.D., is a data scientist at WhatsApp, where he’s responsible for a variety of analytics projects designed to improve messaging and VoIP calling performance and reliability.  Before WhatsApp, Clinton was a data scientist at Facebook, working on large-scale infrastructure analytics projects to inform hardware acquisition, maintenance, and data center operations decisions.  As an avid student and teacher of modern analytics techniques, Clinton is the author of two books, “Foundations for Analytics with Python” and “Multi-objective Decision Analysis,” and also teaches Python programming and data science courses at Facebook and in the Bay Area. Clinton is a past-president of the San Francisco Bay Area Chapter of the American Statistical Association and is a council member for the Section on Practice of the Institute for Operations Research and the Management Sciences. Clinton received degrees from Carnegie Mellon University and American University.

Dave Coughlin currently leads a team of 10 data science professionals in the pursuit of driving greater membership and margin for CVS Health's insurance products. Prior to that he did stints in strategy consulting and population health research. A passion of his is performance improvement and he recently wrote a book to scale the insights he has used to turbocharge his own career (3 promotions in 5 years) but also the careers of his mentees. Dave currently lives just outside of Boston with his wife and three children and holds both an MS in applied math and MBA.

Aimee DeGrauwe brings a broad background in data analysis to drive process and quality improvements in supply management, warehousing, manufacturing, and order management. She has a passion for data as a product and has worked on both the technical and business side of data engineering and analytics. In her current role as Group Product Manager, she leads multiple global teams at John Deere focused on ensuring data from our manufacturing and quality systems are easy to use for decision making.

Matt Denesuk has devoted his life to using math & data to make the world work better.  He is currently SVP of Data Analytics & AI at Royal Caribbean Group, and leads the development and deployment of data- and data-science-driven capabilities across the company, in such areas as revenue management, industrial operations, customer experience, marketing, sales, hotel operations, and supply chain. He previously was Chief Data Science Officer, and a founder, of Noodle.ai, which provides AI-as-a-Service to enterprise and industrial firms. Prior to that, he was the Chief Data Science Officer of General Electric, leading the data, analytics, and Data Science functions across GE’s industrial business units.  He also led Smarter Planet Modeling & Analytics at IBM Research, and was a Partner in IBM’s Venture Capital Group. Matt has B.S., M.S., and Ph.D. Degrees from MIT and the University of Arizona.

Dinakar Deshmukh is the VP of data science and analytics for GE Aviation. He has been working in aviation industry for the last 20 years. In his current role as data science leader for GE Aviation, he is responsible for developing AI based solutions for engine health management, supply chain and MRO operations. His team is also developing ML based applications to help airline operations to improve operational efficiencies.

Eric M. Dunleavy, Ph.D., is the Vice President of Employment and Litigation Support Services at DCI Consulting Group, where he is involved in equal employment opportunity audit and litigation consulting. Eric’s primary areas of expertise are in employee selection, employment testing, validation research, adverse impact analyses and other quantitative methods. His most recent work has focused on conducting independent expert reviews and related research across a wide variety of selection procedures, including those that leverage machine learning techniques to analyze data. . Eric received his M.A. (2002) and Ph.D. (2004) in Industrial/Organizational Psychology with a concentration in data analysis from the University of Houston.

John Elder chairs America’s most experienced Data Science consultancy. Founded in 1995, Elder Research has offices in Virginia, Maryland, North Carolina, Washington DC, and London. Dr. Elder co-authored 3 award-winning books on analytics, was a discoverer of ensemble methods, chairs international conferences, and is a popular keynote speaker. John is occasionally an Adjunct Professor of Systems Engineering at the University of Virginia.

Fabio is a Business Analytics Sr Executive working on the field for over 20 years applying advanced modelling and analytics tech solutions to solve complex business challenges, achieving improved customer engagement and higher operational efficiency servicing most of the top 100 companies in Latin America.

He holds a Masters of Logistics Systems Engineering and BA in Construction Engineering both from University of Sao Paulo, Brazil. Fabio is also a certified Lead of Analytics & AI from Northwestern University.

Fabio developed his professional career inside Accenture Latin America, where he started in 2002, being one of first executive in the Analytics Group back in 2010. He conducted Gapso Acquisition on Accenture side in 2015 becoming Lead for Advanced Analytics and Data Science in the region, eventually leading Supply Chain Analytics for Growth Markets until 2021.

Fabio is currently a Sr Advisor in Analytics and Data Adoption for some of the top companies in Brazil and also supports Startups growth and services in the fields of Analytics and Digital Talent Recruiting.

Jen Gennai leads Google’s Responsible Innovation team which is responsible for operationalizing Google’s AI Principles, ensuring that Google’s products have fair and ethical outcomes on individual users and the world. Her team works with product and engineering, leveraging a multidisciplinary group of experts in ethics, human rights, user research, racial justice and gender equity to validate that products and outputs align with our commitments to fairness, privacy, safety, societal benefit and more. Before she co-authored the AI Principles and founded Responsible Innovation, Jen worked on machine learning fairness and founded the Ethical ML team in Trust & Safety.

Justin Gold is a Product Manager for John Deere's Manufacturing Data Platform where he enables John Deere's Global Manufacturing Partners to make informed decisions about their business through trusted data availability.  He guides a team of data engineers as they build data pipelines to feed the generation of dashboards and analytic solutions.  Prior to this role Justin spent his career as a Manufacturing Engineer supporting day to day production of John Deere products.

Justin holds a Bachelor of Science in Engineering and Management from Clarkson University and a Master of Science in Engineering Management from Clarkson University's Beacon Institute.

Product Manager at heart. Noa's forte is creating products specially made for engineers and tech-savvy geeks. With her strong technical background as a former software engineer, her main passion is to simplify complicated technological pains into intuitive solutions and easy-to-use products that anyone can understand and use. She is currently the Lead Product Manager at Dagshub, the data scientist projects platform. She is a public speaking enthusiast and won't miss an opportunity to present her products in front of an audience.

My name is Dao Ho, I am a Senior Data Scientist at Albertsons. My current focus is personalization. At Albertsons, I have worked on several personalization models such as Buy It Again (ranking past purchases), embedding models for our products and customers. In collaboration with Ankita, I have been working on building a Wide & Deep Neural Network model for recommendations. Before Albertsons, I worked at a research lab for GAC, a Chinese car manufacture, building models to monitor the batteries of 30,000 EVs. Prior to that, I worked at a fintech company modeling market conditions. And finally, I graduated from Carnegie Mellon University with a Ph.D. degree in Physics.

Dr. Usha Jagannathan is a Principal Engineer at McKinsey, bringing twenty years of digital transformation experience in building new technology ecosystems and empowering teams to create user-centric products that meet customer needs. Usha focuses primarily on building data strategy, driving sustainable business innovation initiatives, coaching product development teams, and delivering custom digital solutions on cloud to drive accelerated innovation.

Usha is a passionate STEM advocate and works to increase industry diversity through apprenticeship and work-study programs. She has contributed to several engineering articles and spoken in forums hosted by technical organizations including WomenTech network, Women Who Code, Girls in Tech, Grace Hopper Conference, Stanford HAI, and for Gender Equity in Science and Technology.

 Usha serves on the Industry Advisory Board for Fulton Schools of Engineering at Arizona State University. She received her Bachelors in Electronics, Masters in CS from India and earned her PhD in Technology & E-learning from Arizona.

Kian Katanforoosh is the CEO and cofounder of Workera.ai, the skills intelligence platform redefining how enterprises understand, develop, and mobilize talent. Workera empowers organizations to stay ahead by unlocking the skills data needed to drive innovation. Enterprises get an objective pulse of their innovation skills through a configurable skills ontology, using AI-powered measurement of data, AI, software, cloud, and cyber skills at an atomic-level.

Kian is also a lecturer at Stanford University, where he teaches Deep Learning in the Computer Science department with Prof. Andrew Ng. Kian has been acknowledged for his teaching excellence by Stanford with the Walter J. Gores Award, Stanford’s highest teaching award, and the Centennial Award for Excellence in teaching.

Additionally, Kian is a founding member of deeplearning.ai and he co-created the Deep Learning Specialization on Coursera with Andrew Ng. From 2014 to 2016, Kian co-founded and co-led Daskit, a French start-up developing in-classroom ed-tech solutions for universities.

With almost two decades of experience under his belt, Gulrez is a data wrangling extraordinaire, who has a knack for turning boring numbers into captivating stories. When he's not busy working, you can find him digging through open datasets like they're buried treasure, or passing on his data visualization skills to the next generation in the hopes of creating a world of data literate children.

A strong believer in the power of data literacy, Gulrez is on a mission to improve the way people make sense of data. He's known for delivering corporate workshops that are equal parts informative and entertaining, and is currently working on a book that promises to be a page-turner for data geeks everywhere.

Diego Klabjan is a professor at Northwestern University, Department of Industrial Engineering and Management Sciences. He is also Founding Director, Master of Science in Analytics and Director, Center for Deep Learning. His work is focused on machine learning, deep learning and analytics (modeling, methodologies, theoretical results) with concentration in finance, insurance, sports, and bioinformatics. Professor Klabjan has led projects with large companies such as Intel, Baxter, Allstate, Anthem, and many others. He is also a co-founder of Videspan, LLC after successfully starting Opex Analytics, a Coupa company.

