Dean Abbott is President of Abbott Analytics and currently is the Bodily Bicentennial Professor in Analytics at UVA Darden School of Business. He is an internationally recognized thought leader and innovator in data science and predictive analytics with more than three decades of experience solving a wide range of private and public sector problems. Mr. Abbott is the author of Applied Predictive Analytics (Wiley, 2014) and coauthor of The IBM SPSS Modeler Cookbook (Packt Publishing, 2013).

Rohit works as a Chief Data Officer at Mobisy Technologies), where he focuses on retail analytics by applying state of the art ML & Deep Learning techniques. His retail insights are published in all the leading financial publications in India every week. Prior to Mobisy, he was with GE for 11 years. He has spoken in multiple international conferences including PAW Munich (2019), Berlin (2020), Las Vegas (2022). Rohit has a Masters degree in Information Technology & Bachelors degree in Computer Science.

Experienced Data Scientist and Tech Lead at Imperva's threat research group where I work on creating machine learning algorithms to help protect our customers against web app and DDoS attacks. Before joining Imperva, I obtained a B.Sc and M.Sc in Bioinformatics from Bar Ilan University.

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.

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.

Larry Braman built and currently leads Career Services for UCLA Anderson's Master of Science in Business Analytics program, ranked #2 in the world by QS for the past three years.  With the support of the hundreds of corporate relationships he has developed as well as the Career Curriculum and individual coaching he delivers, his students consistently achieve 100% internship and full-time placement rates in data science and analytics roles across multiple industries and environments, from start-up to Fortune 100.  He welcomes your outreach at .

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.

Peter Bruce founded the Institute for Statistics Education at Statistics.com in 2002.  The Institute, which was acquired by Elder Research, Inc. in 2019, specializes in introductory and graduate level online education in statistics, optimization, risk modeling, predictive modeling, data mining, and other subjects in quantitative analytics. Peter is a leading author in the field of data science.  He co-authored of Responsible Data Science (Wiley, 2021), cited by Bookauthority.com as the Best New Data Science eBooks of 2021, and one of the Best Data Science Model Books of All Time. He is also a co-author of the Wiley best-selling Machine Learning for Business Analytics, (Wiley, 2006 – 2021) with 13 editions, versions and translations, used in over 600 universities around the world. Peter co-authored Practical Statistics for Data Scientists (O’Reilly, 2nd ed. 2020), which ranks #3 in Amazon’s list of best-selling books in Mathematical Analysis. He is also the author of Introductory Statistics and Analytics, a Resampling Perspective (Wiley 2015). In addition to English, Peter’s books have appeared in German, Chinese, Japanese, Korean and Polish. Peter’s role at the Statistics.com centers on course development and faculty recruitment – there are over 60 faculty members from around the world who are published experts in their fields; most teach from their own texts. He also teaches a course on resampling methods. Peter has degrees from Princeton, Harvard and the University of Maryland. Prior to his work in statistics, Peter worked in the US diplomatic corps as a Foreign Service Officer.

Aaron is currently the Vice President of Data Science and Solutions at dotData. As a data science practitioner with 14 years of research and industrial experience, he has held various leadership positions in spearheading new product development in the fields of data science and business intelligence. At dotData, Aaron leads the data science team in working directly with clients and solving their most challenging problems.

Prior to joining dotData, he was a Data Science Principle Manager with Accenture Digital, responsible for architecting data science solutions and delivering business values for the tech industry on the West Coast. He was instrumental in the strategic expansion of Accenture Digital’s footprint in the data science market in North America.

Aaron received his Ph.D. degree in Applied Physics from Northwestern University.

Tom is the founding partner of At One Ventures, which backs early-stage (Seed, Series A) companies using disruptive deep tech to upend the unit economics of established industries while dramatically reducing their planetary footprint.

Previous to founding At One, Tom was a founding member of Google X where he led the teams that created self-driving cars, deep learning artificial intelligence, wearable augmented reality and internet connectivity expansion. He played a significant role in established projects with global reach including Microsoft (Outlook) and Yahoo (Search, Answers). 

He has also spent time in the developing world and via social entrepreneurship accelerators, mentoring 200+ entrepreneurs working on global development issues such as access to clean water, electricity, education, health care, and employment.

Tom has spoken at TEDx, Aspen Institute, YPO, SuperVenture, IDEO, Unreasonable and Summit at Sea. He  is also a lifelong inventor, with 75 patents across hardware, software, design, and mechanical systems.

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.

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.

