Speakers

Dean Abbott is an internationally recognized thought leader and innovator in data science and predictive analytics, with more than three decades of experience solving problems in customer analytics, fraud detection, risk modeling, text mining, survey analysis, and many more. He is frequently included in lists of the top pioneering and influential data scientists in the world. Mr. Abbott is the author of Applied Predictive Analytics (Wiley, 2014) and coauthor of The IBM SPSS Modeler Cookbook (Packt Publishing, 2013). He is a popular keynote speaker and bootcamp/workshop instructor at conferences worldwide and serves on advisory boards for the UC/Irvine Predictive Analytics and UC/San Diego Data Science Certificate programs. He holds a bachelors degree in computational mathematics from Rensselaer Polytechnic Institute and a masters degree in applied mathematics from the University of Virginia.

Cheryl has 13 years experience in Statistical Physics, Computational Modeling, Data Science and Digital technologies having worked with both public and private sectors in developing strategic solutions using Machine Learning and Agent-Based Models. At AWS, Cheryl is a Principal Solution Architect for Autonomous Computing with a focus on Predictive Modeling and Simulations for Digital Twins. Prior to joining AWS, Cheryl worked at Quantum Black – McKinsey and Solvay as Data Science Lead defining digital architectures, and delivering Advanced Analytics and AI assets covering various industries including Chemicals Manufacturing, Agriculture, Aviation, R&I, Procurement, Commercial, Supply Chain, Finance and Energy. Prior to that, she worked on insider threat detection, computer vision for marketing, investment banking trading technologies and geospatial analytics for telecommunications. Cheryl obtained her Ph.D. in Physics from Nanyang Technological University in 2017 where she focused on analytical, graph and computational models for urban, linguistic and genetic systems. She also received a B.S. in Applied Physics from the University of the Philippines with specializations in Neural Network and Complex Systems.

Juan Acevedo is an Enterprise machine learning architect at Google where he helps customers optimize models for large scale distributed training and serving with accelerators such as GPUs and TPUs.

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 has worked in the insurance industry for 25 years, including three multi-billion dollar insurers, leading data science teams and 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.

Bardia Beigi works at Microsoft as a Senior Applied Scientist in the Industry AI group delivering AI/ML based solutions to various industries within Azure. Bardia has a master's degree in Computer Science from Stanford University, as well as Bachelor of Applied Science in Engineering Physics from the University of British Columbia. In his spare time, Bardia enjoys traveling, trying out new dessert spots, and learning new life hacks.

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.

Jodi Blomberg leads the enterprise data science and machine learning teams that integrate models into applications across Waste Management. Former head of data science at Charles Schwab.  Experienced data science executive with wide track record in creating products that embed NLP, 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.

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.

ucas Abreu is the co-Founder and Chief Data Scientist at DHAUZ, with an extensive background in Electronics and Computer Engineering. He holds a Master's degree in Applied Artificial Intelligence, and is deeply committed to the advancement of data science and innovative practical solutions. Lucas has a proven track record of developing critical and scalable AI models, both in leadership roles and hands-on implementation, for several industries. He is dedicated to bringing cutting-edge AI solutions to solve complex business problems and improve customer satisfaction.

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.

Vash Doshi is the Manager of Industry Relations for UCLA Anderson's Master of Science in Business Analytics program.  Daily, Vash strives to show employers why UCLA Anderson's MSBA has been ranked the #2 place in the world for the past four years to study, build an analytics career, and recruit from. He is driven to help students and UCLA MSBA’s hundreds of partner firms find each other to create the perfect analytics fit. Vash believes in the magic of people. Whether through developing and advocating for reciprocal market access for American firms so that more Americans can find meaningful jobs and grow their businesses via internships at U.S. Departments of State and Commerce, or by counseling over 500 students to help them find their perfect career, he has over five years of experience helping people make magic happen.  He is currently finishing up his Ph.D. in Political Science at UCSB and holds an M.A. in International Studies from the University of Denver’s Josef Korbel School of International Studies.

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.

Subramanian Iyer is Senior Director of Data Sciences at Target and leads AI teams for forecasting in Supply Chain and Merchandizing modernization in areas like Inventory Planning; digital placement and allocation; financial and budget planning; price optimization and so on. He has previously been Head of Analytics at First Republic Bank, where he led multiple efforts on quantitative analytics, AI modeling, data warehousing, web development for analytical applications and efficient data representation for analytical datasets. Prior to that he was VP of Investment Banking Strategies at Goldman Sachs where he worked on derivatives pricing and structuring in the Americas Financing Group, with a special focus on financial institutions. Prior to that he was in technical roles at Google, Synopsys and Fujitsu and holds several patents. He is an alumnus of Harvard where he did his executive education in General Management, of UT Austin where he received his doctorate in Computer Sciences in Formal Methods and of IIT Bombay where he got his Bachelors in Computer Science & Engineering.

Dr. Usha Jagannathan is a seasoned technologist with over 20 years of experience in driving digital transformation and building customer-centric products. With a strong focus on building new technology ecosystems, she has made significant contributions to McKinsey's Technology & Digital functions. Her expertise encompasses data strategy, leading AI/ML teams in cloud migration initiatives, driving innovation, and implementing AI ethics frameworks to develop responsible AI products. Usha's dedication to promoting DEI efforts is evident through her leadership of apprenticeship and work-study programs aimed at increasing industry diversity. Recognized by business leaders for her expertise in AI ethics and explainability, she is a sought-after speaker at top tech conferences where she shares insights on trending AI technologies and their societal impact.