William Komp is the Principle Data Scientist at Komplytics LLC.. He has over 2 decades of experience in academia, health care, marketing analytics, transportation, logistics, Oil&Gas, Food&Beverage, environmental management, renewable energy and public utilities. He was the technical editor for Applied Predictive Analytics (J. WIley and Sons 2014). He holds a PhD Physics with areas of research in Gravitation, Cosmology and Quantum Field Theory in Curved Spacetime.

Sam, with over 30 years experience, in the data science space, provides advanced analytic support to his many clients. His current responsibilities at Harte Hanks includes quantitative support to many industries , including retail, financial, health care, automotive, technology, consumer goods, publications, among others. His previous experiences include heading the Predictive and Targeted Modeling area at American Express. There he was responsible for strategic and tactical support for the many subsidiaries of American Express. At TMI associates, a boutique consulting firm, Sam was principal analytic consultant. At JC Penney, Sam was responsible for credit scoring and database analytics. Sam has been fortunate to train many machine learning professionals. He is a  frequent speaker at industry conferences, and has published dozens of machine learning related articles. Sam has an undergraduate degree in mathematics, and earned an MBA at New York University. He has lectured at both Columbia and New York University.

I was born and raised in India. As a child, I moved about quite a bit in India, attending 9 different schools across 3 distinct states (Karnataka, Maharashtra, and Madhya Pradesh). Since change was the only constant, I learned to adapt quickly, be independent, and solve problems. My family prioritized education significantly, which influenced many of my life’s choices. I was accepted into Maharashtra's finest engineering college, the College of Engineering Pune (COEP), where I pursued my bachelor's degree in Electronics and Computer Engineering. Sensing the need to improve my competence in digital solutions development and general problem-solving, I enrolled in a Master’s program in Information Technology and Management at the University of Texas at Dallas. My interest in business development using data as a tool for strategy and innovation started to take precedence over other career options at this point.

Prior to joining Google, I worked at Southwest Airlines, American Airlines, and Intuitive Surgical, in Strategy and Operations using Data Science and Analytics; where I developed numerous solutions and received several awards for customer experience and performance improvement throughout my tenure. To further enhance my skills and gain competence in strategy and business decision-making, I am currently pursuing a Doctorate in Business Administration at Westcliff University.

In my current role, I create analytical solutions that help Google define and quantify performance (success), solve problems, and drive strategy. I collaborate with Engineering, the Product team, the Project Manager's Office, and other cross-functional executives. I focus on optimizing operational performance with the goal of enhancing the customer experience. I develop and continuously improve data pipelines.

A Teaching Associate Professor in the Institute for Advanced Analytics, Dr. Aric LaBarr is passionate about helping people solve challenges using their data. There he helps design the innovative program to prepare a modern work force to wisely communicate and handle a data-driven future at the nation's first Master of Science in analytics degree program. He teaches courses in predictive modeling, forecasting, simulation, financial analytics, and risk management.

Previously, he was Director and Senior Scientist at Elder Research, where he mentored and lead a team of data scientists and software engineers. As director of the Raleigh, NC office he worked closely with clients and partners to solve problems in the fields of banking, consumer product goods, healthcare, and government.

Dr. LaBarr holds a B.S. in economics, as well as a B.S., M.S., and Ph.D. in statistics — all from NC State University.

Jared P. Lander is Chief Data Scientist of Lander Analytics, the Organizer of the New York Open Statistical Programming Meetup and the New York and Government R Conferences, an Adjunct Professor at Columbia Business School, and a Visiting Lecturer at Princeton University. With a masters from Columbia University in statistics and a bachelors from Muhlenberg College in mathematics, he has experience in both academic research and industry. Jared oversees the long-term direction of the company and acts as Lead Data Scientist, researching the best strategy, models and algorithms for modern data needs. This is in addition to his client-facing consulting and training. He specializes in data management, multilevel models, machine learning, generalized linear models, data management, visualization and statistical computing. He is the author of R for Everyone (now in its second edition), a book about R Programming geared toward Data Scientists and Non-Statisticians alike. The book is available from Amazon, Barnes & Noble and InformIT. The material is drawn from the classes he teaches at Columbia and is incorporated into his corporate training. Very active in the data community, Jared is a frequent speaker at conferences, universities and meetups around the world.

Michael Lawrence is Director, Business Intelligence, Operations, & Transformation at Tata Communications. Mr. Lawrence has 20 years of experience in telecommunications, program management and business operations.  He is an expert in change management and driving a culture of making business decisions off of data insights.  Michael has a MS in Information Science from Penn State University as well as an undergraduate degree in Mathematics from the University of Scranton.

Hien Luu is a Sr. Engineering Manager at DoorDash, leading the Machine Learning Platform team. He is particularly passionate about the intersection between Big Data and Artificial Intelligence. He is the author of the Beginning Apache Spark 3 book. He has given presentations at various conferences such as GHC 2022, Data+AI Summit, XAI 21 Summit, MLOps World, YOW Data!, appy(), QCon (SF,NY, London).

Dr. Ankita Mangal is a Senior Data Scientist at Albertsons Companies. She has a broad experience applying data science & analytics solutions at companies like Procter & Gamble, Robert Bosch and Tata Steel Ltd. She is an accomplished leader in the field of retail and marketing science, who is championing data informed decision making in the Retail and Consumer Packaged Goods industry. Dr. Mangal is passionate about efficient cross functional collaborations for creating successful ML solutions. In her current role, she provides technical leadership, mentorship and develops interpretable and accurate models for business strategy decisions. Dr. Mangal has a doctoral degree from Carnegie Mellon University and is an alumnus of IIT Kharagpur.

James McCaffrey, who annually leads the full-day deep learning workshop at Machine Learning Week, works for Microsoft Research in Redmond, Wash. James has a PhD in cognitive psychology and computational statistics from the University of Southern California, a BA in psychology, a BA in applied mathematics, and an MS in computer science. James learned to speak to the public while working at Disneyland as a college student, and he can still recite the entire Jungle Cruise ride narration from memory.

Long before the buzz surrounding generative AI, Martin Musiol was already advocating for its significance in 2015. Since then, he has been a frequent speaker at conferences, podcasts, and panel discussions, addressing the technological advancements, practical applications, and ethical considerations of generative AI. Martin Musiol is a co-founder of generativeAI.net, a lecturer on AI to over 1000 students, and publisher of the newsletter 'Generative AI: Short & Sweet'. As a Data Science Manager at Infosys Consulting (previously at IBM), Martin Musiol helps companies globally harness the power of generative AI to gain a competitive advantage.

A seasoned Data leader with 16+ years of experience in Data Science delivery, product development, and consulting. Currently, he is working as a Director in Tata CLiQ (the e-commerce arm of Tata Industry for Lifestyle & Beauty business), responsible for driving Data Operations, Data Governance, Analytics & Insight practices. He is distinguished as an author of multiple papers and poster presentations at various National & International conferences. He has to his credit four patents filed in the Customer & Pricing Analytics space and has one publication in an International journal. He is also passionate about teaching and has worked as a visiting lecturer across multiple Institutes and ed-tech organizations.

Marina Petzel is a Machine Learning Engineer at Autodesk. In her role, she develops ML solutions to further improve the AutoCAD users experience; Autodesk's flagship design and drafting tool. Marina leads the data collection and labeling processes through automation using ML.

She is passionate about finding and developing efficient data driven solutions that address business needs. Marina has extensive experience in applying data science to various industries such as construction, healthcare, oil and gas, and finance.

Marina is an AI Influencer in social media where she shares AI/ML tips and best practices. She coaches and mentors young professionals in data science, engineering and career strategy.

Marina graduated from the University of Rochester, NY with a Master of Science degree in Data Science. She received her Bachelor degree in Computer Science from Moscow State University.

Kumaran Ponnambalam is a technology leader with 20+ years of experience in AI, Big Data, Data Processing & Analytics. His focus is on creating robust, scalable AI models and services to drive effective business solutions.  He is currently leading AI initiatives in the Emerging Technologies & Incubation Group in Cisco. In his previous roles, he has built data pipelines, analytics, integrations, and conversational bots around customer engagement. He has also authored several courses on the LinkedIn Learning Platform in AI and Big Data.

In her current role as Chief Data & Analytics Officer of Team One, Prachi manages the agency’s consolidated Data & Analytics function across all locations. With over 18 years of success conceptualizing and delivering best-in-class analytics solutions, she provides thought leadership on the power of data and how data can be leveraged to deliver a customer-centric experience and accelerate business results. She also ensures that the company’s products and capabilities are ahead of industry trends, by archetyping the next generation of data strategy and partnerships. 

Before data became “cool,” Prachi pioneered some of the earliest advancement in the analytics space and helped companies find ease and avoid over-architecting informed solutions.

Prior to joining Team One, she held various leadership roles, both on the agency and business-side, at global firms like Wunderman Thompson, UnitedHealthcare, and Lifetime Fitness where she helped drive growth and strategic consumer relationships.

Additionally, Prachi has held board and advisory roles at several industry and community organizations. She currently serves on the Asians in Advertising and I-COM advisory boards and collaborates with industry leaders to develop best practices in Data-driven Marketing. 

Steven J. Ramirez is the chief executive officer of Berkeley, Calif.-based Beyond the Arc, Inc., a firm recognized as a leader in helping companies transform their customer experiences by leveraging advanced analytics.