Usama Fayyad is the Executive Director of the Institute for Experiential AI and Chairman of Open Insights, a technology and consulting firm he founded in 2008. His previous roles include co-Founder & CTO at OODA Health, Inc., Global Chief Data Officer at Barclays Bank. Fayyad was also the first person to hold the Chief Data Officer title when Yahoo acquired his second startup in 2004. There, he built the Strategic Data Solutions group and founded Yahoo Research Labs. He held leadership roles at Microsoft and founded the Machine Learning Systems group at NASA's Jet Propulsion Laboratory. He has published over 100 technical articles, edited two books, holds over 20 patents, and is an ACM and AAAI Fellow. Usama has served on the boards/advisory boards of private and public companies.

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.

Grant Fleming is a Data Scientist at Elder Research. At Elder Research, Grant works on developing, designing, and implementing analytic solutions and educational materials for private and public sector clients. His professional focus is on machine learning for social science applications, model interpretability, civic technology, and building software tools to improve reproducibility in data science.

Bill Franks is the Director of the Center for Statistics and Analytical Research at Kennesaw State University. He is also Chief Analytics Officer for The International Institute For Analytics (IIA) and serves on several corporate advisory boards. Franks is also the author of the books Winning The Room, Taming The Big Data Tidal Wave, The Analytics Revolution, and 97 Things About Ethics Everyone In Data Science Should Know. He is a sought after speaker and frequent blogger who has over the years been ranked a top global big data influencer, a top global artificial intelligence and big data influencer, a top AI influencer, and was an inaugural inductee into the Analytics Hall of Fame. His work, including several years as Chief Analytics Officer for Teradata (NYSE: TDC), has spanned clients in a variety of industries for companies ranging in size from Fortune 100 companies to small non-profit organizations.  You can learn more at http://www.bill-franks.com.

Bala Ganesh leads the Operation Technology, Advanced Technology & Technology Support Groups at UPS. He joined UPS in 2012 as a Program Manager for UPS’s customer technology group. Thereafter he had stints in Global Retail Strategy and the Advanced Analytics & Revenue Management groups.

Prior to joining UPS, Bala was a consultant with McKinsey & Co.  He has also worked as an Aerospace Engineering researcher at the Georgia Institute of Technology.  Early in his career, Ganesh served as a pilot in the Indian Air Force. 

Bala earned a PhD in Aerospace Engineering with a minor in Math along with an MBA from the Georgia Institute of Technology. He graduated from the Indian National Defense Academy and Air Force Academy with his undergraduate degree.

Siddha Ganju, whom Forbes featured in their 30 under 30 list, leads AI innovation in LLM and Guardrails along with the deployment of Medical Instruments for Nvidia partners at Nvidia. Siddha previously worked in the self-driving teams for simulation, perception, scalable training, and inference along with global automotive partnerships and go-to-market strategies.

Bas is a technology leader in the AI and big data domain. His academic background is in Artificial Intelligence and Informatics. Trained as a software engineer and architect, he has 15 years experience in delivering successful data-driven projects with a wide range of companies and technologies. He occasionally teaches programming courses and is a regular speaker on conferences and informal meetings, where he brings a mixture of market context, his own vision, business cases, architecture and source code in an enthusiastic way towards his audience.

Dante is a data scientist at Cape Fear Collective, a non-profit which supports Southeastern North Carolina’s front line organizations in combating poverty, racism, poor health and education outcomes, and socio-economic disparities. In his current role, he builds a Community Data Platform and builds relationships with non-profits, unlocking new potential with data. Prior to his current role at CFC, Dante built data solutions to tackle some of the toughest problems faced by the federal government doing consulting work with Deloitte and Accenture. He lives in Wilmington, North Carolina.

Weiwei is a data science and analytics leader with extensive experience delivering actionable insights and innovative solutions that drive business and system changes through analytics and market research. Currently leading the Research Center of Excellence (COE) team at Zendesk to drive cross-functional collaboration with executives, business, technical teams to achieve effective outcomes at the speed of business. Winner of the Citrix Marketing ACE award and the Analytic 50 award for the innovative use of data and analytics to create and deliver business values.

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.

Michelle Li is a Data Scientist at Paychex and work on predictive modeling, text analytics and business intelligence. Before joining Paychex, Michelle received a PhD degree in Earth Science and spent over 10 years analyzing and modeling data in a variety of fields including satellite imagery, weather prediction, environmental protection, and child welfare.  

James Livingston is a Data Scientist at Paychex where he specializes in implementing machine learning solutions.  James has over 15 years experience in the software, DevOps, and Data Science space with a strong commitment to innovation.  James operates where technology intersects algorithms and enjoys solving data-centric business problems with advanced methods.  James holds a bachelor’s degree in Computer Science and a master’s degree in Data Science from The Rochester Institute of Technology.

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 is founder and director of the applied AI startup Bōwdee. Previously, he led 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, he facilitates outcomes in Customer Retention, Pricing, and other enterprise applications.