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.

Koga leads Planning and Business Intelligence organization at Jetson, a leader in personal mobility devices including electric bikes, electric scooters, and hoverboards. Koga joined Jetson in 2021 where is responsible for building the Data & Analytics foundation that generates insights to positively impact customer experience and improve Jetson’s operational performance. He brings extensive knowledge in the consumer electronics industry after working at different services roles at Samsung, Nokia and Microsoft and he also held a series of strategy and consulting roles earlier in her career at Accenture.

Koga prides himself on being very analytical and by connecting the dots across different parts of the customer journey. He is truly passionate about performing deep dive analysis to find the optimal spot between positively impact customer experience, and bringing positive ROI to the 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.

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.

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.

Long before the buzz surrounding Generative AI emerged, Martin Musiol already advocated for its significance in 2016. Since then, he has frequently appeared at conferences, podcasts, and panel discussions, addressing the technological advancements, practical applications, and ethical considerations surrounding Generative AI, Autonomous AI Agents, and Artificial General Intelligence.

In 2018, Martin Musiol founded GenerativeAI.net. There, he lectured to over 10,000 students on AI and published the newsletter 'Generative AI: Short & Sweet,' reaching over 43,000 subscribers. Additionally, he authored "Generative AI - Navigating the Course to the Artificial General Intelligence Future," published by Wiley.

As the GenAI Lead for EMEA at Infosys Consulting (formerly IBM), Martin Musiol assisted companies globally in harnessing the power of Generative AI, especially LLMs, to gain a competitive advantage.

Now, he is building AI Agents that take over software engineering tasks.

Martin’s LinkedIn Profile: https://www.linkedin.com/in/ma...

GenerativeAI.net's Webpage: https://generativeai.net/

Martin’s Newsletter: https://generativeai.net/newsl...

[book] Generative AI - Navigating the Course to the Artificial General Intelligence Future: https://a.co/d/ehyIKoX 

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.

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.

Dr. Jennifer Schaff leads Elder Research's Commercial business unit where she advises organizational decision makers to help them realize maximum value from their analytics investments. In her 20 years of management, data analysis, and business experience, Dr. Schaff has built her reputation as a "Barricade Buster" in the data analytics industry. Her experience has uncovered that business barriers -- defining the right opportunity and consumer, delivering the pertinent results to guide data driven decisions, and implementing the change processes -- rather than model building, is where analytics initiatives often fail. Dr. Schaff channels this approach into a passion for guiding organizations through these business challenges to maximize their analytics ROI.

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., is a leading consultant and former Columbia University professor who helps companies deploy machine learning. He is the founder of the long-running Machine Learning Week conference series and its new sister, Generative AI Applications Summit, the instructor of the acclaimed online course “Machine Learning Leadership and Practice – End-to-End Mastery,” executive editor of The Machine Learning Times, and a frequent keynote speaker. He wrote the bestselling Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die, which has been used in courses at hundreds of universities, as well as The AI Playbook: Mastering the Rare Art of Machine Learning Deployment. Eric’s interdisciplinary work bridges the stubborn technology/business gap. At Columbia, he won the Distinguished Faculty award when teaching the graduate computer science courses in ML and AI. Later, he served as a business school professor at UVA Darden. Eric also publishes op-eds on analytics and social justice.

Eric has appeared on Bloomberg TV and Radio, BNN (Canada), Israel National Radio, National Geographic Breakthrough, NPR Marketplace, Radio National (Australia), and TheStreet. Eric and his books have been featured in Big Think, Businessweek, CBS MoneyWatch, Contagious Magazine, The European Business Review, Fast Company, The Financial Times, Forbes, Fortune, GQ, Harvard Business Review, The Huffington Post, The Los Angeles Times, Luckbox Magazine, MIT Sloan Management Review, The New York Review of Books, The New York Times, Newsweek, Quartz, Salon, The San Francisco Chronicle, Scientific American, The Seattle Post-Intelligencer, Trailblazers with Walter Isaacson, The Wall Street Journal, The Washington Post, and WSJ MarketWatch.

Prerna Singh is currently working as an Applied Scientist II in the Industry AI group @Microsoft where she develops machine learning-based solutions for different industrial verticals including finance and sustainability. Before joining Microsoft, she obtained her master's degree in Electrical and Computer Engineering with a concentration on Machine Learning from Carnegie Mellon University (CMU). Prerna is passionate about machine learning, NLP and deep Reinforcement Learning. Besides work, Prerna enjoys traveling, Zumba and hiking in her free time.

Corwin Smith is an accomplished data & analytics leader, strategist & practitioner. In his role at Wallick Communities, Corwin leads the team focused on delivering advanced analytic models to quantifiably enrich the qualitative expertise of executive leaders and decision-makers. Prior to his current role, Corwin spent over 20 years in the financial & insurance product and consulting industries in roles spanning sales, digital, marketing technology and data & analytics (D&A).

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 brought his military experience to Elder Research to deliver client solutions as a Data Scientist. He now serves as the Director of Analytics Strategy, helping to marry the exciting things that analytics can do with the myriad of challenges that people are facing. Evan almost always has a smile on his face, and that smile is the widest when he is helping organizations use data in new ways to solve unique problems. Evan earned his BS in Management from Georgia Tech, his MS in Economics from East Carolina University and his MS in Analytics from the Institute for Advanced Analytics at NC State University.  He loves teaching and learning and can often be found exploring the outdoors with his wife and children.