In addition to developing and executing the vision for Beyond the Arc, Ramirez leads teams of data and strategy consultants committed to client success. They analyze customer and social media data, combined with text analysis, to drive customer growth, improve customer retention, understand service breaks and build stronger customer loyalty.

Prior to leading Beyond the Arc, Ramirez served as an executive with Time Warner, where he was responsible for creating and successfully implementing marketing and corporate development strategies.

Ramirez earned a bachelor's degree and master's in Business Administration from the University of California at Berkeley. He as also created and taught courses in business management for UC Berkeley and been a guest speaker at the university's Haas School of Business.

Karl Rexer founded Rexer Analytics in 2002. He and his teams have built an outstanding reputation providing predictive modeling and analytic consulting to clients across many industries. Recent clients include OneBlood, PwC, Boston Scientific, Redbox, ADT Security, Interamericana University, MIT, Forward Financing, SharkNinja, and many smaller companies. In addition to leading client engagements and hands-on data work, Karl is a predictive analytics evangelist, frequently speaking at conferences, colleges, and other events. He also serves on Advisory Boards for the Business Analytics programs at both Babson College and Bentley University. Since 2007 Rexer Analytics has conducted surveys of analytic professionals, asking them about their algorithms, tools, behaviors and  views. Summary reports from these surveys are available as a free download from the Rexer Analytics website. Prior to founding Rexer Analytics, Karl held leadership positions at several consulting firms and two multi-national banks. Karl holds a PhD from the University of Connecticut.

Brian Sampsel is a Vice President with the International Institute for Analytics, where he leads delivery of the company's services such as the Research and Advisory Network and the Analytics Leadership Consortium. He possesses a wide breadth of experience in the data and analytics field across a variety of industries and functions, holding leadership roles on both the client and vendor sides. Brian seeks to help his clients through a consultative and solutions focused mindset, with expertise across a number of tools and techniques including business analytics, data science, cognitive services and robotic process automation. Brian has a Bachelor's degree in Mathematics from Cedarville University and a Master's degree in Statistics from Miami University.

Asha Saxena is a strategic, innovative leader with a proven track record of building successful tech businesses for the last 25 years. With a strong academic background, creative problem-solving skills, and an effective management style. She has been instrumental in building business models for success.

Asha Saxena is the Founder and CEO of Women Leaders in Data and AI (WLDA), an organization bringing senior leaders together with a mission to create an impactful digital world with parity and equity.

Asha Saxena is also a partner at CEO Coaching International, a leading coaching firm for growth-focused CEOs and entrepreneurs, where we follow a practical and proven methodology to help CEOs and their teams perform at their very best and achieve their business goals.

As a Board Advisor and an Adjunct Professor at Columbia University, she teaches graduate classes on Management Consulting, Entrepreneurship and Big Data Analytics. She has served a four-year term as Entrepreneur-in-Residence at Columbia Business School.

Published Author, Columnist at Entrepreneur Magazine, Asha Saxena is a well-known key-note speaker on Entrepreneurship, Leadership, Women in Technology, Artificial Intelligence and Big Data.

Dan works as the Head of Machine Learning at Abnormal Security, where he builds cybercrime detection systems to keep people and businesses safe. Cybercrime is always changing as attackers innovate, and the detection organization at Abnormal Security must stay ahead of these innovations. As the Head of Machine Learning, Dan works to optimize the detection organization's ability to anticipate these innovations, iterate and improve.

Before joining Abnormal Dan worked at Twitter: first as an ML researcher working on recommendation systems, and then as the engineering manager for the web ads machine learning team. Before Twitter Dan built smartphone sensor algorithms at TrueMotion and Computer Vision systems at the Serre Lab. Dan's PhD at the University of Oxford focused on the applications of Category Theory to Machine Learning.

Eric Siegel, Ph.D., founder of the Predictive Analytics World conference series and executive editor of The Machine Learning Times, makes the how and why of predictive analytics understandable and captivating. He is the author of the award-winning Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die, a former Columbia University professor who used to sing to his students, and a renowned speaker, educator, and leader in the field.

Eric has appeared on Bloomberg TV and Radio, Business News Network (Canada), Fox News, Israel National Radio, NPR Marketplace, Radio National (Australia), and TheStreet. He and his book have been featured in Businessweek, CBS MoneyWatch, Contagious Magazine, The European Business Review, The Financial Times, Forbes, Forrester, Fortune, Harvard Business Review, The Huffington Post, The New York Review of Books, Newsweek, Quartz, Salon, Scientific American, The Seattle Post-Intelligencer, The Wall Street Journal, The Washington Post, and WSJ MarketWatch. Follow him at @predictanalytic.

Corwin Smith is an accomplished data & analytics strategist and practitioner. In his role, Corwin focuses on designing and implementing predictive and statistical models to forecast future business performance by leveraging advanced machine learning platforms. Additionally he analyzes internal & external data to understand performance drivers to identify improvement opportunities to streamline and automate the analytical processes and data pipelines that feed predictive models and dashboards necessary for decision-making. Corwin spent 20 years in the financial and insurance product industry spanning sales, digital, marketing and data & analytics (D&A). He spent the last 5 of those years focused on D&A, where he enabled delivery of over $60 million in quantifiable value for organizational partners by owning the development and deployment of the artificial intelligence and machine learning data product solution strategies.

Dr. Marc A. Smith is a sociologist specializing in the social organization of online communities and computer mediated interaction. Smith leads the Connected Action consulting group. Smith co-founded the Social Media Research Foundation (http://www.smrfoundation.org/), a non-profit devoted to open tools, data, and scholarship related to social media research. He contributes to the open and free NodeXL project (http://nodexl.codeplex.com) that adds social network analysis features to the familiar Excel spreadsheet. NodeXL enables social network analysis of email, Twitter, Flickr, WWW, Facebook and other network data sets. Along with Derek Hansen and Ben Shneiderman, he is the co-author and editor of Analyzing Social Media Networks with NodeXL: Insights from a connected world, from Morgan-Kaufmann which is a guide to mapping connections created through computer-mediated interactions. Smith has published research on social media extensively, providing a map to the landscape of connected communities on the Internet.

Brandon Southern, MBA, is a Director of Analytics with over 20 years' experience across analytics, software engineering, quality assurance, data engineering, and leadership. As a business and technical leader, he has generated millions of dollars in revenue and cost reductions through advanced analytics.  Brandon is also the founder of Analytics Mentor, where he specializes in training, coaching, and elevating analytics professionals.

David Talby is the Chief Technology Officer at John Snow Labs, helping companies apply artificial intelligence to solve real-world problems in healthcare and life science. David is the creator of Spark NLP the world's most widely used natural language processing library in the enterprise. He has extensive experience building and running web-scale software platforms and teams – in startups, for Microsoft's Bing in the US and Europe, and to scale Amazon's financial systems in Seattle and the UK. David holds a Ph.D. in Computer Science and Masters degrees in both Computer Science and Business Administration. He was named USA CTO of the Year by the Global 100 Awards and GameChangers Awards in 2022.

James Taylor is the CEO of Decision Management Solutions and is a leading expert in how to use business rules and analytic technology to build decision management systems. He is passionate about using decision management systems to help companies improve decision-making and develop an agile, analytic and adaptive business. He provides strategic consulting to companies of all sizes, working with clients in all sectors to adopt decision-making technology. James is an expert member of the International Institute for Analytics and is the author of multiple books and articles on decision management, decision modeling, predictive analytics and business rules, and writes a regular blog at JT on EDM. James also delivers webinars, workshops and training. He is a regular keynote speaker at conferences around the world.

Annette Tyman is a Partner at the law firm Seyfarth Shaw LLP.  She chairs the People Analytics practice group and regularly advises employers on diversity, equity and inclusion workforce analytics and the legally compliant use of machine learning in the workplace.  Annette collaborates with employers and vendors to design, develop and implement machine learning while mitigating the legal risks associated with its use.   Annette has also provided testimony on proposed labor and employment legislation and regulations pending before the United States Senate, House of Representatives, and the Equal Employment Opportunity Commission.  Most recently, Annette testified before the New York City Department of Consumer and Worker Protection on proposed rules implementing Local Law 144 of 2021 on the use of automated employment decision tools and hearings regarding the implementation of proposed laws in Washington D.C.

Dr. Vazirabadi (Vazeerabaadi), received her PhD in Psychological Measurement and Quantitative Research Methods from University of Denver, in Denver, CO in 2010. She has been contributing to the workforce analytics field since 2005 and was directly responsible for her team's achievement of their first industry award in 2008 from IQPC for Best HR Metrics and Analytics. Since then, she has been key in the analytics strategy, development, and execution of number of mid-size and large organization where through her work she was responsible for significant cost savings, business process improvement and HR effectiveness measures. She has received multiple industry awards for her work, published in peer reviewed journals and taught at colleges and universities in her field of expertise. For the past six years she has been working for Bristol Myers Squibb as a subject matter expert in HR Analytics, where she designs measurement techniques, analyzes data, interprets results, and provides action plans and next steps for her HR executives.

Evan Wimpey was a Financial Management Officer in the Marine Corps and an Operations Associate at Goldman Sachs prior to joining Elder Research as a Data Scientist. He holds master's degrees in Economics from East Carolina University and in Analytics from North Carolina State University. He is currently the Director of Strategic Analytics at Elder Research. Evan has a passion for cryptocurrency and exploring more equitable access to credit markets. Evan lives in Cary, NC with his wife and two sons.

Rohit works as a  Chief Data Officer at Mobisy Technologies, where he leads a team of Data Scientists & Software Engineers, focusing on retail analytics by applying state of the art ML & Deep Learning techniques. His analysis is published in all the leading financial publications in India every month. Prior to that he spent 11 years in GE working on some of the most challenging data problems for Healthcare & Life sciences.

Rohit has been an active Manning Publication Reviewer and reviewed multiple books & live projects related to Deep Learning & NLP. He has spoken in multiple international conferences including Predictive Analytics conference, Munich (2019,2020). Rohit has a Masters degree in Information Technology  & Bachelors degree in Computer Science

Jie Chen is the head of Decision Science and Artificial Intelligence Model Validation in Corporate Model Risk at Wells Fargo. Her team covers model validation in decision science, natural language processing (NLP), fair lending, financial crime detection, fraud detection and marketing. Prior to that, she led the Cross-Functional Model Validation team and the Statistical Modeling and Machine Learning R&D team in Corporate Model Risk at Wells Fargo.  Before joining Wells Fargo, Jie was a vice president at Bank of America working on market risk model development and consumer credit risk solutions.  She has over fifteen-year experience on machine learning, artificial intelligence, and advanced statistics in the banking industry.  Jie holds a Ph.D. in statistics from the Stewart School of Industrial and Systems Engineering at the Georgia Institute of Technology.

John Elder chairs America’s most experienced Data Science consultancy. Founded in 1995, Elder Research has offices in Virginia, Maryland, North Carolina, Washington DC, and London. Dr. Elder co-authored 3 award-winning books on analytics, was a discoverer of ensemble methods, chairs international conferences, and is a popular keynote speaker. John is occasionally an Adjunct Professor of Systems Engineering at the University of Virginia.

Jen Gennai leads Google’s Responsible Innovation team which is responsible for operationalizing Google’s AI Principles, ensuring that Google’s products have fair and ethical outcomes on individual users and the world. Her team works with product and engineering, leveraging a multidisciplinary group of experts in ethics, human rights, user research, racial justice and gender equity to validate that products and outputs align with our commitments to fairness, privacy, safety, societal benefit and more. Before she co-authored the AI Principles and founded Responsible Innovation, Jen worked on machine learning fairness and founded the Ethical ML team in Trust & Safety.

With almost two decades of experience under his belt, Gulrez is a data wrangling extraordinaire, who has a knack for turning boring numbers into captivating stories. When he's not busy working, you can find him digging through open datasets like they're buried treasure, or passing on his data visualization skills to the next generation in the hopes of creating a world of data literate children.

A strong believer in the power of data literacy, Gulrez is on a mission to improve the way people make sense of data. He's known for delivering corporate workshops that are equal parts informative and entertaining, and is currently working on a book that promises to be a page-turner for data geeks everywhere.

Dr. Li is the leading Research Scientist for AI Risks of Munich Re in the US. As part of a team developing insurance solutions around AI/ML underperformance, she focuses on model uncertainty quantification in an applied and theoretical way. This extends her academic research at UC Davis where she received her PhD in statistics. Munich Re is a leading global risk and insurance solutions providers.

James McCaffrey, who annually leads the full-day deep learning workshop at Machine Learning Week, works for Microsoft Research in Redmond, Wash. James has a PhD in cognitive psychology and computational statistics from the University of Southern California, a BA in psychology, a BA in applied mathematics, and an MS in computer science. James learned to speak to the public while working at Disneyland as a college student, and he can still recite the entire Jungle Cruise ride narration from memory.

Long before the buzz surrounding generative AI, Martin Musiol was already advocating for its significance in 2015. Since then, he has been a frequent speaker at conferences, podcasts, and panel discussions, addressing the technological advancements, practical applications, and ethical considerations of generative AI. Martin Musiol is a co-founder of generativeAI.net, a lecturer on AI to over 1000 students, and publisher of the newsletter 'Generative AI: Short & Sweet'. As a Data Science Manager at Infosys Consulting (previously at IBM), Martin Musiol helps companies globally harness the power of generative AI to gain a competitive advantage.

Karl Rexer founded Rexer Analytics in 2002. He and his teams have built an outstanding reputation providing predictive modeling and analytic consulting to clients across many industries. Recent clients include OneBlood, PwC, Boston Scientific, Redbox, ADT Security, Interamericana University, MIT, Forward Financing, SharkNinja, and many smaller companies. In addition to leading client engagements and hands-on data work, Karl is a predictive analytics evangelist, frequently speaking at conferences, colleges, and other events. He also serves on Advisory Boards for the Business Analytics programs at both Babson College and Bentley University. Since 2007 Rexer Analytics has conducted surveys of analytic professionals, asking them about their algorithms, tools, behaviors and  views. Summary reports from these surveys are available as a free download from the Rexer Analytics website. Prior to founding Rexer Analytics, Karl held leadership positions at several consulting firms and two multi-national banks. Karl holds a PhD from the University of Connecticut.

Eric Siegel, Ph.D., founder of the Predictive Analytics World conference series and executive editor of The Machine Learning Times, makes the how and why of predictive analytics understandable and captivating. He is the author of the award-winning Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die, a former Columbia University professor who used to sing to his students, and a renowned speaker, educator, and leader in the field.

Eric has appeared on Bloomberg TV and Radio, Business News Network (Canada), Fox News, Israel National Radio, NPR Marketplace, Radio National (Australia), and TheStreet. He and his book have been featured in Businessweek, CBS MoneyWatch, Contagious Magazine, The European Business Review, The Financial Times, Forbes, Forrester, Fortune, Harvard Business Review, The Huffington Post, The New York Review of Books, Newsweek, Quartz, Salon, Scientific American, The Seattle Post-Intelligencer, The Wall Street Journal, The Washington Post, and WSJ MarketWatch. Follow him at @predictanalytic.

Hariom Tatsat currently works as a Vice President in the Quantitative Analytics division of an investment bank in New York. He is the co-author of the book "Machine Learning and Data Science Blueprints for Finance". Hariom has extensive experience as a Quant in the areas of predictive modelling, financial instrument pricing, and risk management in several global investment banks and financial organizations. He completed his MS at UC Berkeley and his undergrad at Indian Institute of Technology.

James Taylor is the CEO of Decision Management Solutions and is a leading expert in how to use business rules and analytic technology to build decision management systems. He is passionate about using decision management systems to help companies improve decision-making and develop an agile, analytic and adaptive business. He provides strategic consulting to companies of all sizes, working with clients in all sectors to adopt decision-making technology. James is an expert member of the International Institute for Analytics and is the author of multiple books and articles on decision management, decision modeling, predictive analytics and business rules, and writes a regular blog at JT on EDM. James also delivers webinars, workshops and training. He is a regular keynote speaker at conferences around the world.

Mack Wallace is Senior Director, Head of Student Loans at MPOWER Financing. His area of expertise is the use of new methods in data and analytics in highly regulated areas of consumer finance, including credit underwriting. Mr Wallace also serves as an external Advisor at both the Aspen Institute and the World Bank where he researches and publishes on the use of data and technology to advance financial inclusion and consumer protection.

William (Bill) Wilkins is a multi-purpose actuary for the Safety National Casualty Corporation(SNCC). He is a CERA, FCAS, ASA and MAAA.  While his main focus is on Enterprise Risk Management and Predictive Analytics, Bill has experience in pricing insurance, reinsurance, credit risk products, risk management, reserving and broker management.  He is currently Co-Chair of the SNCC Data Analytics Committee.  The Data Analytics Committee is a cross-functional group tasked with all aspects of data for SNCC.  The Committee works on data to be collected, how it is collected, where it is collected from, how it stored, standards and practices of usage, etc.  This includes the populating items like benchmarking reports or how best to create and use predictive analytics.  The goal is to establish a process that is repeatable and adaptable so SNCC can deliver both internally and externally.

Evan Wimpey was a Financial Management Officer in the Marine Corps and an Operations Associate at Goldman Sachs prior to joining Elder Research as a Data Scientist. He holds master's degrees in Economics from East Carolina University and in Analytics from North Carolina State University. He is currently the Director of Strategic Analytics at Elder Research. Evan has a passion for cryptocurrency and exploring more equitable access to credit markets. Evan lives in Cary, NC with his wife and two sons.

Gordon Yang is a Fellow of the Society of Actuaries (FSA) with 15 years of experience serving the finance and insurance industry. Currently, he is leading the advanced analytics and AUW effort in the underwriting department at Pacific Life. Gordon is a frequent speaker in the industry, providing thought leadership on utilizing machine learning techniques in the actuarial and financial risk management space.

Prior to being an actuary, Gordon obtained a master's degree in Applied Mathematics from Columbia University. Gordon is also a certified AWS practitioner with an analytics specialty and a certified Financial Risk Manager (FRM).

Cal Al-Dhubaib is a globally recognized data scientist, entrepreneur, and innovator in trustworthy artificial intelligence. He is the founder and CEO of Pandata, a consulting company that helps organizations operating in regulated industries design and develop AI-powered solutions to complex business problems. Cal's commitment to diversity and ethics is centered at the heart of his work.

He has gone on to be featured in multiple noteworthy publications, including Forbes,

Ohiox, Cleveland.com, the Marketing AI Institute, and Open Data Science. Cal has also received recognition in Crain's Cleveland Twenty in their 20s and Notable Immigrant Leaders, and Smart Business's Technology Awards and Smart 50 Awards. Most recently, he was named as a Cleveland 2021 Notable Entrepreneur .

Steve Anderson is an analytics executive who has lead analytics teams for several years and has wrangled petabytes of data to drive positive outcomes/impact. He is currently the VP of Analytics at Outlook Amusement, which is a company based in Los Angeles. Mr. Anderson specializes in: Database Marketing, Data Analysis, Data Warehousing, Report Development, Business Intelligence and Machine Learning. His expertise expands across several industries – sports, entertainment, financial services, gaming, and retail. Additionally, he received a Master of Engineering Management degree from Christian Brothers University and a Bachelor of Science in Computer Engineering from The University of Memphis.

Andrew Bate is VP & Head of Safety Innovation & Analytics at GSK and leads the development of next generation Safety capability as a member of the Global Safety Leadership team. Previously Andrew was in the Global Epidemiology Leadership team at Pfizer and prior to that led the Research function at the WHO Collaborating Centre for International Drug Monitoring.

Andrew has contributed to many international initiatives and partnerships including membership of the FDA Science Board Subcommittee on Pharmacovigilance, CIOMS VIII on signal detection of adverse effects of medicinal products and Transcelerate Pharmacovigilance Steering Committee where he is sponsor of the Intelligent Automation work stream. He has served on both the Executive Committee of ISoP and the Board of ISPE. He is currently a member of the international, non-governmental, non-profit organization established jointly by WHO and UNESCO Council for International Organizations of Medical Sciences (CIOMS)’s Working Group on Artificial Intelligence.

Dr. Carroll is a physician leader with experience in retail health, workmen’s compensation, Medicare and commercial risk programs, integrated delivery networks, managed care and primary care practices. He has led groups in value-based care transformation in the era of global risk payment. He has extensive experience in retail health, ACO/MSSP development and execution in a variety of settings: the Indian Health Service, Medical Director at Tufts Health Plan, a large innovative multispecialty group at Atrius Health, CMO in a 3 billion dollar fully integrated health system at Hartford Healthcare, Group Vice President / CMO Walgreens, CMO at HIMS-HERS, CMO Vida Health and currently at Whoop.

Ben Cleveland is a Principal Data Scientist at UnityPoint Health in Strategic Analytics. He designs and operationalizes data products that utilize advanced data modeling techniques for the purposes of clinical excellence, strategic planning, and improvement within a large health system. His machine learning and visualization tools are in active use across the enterprise, from executive leadership to clinicians and care teams. Cleveland is a nationally recognized data science practitioner with speaking invitations at analytics, IT, and population health events across the country. His work was awarded the 2016 Project of the Year in Patient Safety from Health Data Management, Finalist for the 2016 ANNY Award from the International Institute for Analytics, and first place in the 2018 Healthcare Informatics Innovator Awards.

Dave Coughlin currently leads a team of 10 data science professionals in the pursuit of driving greater membership and margin for CVS Health's insurance products. Prior to that he did stints in strategy consulting and population health research. A passion of his is performance improvement and he recently wrote a book to scale the insights he has used to turbocharge his own career (3 promotions in 5 years) but also the careers of his mentees. Dave currently lives just outside of Boston with his wife and three children and holds both an MS in applied math and MBA.

Fabio is a Business Analytics Sr Executive working on the field for over 20 years applying advanced modelling and analytics tech solutions to solve complex business challenges, achieving improved customer engagement and higher operational efficiency servicing most of the top 100 companies in Latin America.

He holds a Masters of Logistics Systems Engineering and BA in Construction Engineering both from University of Sao Paulo, Brazil. Fabio is also a certified Lead of Analytics & AI from Northwestern University.

Fabio developed his professional career inside Accenture Latin America, where he started in 2002, being one of first executive in the Analytics Group back in 2010. He conducted Gapso Acquisition on Accenture side in 2015 becoming Lead for Advanced Analytics and Data Science in the region, eventually leading Supply Chain Analytics for Growth Markets until 2021.

Fabio is currently a Sr Advisor in Analytics and Data Adoption for some of the top companies in Brazil and also supports Startups growth and services in the fields of Analytics and Digital Talent Recruiting.

Chris is the Chair of Predictive Analytics World Healthcare and the Vice President of Advanced Analytics for OSF Healthcare where he leads a team of data scientists and automation engineers who create and deploy industry leading advanced analytics solutions.  He has more than 16 years of experience working in healthcare and holds a MS in Predictive Analytics from Northwestern University, where he focused on advanced modeling techniques and predictive text mining.

Jen Gennai leads Google’s Responsible Innovation team which is responsible for operationalizing Google’s AI Principles, ensuring that Google’s products have fair and ethical outcomes on individual users and the world. Her team works with product and engineering, leveraging a multidisciplinary group of experts in ethics, human rights, user research, racial justice and gender equity to validate that products and outputs align with our commitments to fairness, privacy, safety, societal benefit and more. Before she co-authored the AI Principles and founded Responsible Innovation, Jen worked on machine learning fairness and founded the Ethical ML team in Trust & Safety.

Craig Kurtzweil leads the UnitedHealthcare Center for Advanced Analytics, which is focused on using analytic innovations to better evaluate and improve health care value for employers and members. His team is focused on the serving large employers with the most complex health care challenges, taking a broad view of data spanning quality, cost, and productivity. Recent work includes the creation of the Health Business Improvement Model, which demonstrated the ability to enhance health outcomes, improve productivity and reduce presentism. Craig brings nearly 20 years of health care experience, including previous roles focused on using data to improve the health of communities and decision making by elected/appointed officials. Craig frequently speaks at health care and technology conferences, including recent appearances at the 2022 Constellation Connected Enterprise Summit, Teradata Possible and Integrated Benefits Institute.  He holds a Bachelor’s degree in Actuarial Science from Carlson School of Management.

James McCaffrey, who annually leads the full-day deep learning workshop at Machine Learning Week, works for Microsoft Research in Redmond, Wash. James has a PhD in cognitive psychology and computational statistics from the University of Southern California, a BA in psychology, a BA in applied mathematics, and an MS in computer science. James learned to speak to the public while working at Disneyland as a college student, and he can still recite the entire Jungle Cruise ride narration from memory.

Long before the buzz surrounding generative AI, Martin Musiol was already advocating for its significance in 2015. Since then, he has been a frequent speaker at conferences, podcasts, and panel discussions, addressing the technological advancements, practical applications, and ethical considerations of generative AI. Martin Musiol is a co-founder of generativeAI.net, a lecturer on AI to over 1000 students, and publisher of the newsletter 'Generative AI: Short & Sweet'. As a Data Science Manager at Infosys Consulting (previously at IBM), Martin Musiol helps companies globally harness the power of generative AI to gain a competitive advantage.

Eric Siegel, Ph.D., founder of the Predictive Analytics World conference series and executive editor of The Machine Learning Times, makes the how and why of predictive analytics understandable and captivating. He is the author of the award-winning Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die, a former Columbia University professor who used to sing to his students, and a renowned speaker, educator, and leader in the field.

Eric has appeared on Bloomberg TV and Radio, Business News Network (Canada), Fox News, Israel National Radio, NPR Marketplace, Radio National (Australia), and TheStreet. He and his book have been featured in Businessweek, CBS MoneyWatch, Contagious Magazine, The European Business Review, The Financial Times, Forbes, Forrester, Fortune, Harvard Business Review, The Huffington Post, The New York Review of Books, Newsweek, Quartz, Salon, Scientific American, The Seattle Post-Intelligencer, The Wall Street Journal, The Washington Post, and WSJ MarketWatch. Follow him at @predictanalytic.

David Talby is the Chief Technology Officer at John Snow Labs, helping companies apply artificial intelligence to solve real-world problems in healthcare and life science. David is the creator of Spark NLP the world's most widely used natural language processing library in the enterprise. He has extensive experience building and running web-scale software platforms and teams – in startups, for Microsoft's Bing in the US and Europe, and to scale Amazon's financial systems in Seattle and the UK. David holds a Ph.D. in Computer Science and Masters degrees in both Computer Science and Business Administration. He was named USA CTO of the Year by the Global 100 Awards and GameChangers Awards in 2022.

Dr. Nephi Walton is a biomedical informaticist and clinical geneticist with experience in machine learning and genomics. He had led several research initiatives in genomics and informatics at Geisinger prior to joining Intermountain Healthcare. At Geisinger he successfully completed a pilot integration of genomics data into the EPIC electronic health record system for both pharmacogenomics and CDC tier one genetic conditions. He currently serves as the Associate Medical Director of Intermountain Precision Genomics where he leads the HerediGene Genomic Sequencing Return of Results program. He also serves as the Associate Medical Director of Intermountain’s sequencing laboratory.  He is the Chair of Genomics and Translational Bioinformatics for the American Medical Informatics Association and has presented at several meetings on translating the use of genomics into general medical practice, something he is actively pursuing at Intermountain Healthcare.

Dean Abbott is Co-Founder and Chief Data Scientist of Smarter Remarketer, Inc., and President of Abbott Analytics, Inc. in San Diego, California. Mr. Abbott is an internationally recognized data mining and predictive analytics expert with over two decades experience applying advanced data mining algorithms, data preparation techniques, and data visualization methods to real-world problems, including fraud detection, risk modeling, text mining, personality assessment, response modeling, survey analysis, planned giving, and predictive toxicology.

Mr. Abbott is the author of Applied Predictive Analytics (Wiley, 2014) and co-author of IBM SPSS Modeler Cookbook (Packt Publishing, 2013). He is a highly-regarded and popular speaker at Predictive Analytics and Data Mining conferences and meetups, and is on the Advisory Boards for the UC/Irvine Predictive Analytics Certificate as well as the UCSD Data Mining Certificate programs.

He has a B.S. in Mathematics of Computation from Rensselaer (1985) and a Master of Applied Mathematics from the University of Virginia (1987).

Dr. Chakrabarti is a Senior Research Scientist in Hitachi's Financial Innovation Lab. in Santa Clara. He works at the intersection of data science and finance, and has been doing industrial research for over ten years . He did his MS-PhD in Electrical and Computer Engineering at Rice University, and afterwards did his Master of Financial Engineering at U C Berkeley. Dr. Chakrabarti's research publications and patents have collectively been cited over one thousand times.

Jim is an Academician of International Academy for Quality, a Fellow of American Society for Quality, and is co-author on 9 international patents for advanced analytics in Oil & Gas, and Utilities.  His most recent publications are on Disruptive Analytics and Data Science.  He lectures internationally on Big Data and Advanced Analytics for the China International Industries Fair (keynote 4 years) as well as India and universities in Taiwan, Portugal and Qatar.  Jim’s career includes positions as a corporate director for two Fortune 100 companies.  His positions included Director, Strategic Business Analytics for Anheuser-Busch, Senior Data Scientist for SAS Institute, and Technology Director, Corporate Quality Assurance for Reynolds Metals.  He chaired the committee on statistical procedures for the Aluminum Association and served on the GMP SPC Committee for the Pharmaceutical Manufacturers Association.  Jim holds BS and MS degrees in statistics.

John Elder chairs America’s most experienced Data Science consultancy. Founded in 1995, Elder Research has offices in Virginia, Maryland, North Carolina, Washington DC, and London. Dr. Elder co-authored 3 award-winning books on analytics, was a discoverer of ensemble methods, chairs international conferences, and is a popular keynote speaker. John is occasionally an Adjunct Professor of Systems Engineering at the University of Virginia.

Jen Gennai leads Google’s Responsible Innovation team which is responsible for operationalizing Google’s AI Principles, ensuring that Google’s products have fair and ethical outcomes on individual users and the world. Her team works with product and engineering, leveraging a multidisciplinary group of experts in ethics, human rights, user research, racial justice and gender equity to validate that products and outputs align with our commitments to fairness, privacy, safety, societal benefit and more. Before she co-authored the AI Principles and founded Responsible Innovation, Jen worked on machine learning fairness and founded the Ethical ML team in Trust & Safety.

Sarah Kalicin is a HR Measurement Data Scientist with Intel Corporation, who is passionate about how organizations gain more business value through Data Science. In her extensive data career at Intel, she develops strategic plans for analytic adoption to increase business impact. Working in various industry and government positions, such as Becton Dickinson (BD), Kraft Foods, Nabisco, Ford Motor Company, and USDA/National Agriculture Statistics Service, she has gained insight and experience on how successful organizations function that allow them to succeed in their analytic initiatives.  She holds a Master’s degree in Applied Statistics from the University of Michigan and Bachelors’ degrees in Mathematics and Psychology from the SUNY at Oswego.

Diego Klabjan is a professor at Northwestern University, Department of Industrial Engineering and Management Sciences. He is also Founding Director, Master of Science in Analytics and Director, Center for Deep Learning. His work is focused on machine learning, deep learning and analytics (modeling, methodologies, theoretical results) with concentration in finance, insurance, sports, and bioinformatics. Professor Klabjan has led projects with large companies such as Intel, Baxter, Allstate, Anthem, and many others. He is also a co-founder of Videspan, LLC after successfully starting Opex Analytics, a Coupa company.

Wes is a data science innovator, with a career of experience working on projects that elevate data science solutions to business problems.  With a strong background in software engineering, analytics, and machine learning Wes is able to bridge the gap between computer science and data science.  Wes has built software to streamline machine learning at scale, built product integrated machine learning models that drive revenue by increasing product ROI, and answered countless questions with deep dive analysis projects.

James McCaffrey, who annually leads the full-day deep learning workshop at Machine Learning Week, works for Microsoft Research in Redmond, Wash. James has a PhD in cognitive psychology and computational statistics from the University of Southern California, a BA in psychology, a BA in applied mathematics, and an MS in computer science. James learned to speak to the public while working at Disneyland as a college student, and he can still recite the entire Jungle Cruise ride narration from memory.

Terry Miller has spent nearly 10 years working with OEMs to evaluate and optimize industrial processes through increased performance of their machines. After finishing a Master’s Degree in Predictive Analytics, Terry began formally training and deploying traditional statistical models, as well as Machine Learning algorithms for asset-predictive (explanatory) maintenance and process optimization, specifically on industrial robots.

In his current role, Terry is building a global team of data scientists and data engineers to solve problems in the Services business for Johnson Controls.  Deploying the best practices of Machine Learning and Predictive Analytics, his team facilitates outcomes in Customer Retention, Pricing, and other enterprise applications.

Long before the buzz surrounding generative AI, Martin Musiol was already advocating for its significance in 2015. Since then, he has been a frequent speaker at conferences, podcasts, and panel discussions, addressing the technological advancements, practical applications, and ethical considerations of generative AI. Martin Musiol is a co-founder of generativeAI.net, a lecturer on AI to over 1000 students, and publisher of the newsletter 'Generative AI: Short & Sweet'. As a Data Science Manager at Infosys Consulting (previously at IBM), Martin Musiol helps companies globally harness the power of generative AI to gain a competitive advantage.

Ayush is the co-founder of TwelveFold, an AI start-up studio, where he manages a portfolio of MLOps and Generative AI companies with entrepreneurs. He also works as the CEO of Censius, an AI Observability platform that helps to optimize AI models' real-world performance.  As a seasoned professional, he has closely worked with customers across industry verticals, AI teams, and research projects to build reliable and compliant AI solutions to solve everyday business problems and scale models at production.

Steven J. Ramirez is the chief executive officer of Berkeley, Calif.-based Beyond the Arc, Inc., a firm recognized as a leader in helping companies transform their customer experiences by leveraging advanced analytics.

In addition to developing and executing the vision for Beyond the Arc, Ramirez leads teams of data and strategy consultants committed to client success. They analyze customer and social media data, combined with text analysis, to drive customer growth, improve customer retention, understand service breaks and build stronger customer loyalty.

Prior to leading Beyond the Arc, Ramirez served as an executive with Time Warner, where he was responsible for creating and successfully implementing marketing and corporate development strategies.

Ramirez earned a bachelor's degree and master's in Business Administration from the University of California at Berkeley. He as also created and taught courses in business management for UC Berkeley and been a guest speaker at the university's Haas School of Business.

Karl Rexer founded Rexer Analytics in 2002. He and his teams have built an outstanding reputation providing predictive modeling and analytic consulting to clients across many industries. Recent clients include OneBlood, PwC, Boston Scientific, Redbox, ADT Security, Interamericana University, MIT, Forward Financing, SharkNinja, and many smaller companies. In addition to leading client engagements and hands-on data work, Karl is a predictive analytics evangelist, frequently speaking at conferences, colleges, and other events. He also serves on Advisory Boards for the Business Analytics programs at both Babson College and Bentley University. Since 2007 Rexer Analytics has conducted surveys of analytic professionals, asking them about their algorithms, tools, behaviors and  views. Summary reports from these surveys are available as a free download from the Rexer Analytics website. Prior to founding Rexer Analytics, Karl held leadership positions at several consulting firms and two multi-national banks. Karl holds a PhD from the University of Connecticut.

Alejandro Jesús Castañeira Rodríguez is the Principal Data Scientist atJanzz.technology a leading developing and consulting company in jobmatching solutions, international classification systems, multilingualknowledge graphs, and processing of Human Resources(HR) information.Janzz offers SaaS/Cloud solutions as well as standard on-premise andwhite-label products in up to 40 languages for multinational jobportals, social and career networks, governmental or state-levelorganizations and public employment services(PES) worldwide. In hiscurrent role, Alejandro leads multiple stages of the product developmentcycle, from data collection, training of deep learning models,evaluation, deployment, maintenance, and customer support. He alsosupports and mentors other members of its team, providing guidance ontechnical issues, setting performance goals, and identifying areas forprofessional growth. Before coming to the HR industry, Alejandro was alecturer of Applied Mathematics and researcher, for more than 5 years atone of the most prestigious and beloved universities in Latin America,the Universidad de Oriente, Cuba. Where he graduated from a Master'sDegree in Computer Science specializing in the field of ArtificialIntelligence and Natural Language Processing.

Asha Saxena is a strategic, innovative leader with a proven track record of building successful tech businesses for the last 25 years. With a strong academic background, creative problem-solving skills, and an effective management style. She has been instrumental in building business models for success.

Asha Saxena is the Founder and CEO of Women Leaders in Data and AI (WLDA), an organization bringing senior leaders together with a mission to create an impactful digital world with parity and equity.

Asha Saxena is also a partner at CEO Coaching International, a leading coaching firm for growth-focused CEOs and entrepreneurs, where we follow a practical and proven methodology to help CEOs and their teams perform at their very best and achieve their business goals.

As a Board Advisor and an Adjunct Professor at Columbia University, she teaches graduate classes on Management Consulting, Entrepreneurship and Big Data Analytics. She has served a four-year term as Entrepreneur-in-Residence at Columbia Business School.

Published Author, Columnist at Entrepreneur Magazine, Asha Saxena is a well-known key-note speaker on Entrepreneurship, Leadership, Women in Technology, Artificial Intelligence and Big Data.

Eric Siegel, Ph.D., founder of the Predictive Analytics World conference series and executive editor of The Machine Learning Times, makes the how and why of predictive analytics understandable and captivating. He is the author of the award-winning Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die, a former Columbia University professor who used to sing to his students, and a renowned speaker, educator, and leader in the field.

Eric has appeared on Bloomberg TV and Radio, Business News Network (Canada), Fox News, Israel National Radio, NPR Marketplace, Radio National (Australia), and TheStreet. He and his book have been featured in Businessweek, CBS MoneyWatch, Contagious Magazine, The European Business Review, The Financial Times, Forbes, Forrester, Fortune, Harvard Business Review, The Huffington Post, The New York Review of Books, Newsweek, Quartz, Salon, Scientific American, The Seattle Post-Intelligencer, The Wall Street Journal, The Washington Post, and WSJ MarketWatch. Follow him at @predictanalytic.

Evan Wimpey was a Financial Management Officer in the Marine Corps and an Operations Associate at Goldman Sachs prior to joining Elder Research as a Data Scientist. He holds master's degrees in Economics from East Carolina University and in Analytics from North Carolina State University. He is currently the Director of Strategic Analytics at Elder Research. Evan has a passion for cryptocurrency and exploring more equitable access to credit markets. Evan lives in Cary, NC with his wife and two sons.

Dean Abbott is Co-Founder and Chief Data Scientist of Smarter Remarketer, Inc., and President of Abbott Analytics, Inc. in San Diego, California. Mr. Abbott is an internationally recognized data mining and predictive analytics expert with over two decades experience applying advanced data mining algorithms, data preparation techniques, and data visualization methods to real-world problems, including fraud detection, risk modeling, text mining, personality assessment, response modeling, survey analysis, planned giving, and predictive toxicology.

Mr. Abbott is the author of Applied Predictive Analytics (Wiley, 2014) and co-author of IBM SPSS Modeler Cookbook (Packt Publishing, 2013). He is a highly-regarded and popular speaker at Predictive Analytics and Data Mining conferences and meetups, and is on the Advisory Boards for the UC/Irvine Predictive Analytics Certificate as well as the UCSD Data Mining Certificate programs.

He has a B.S. in Mathematics of Computation from Rensselaer (1985) and a Master of Applied Mathematics from the University of Virginia (1987).

Vladimir Barash is Director Graphika Labs. He has received his Ph.D. from Cornell University, where he studied Information Science and wrote his thesis on the flow of rumors and virally marketed products through social networks. At Graphika, Vladimir's research focuses on deep learning applications of network analysis, detection and deterrence of disinformation operations on networks, and causal mechanisms of large-scale social behavior.

In addition to his research duties, Vladimir has a decade's experience working with big data, from scientific computing (Matlab, scipy) to parallel processing technologies (Hadoop / Hive) to data storage and pipelining (Redis, mongodb, MYSQL) at the terabyte scale. At Graphika, Vladimir has co-designed and implemented systems that process tens of millions every six hours to deliver timely information on influencers and conversation leaders in online communities tailored to client interests. Vladimir is proficient in over a dozen programming languages and frameworks and has designed production-ready systems for every stage of big data analysis, from collection to client-facing presentation via web, spreadsheet or graphic visualization.

Vladimir has been active in the Social Media Research Foundation (SMRF) and the NodeXL project, helping build a network analysis package that brings relational data analysis at scale to the fingertips of any interested user, without requiring specialized knowledge or technical training beyond familiarity with Microsoft Excel. NodeXL has enabled users in academia, industry and the general public to analyze tens of thousands of social networks, from networks of politicians voting on bills to networks of motorcycle enthusiasts working together. As part of his work with SMRF and the NodeXL team, Vladimir has contributed a chapter on Twitter analysis to Analyzing Social Media Networks with NodeXL: Insights from a Connected World.

Vladimir's work has received awards at the International Conference for Weblogs in Social Media and Bits on Our Minds. He has presented his research at academic and industrial campuses all over North America and Europe, including: Xerox/PARC, Microsoft, Colgate University, Northeastern University, UMCP and Oxford University (Oxford Internet Institute). He currently resides in Somerville, MA.

Leo Betthauser works at Microsoft Research in Redmond, Wash. Leo has a Ph.D. in mathematics from the University of Florida where he studied applied algebraic topology. Leo is currently exploring the application of deep neural techniques to cyber security. In his spare time, Leo enjoys traveling, cooking, and skiing.

Christopher Brossman leads the enterprise ML/AI teams and Data Engineering teams that enable scale and profitability at The RealReal. Experienced ML/AI engineer executive with wide track record in creating products that embed computer vision, machine learning, statistical modeling, and optimization to create demonstrable value.

Clinton Brownley, Ph.D., is a data scientist at WhatsApp, where he’s responsible for a variety of analytics projects designed to improve messaging and VoIP calling performance and reliability.  Before WhatsApp, Clinton was a data scientist at Facebook, working on large-scale infrastructure analytics projects to inform hardware acquisition, maintenance, and data center operations decisions.  As an avid student and teacher of modern analytics techniques, Clinton is the author of two books, “Foundations for Analytics with Python” and “Multi-objective Decision Analysis,” and also teaches Python programming and data science courses at Facebook and in the Bay Area. Clinton is a past-president of the San Francisco Bay Area Chapter of the American Statistical Association and is a council member for the Section on Practice of the Institute for Operations Research and the Management Sciences. Clinton received degrees from Carnegie Mellon University and American University.

Pranjal helped set up Cisco Innovation Labs after dropping out of his PhD and handles Machine Learning/Product there. He also serves as an Entrepreneur-in-Residence at Vonzos Partners. Previously he conducted ML research at Adobe Research, IBM Research, University of Alberta, Purdue University and Northwestern University. He attended Stanford GSB in the Ignite program and is an On Deck Fellow.

At Google DeepMind, Praneet is a Senior Research Engineer, having previously worked on AI for Industrial Controls in its Applied group. Praneet serves as part of the Technical Program Committee for leading AI venues  such as NeurIPS, ICML and ICLR among others. He is a member of the Confederation of Indian Industry's Artificial Intelligence Task Force. Before DeepMind, he was a  Machine Learning Engineer at Google Cloud. He holds an MS in Electrical and Computer Engineering from Carnegie Mellon University and is an alumni of the Stanford Graduate School of Business Ignite program.

John Elder chairs America’s most experienced Data Science consultancy. Founded in 1995, Elder Research has offices in Virginia, Maryland, North Carolina, Washington DC, and London. Dr. Elder co-authored 3 award-winning books on analytics, was a discoverer of ensemble methods, chairs international conferences, and is a popular keynote speaker. John is occasionally an Adjunct Professor of Systems Engineering at the University of Virginia.

Jen Gennai leads Google’s Responsible Innovation team which is responsible for operationalizing Google’s AI Principles, ensuring that Google’s products have fair and ethical outcomes on individual users and the world. Her team works with product and engineering, leveraging a multidisciplinary group of experts in ethics, human rights, user research, racial justice and gender equity to validate that products and outputs align with our commitments to fairness, privacy, safety, societal benefit and more. Before she co-authored the AI Principles and founded Responsible Innovation, Jen worked on machine learning fairness and founded the Ethical ML team in Trust & Safety.

My name is Dao Ho, I am a Senior Data Scientist at Albertsons. My current focus is personalization. At Albertsons, I have worked on several personalization models such as Buy It Again (ranking past purchases), embedding models for our products and customers. In collaboration with Ankita, I have been working on building a Wide & Deep Neural Network model for recommendations. Before Albertsons, I worked at a research lab for GAC, a Chinese car manufacture, building models to monitor the batteries of 30,000 EVs. Prior to that, I worked at a fintech company modeling market conditions. And finally, I graduated from Carnegie Mellon University with a Ph.D. degree in Physics.

Diego Klabjan is a professor at Northwestern University, Department of Industrial Engineering and Management Sciences. He is also Founding Director, Master of Science in Analytics and Director, Center for Deep Learning. His work is focused on machine learning, deep learning and analytics (modeling, methodologies, theoretical results) with concentration in finance, insurance, sports, and bioinformatics. Professor Klabjan has led projects with large companies such as Intel, Baxter, Allstate, Anthem, and many others. He is also a co-founder of Videspan, LLC after successfully starting Opex Analytics, a Coupa company.

Jared P. Lander is Chief Data Scientist of Lander Analytics, the Organizer of the New York Open Statistical Programming Meetup and the New York and Government R Conferences, an Adjunct Professor at Columbia Business School, and a Visiting Lecturer at Princeton University. With a masters from Columbia University in statistics and a bachelors from Muhlenberg College in mathematics, he has experience in both academic research and industry. Jared oversees the long-term direction of the company and acts as Lead Data Scientist, researching the best strategy, models and algorithms for modern data needs. This is in addition to his client-facing consulting and training. He specializes in data management, multilevel models, machine learning, generalized linear models, data management, visualization and statistical computing. He is the author of R for Everyone (now in its second edition), a book about R Programming geared toward Data Scientists and Non-Statisticians alike. The book is available from Amazon, Barnes & Noble and InformIT. The material is drawn from the classes he teaches at Columbia and is incorporated into his corporate training. Very active in the data community, Jared is a frequent speaker at conferences, universities and meetups around the world.

Ledion Lico is a highly experienced IT/Data professional and researcher, working as a data scientist at Paychex. In his current role he has worked on a variety of machine learning and deep learning projects including job title normalization, call transcript data analytics, customer segmentation, growth prediction, and others. Having previously worked as an NLP researcher at the University of Rochester Medical Center, Ledion has studied and researched the most advanced methods utilizing deep learning in NLP. Prior to Paychex, he worked as an IT manager for several years, dealing with various business data processes and platforms. Ledion has a MS degree in Data Science from the University of Rochester and a PhD in Information Technology from the Polytechnic University of Tirana. He has published several papers regarding the utilization of Machine Learning in customer behavior analysis and prediction.

Hien Luu is a Sr. Engineering Manager at DoorDash, leading the Machine Learning Platform team. He is particularly passionate about the intersection between Big Data and Artificial Intelligence. He is the author of the Beginning Apache Spark 3 book. He has given presentations at various conferences such as GHC 2022, Data+AI Summit, XAI 21 Summit, MLOps World, YOW Data!, appy(), QCon (SF,NY, London).

Dr. Ankita Mangal is a Senior Data Scientist at Albertsons Companies. She has a broad experience applying data science & analytics solutions at companies like Procter & Gamble, Robert Bosch and Tata Steel Ltd. She is an accomplished leader in the field of retail and marketing science, who is championing data informed decision making in the Retail and Consumer Packaged Goods industry. Dr. Mangal is passionate about efficient cross functional collaborations for creating successful ML solutions. In her current role, she provides technical leadership, mentorship and develops interpretable and accurate models for business strategy decisions. Dr. Mangal has a doctoral degree from Carnegie Mellon University and is an alumnus of IIT Kharagpur.

James McCaffrey, who annually leads the full-day deep learning workshop at Machine Learning Week, works for Microsoft Research in Redmond, Wash. James has a PhD in cognitive psychology and computational statistics from the University of Southern California, a BA in psychology, a BA in applied mathematics, and an MS in computer science. James learned to speak to the public while working at Disneyland as a college student, and he can still recite the entire Jungle Cruise ride narration from memory.

Mrinal Mohit heads machine learning at Glean, a Sequoia-backed unicorn building the next generation of enterprise search. Mrinal previously worked as a Machine Learning engineer at Facebook, where he built conversational systems powering Facebook Portal, Oculus Quest, and Ray-Ban Stories. His research has been published research at NeurIPS and EMNLP, and he co-created the open source library PyText. He holds a masters from MIT, and a bachelors from IIT.

Long before the buzz surrounding generative AI, Martin Musiol was already advocating for its significance in 2015. Since then, he has been a frequent speaker at conferences, podcasts, and panel discussions, addressing the technological advancements, practical applications, and ethical considerations of generative AI. Martin Musiol is a co-founder of generativeAI.net, a lecturer on AI to over 1000 students, and publisher of the newsletter 'Generative AI: Short & Sweet'. As a Data Science Manager at Infosys Consulting (previously at IBM), Martin Musiol helps companies globally harness the power of generative AI to gain a competitive advantage.

Ayush is the co-founder of TwelveFold, an AI start-up studio, where he manages a portfolio of MLOps and Generative AI companies with entrepreneurs. He also works as the CEO of Censius, an AI Observability platform that helps to optimize AI models' real-world performance.  As a seasoned professional, he has closely worked with customers across industry verticals, AI teams, and research projects to build reliable and compliant AI solutions to solve everyday business problems and scale models at production.

I'm currently a Machine Learning Engineer at Stripe. Previously, I worked at a small AI start up Node, acquired by Sugar CRM, and BlackRock.

I'm also the USA Ambassador of WomeninAI, a global nonprofit. Most recently, I volunteered to help build COVIDNearYou with Harvard Medical School and Boston Children’s Hospital, which was featured on CNBC. I share my AI expertise with venture capital and technology policy as an Advisor for Oxylabs, Alumni Venture Group Fellow and Lincoln Network Policy Hacker Fellow. I've also been recognized as a Google Developer Expert and Google Woman Techmaker.

I've spoken about artificial intelligence at meet-ups and conferences around the world, including but not limited to, O'Reilly AI, O'Reilly Tensorflow World, and Pyladies. I've also been featured in the Wogrammer, the AI Journal, Elpha, and CNBC.

Personal Website: www.pujaarajan.com

Rishab is the co-founder & CTO of Openlayer. Openlayer is a YC-backed company that aims to make it easy for ML teams to find failures and biases in their models, figure out their root causes and use better data to fix them. Rishab graduated from Yale in 2019, and subsequently worked at Apple on a variety of projects within their AI/ML org before founding Openlayer.

Dan works as the Head of Machine Learning at Abnormal Security, where he builds cybercrime detection systems to keep people and businesses safe. Cybercrime is always changing as attackers innovate, and the detection organization at Abnormal Security must stay ahead of these innovations. As the Head of Machine Learning, Dan works to optimize the detection organization's ability to anticipate these innovations, iterate and improve.

Before joining Abnormal Dan worked at Twitter: first as an ML researcher working on recommendation systems, and then as the engineering manager for the web ads machine learning team. Before Twitter Dan built smartphone sensor algorithms at TrueMotion and Computer Vision systems at the Serre Lab. Dan's PhD at the University of Oxford focused on the applications of Category Theory to Machine Learning.

Eric Siegel, Ph.D., founder of the Predictive Analytics World conference series and executive editor of The Machine Learning Times, makes the how and why of predictive analytics understandable and captivating. He is the author of the award-winning Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die, a former Columbia University professor who used to sing to his students, and a renowned speaker, educator, and leader in the field.

Eric has appeared on Bloomberg TV and Radio, Business News Network (Canada), Fox News, Israel National Radio, NPR Marketplace, Radio National (Australia), and TheStreet. He and his book have been featured in Businessweek, CBS MoneyWatch, Contagious Magazine, The European Business Review, The Financial Times, Forbes, Forrester, Fortune, Harvard Business Review, The Huffington Post, The New York Review of Books, Newsweek, Quartz, Salon, Scientific American, The Seattle Post-Intelligencer, The Wall Street Journal, The Washington Post, and WSJ MarketWatch. Follow him at @predictanalytic.

Dr. Marc A. Smith is a sociologist specializing in the social organization of online communities and computer mediated interaction. Smith leads the Connected Action consulting group. Smith co-founded the Social Media Research Foundation (http://www.smrfoundation.org/), a non-profit devoted to open tools, data, and scholarship related to social media research. He contributes to the open and free NodeXL project (http://nodexl.codeplex.com) that adds social network analysis features to the familiar Excel spreadsheet. NodeXL enables social network analysis of email, Twitter, Flickr, WWW, Facebook and other network data sets. Along with Derek Hansen and Ben Shneiderman, he is the co-author and editor of Analyzing Social Media Networks with NodeXL: Insights from a connected world, from Morgan-Kaufmann which is a guide to mapping connections created through computer-mediated interactions. Smith has published research on social media extensively, providing a map to the landscape of connected communities on the Internet.

David Talby is the Chief Technology Officer at John Snow Labs, helping companies apply artificial intelligence to solve real-world problems in healthcare and life science. David is the creator of Spark NLP the world's most widely used natural language processing library in the enterprise. He has extensive experience building and running web-scale software platforms and teams – in startups, for Microsoft's Bing in the US and Europe, and to scale Amazon's financial systems in Seattle and the UK. David holds a Ph.D. in Computer Science and Masters degrees in both Computer Science and Business Administration. He was named USA CTO of the Year by the Global 100 Awards and GameChangers Awards in 2022.

James Taylor is the CEO of Decision Management Solutions and is a leading expert in how to use business rules and analytic technology to build decision management systems. He is passionate about using decision management systems to help companies improve decision-making and develop an agile, analytic and adaptive business. He provides strategic consulting to companies of all sizes, working with clients in all sectors to adopt decision-making technology. James is an expert member of the International Institute for Analytics and is the author of multiple books and articles on decision management, decision modeling, predictive analytics and business rules, and writes a regular blog at JT on EDM. James also delivers webinars, workshops and training. He is a regular keynote speaker at conferences around the world.

Evan Wimpey was a Financial Management Officer in the Marine Corps and an Operations Associate at Goldman Sachs prior to joining Elder Research as a Data Scientist. He holds master's degrees in Economics from East Carolina University and in Analytics from North Carolina State University. He is currently the Director of Strategic Analytics at Elder Research. Evan has a passion for cryptocurrency and exploring more equitable access to credit markets. Evan lives in Cary, NC with his wife and two sons.