Ehsan Mousavi is a Principal Machine Learning Engineer at Apple. He has led teams of engineers and scientists to develop various machine learning-based products in Apple, Uber, and Target. He received his Ph.D. from Stanford University in Operation Research. Dr. Mousavi specializes in deep learning, reinforcement learning, optimization and statistical modeling, and their synergistic application to the problems arising in E-commerce, revenue management, and marketing. 

Sage Murakishi is the Senior Data Scientist at Little Caesars Enterprises where he leads and optimizes reporting, analytics, and data science projects. As a data storyteller, Sage utilizes everything from basic statistics to automated machine learning to explain what happened to what will happen. He has experience using analytics in QSR, insurance, finance, healthcare, and retail.

Sage holds a Bachelor of Arts in Political Science from Michigan State University and a Master of Science Predictive Analytics from Northwestern University.

Sharada Narayanan is a Senior Data Scientist at dotData. Currently working in the ML and Feature Engineering automation technologies, Sharada has worked on multiple projects with large volume and variety of data which generate value for organizations in the Healthcare, Supply chain and Customer Analytics space. She has a passion for educating organizations new to data science to facilitate strategic and quick success in driving data driven decisions.

Ali has joined Twitter since 2019 through the acquisition of Delecta Technologies, a company he had co-founded with his friend. He is a member of the Metrics-team, and is currently the tech-lead for Twitter's user growth modeling and forecasting. Ali has a PhD in AstroPhysics. His PhD was focused on analysing data from the Plack space telescope, a mission led by the European space agency in cooperation with NASA and the Canadian space agency.

Aleks Ontman, PhD, is a Lead Data Scientist and Senior Manager at Deloitte, specializing in data science, algorithms, and advanced analytics with a focus on NLP and Graph Theory. He has over 15 years of experience in academia, industry, and government in the theory and application of most sophisticated and up-to-date machine learning and stochastic modeling to real-world problems building and leading teams ensuring rigor and adoption of best-in-class practices in data preparation, modeling, and performance measurement. Additionally, Aleks is actively engaged in firm and external activities which include algorithm development (in various programming environments, e.g., MATLAB, Java SE, C++), implementation, deployment, and optimization. Aleks has over seven years of consulting experience with strong communication and technical skills which are demonstrated by numerous client projects, firm contributions, and publications.

Ash Pahwa, Ph.D., is an educator, author, entrepreneur, and technology visionary. He is the CEO of A+ Web Services which provides data mining services.

Dr. Pahwa has worked for General Electric, AT&T Bell Laboratories, Xerox Corporation, and Oracle. He founded CD-Gen, Inc. and DV Studio Technologies, LLC., which introduced successful products for CD-Recording (CDR), MPEG encoding, and DVD archiving. His book,CD-Recordable Bible was published in English, Japanese, and German. He is listed in Who's Who in the Frontiers of Science and Technology. He is also a Google Certified Analytics Consultant.

Dr. Pahwa teaches machine learning courses in the University of California system and Chapman University. Since 2008, he taught many courses at UC Irvine, UCLA, and UC San Diego.

Olivia is an expert data scientist, award-winning and best-selling author, and communication coach. Her passion for data science and emotional intelligence guides her quantitative and qualitative research that unveils the relationship between human-centered corporate culture and long-term corporate profits. Olivia's success in data science led to the writing of her international best-seller, Data Mining Cookbook (Wiley 2001). Her research into the need for higher emotional intelligence to thrive in our increasingly complex economy led to her second book, Business Intelligence Success Factors, Aligning for Success in a Global Economy (Wiley/SAS, 2009). Her third book, "Business Analysis Using SAS Enterprise Miner and SAS Enterprise Guide, A Beginner's Guide," highlighted communication and won Best of Show at the Carolina Technical Book competition.

Olivia holds a BA in Mathematics, an MS in Statistics. Clients include Cisco, Clorox, Walmart, Wells Fargo, Genentech, State Farm, Nationwide, Liberty Mutual, Citizen's Bank, HP, IBM, SAS, and Xerox.

George Paslaski has a PhD in Mathematics from LSU and an MBA from University of Richmond. He started his career in statistics, in 1999 at Capital One where he led the Analytic Testing Lab and was instrumental in getting Capital One statisticians to be early adopters of Stochastic Gradient Boosting. He moved to Farmers Insurance in 2007 where he served as the Director of R&D and later as the Director of Growth Analytics. He became the Director of Data Science at DriveTime in January of 2021.

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.

Nikitha Reghu is a Data Science & Analytics Manager at Deloitte. She has over six years of consulting experience leading data science and advanced analytics engagements. Nikitha leads teams to streamline data pipelines, implement natural language processing (NLP) models, and visualize insights in reports and dashboards. She has established data science and analytics workstreams for numerous customers. Additionally, Nikitha leads initiatives that inspire and support women in data and AI roles and careers. 

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.

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.

Tim Shokair is the head of Data Science and Machine Learning Engineering at Conde Nast. Tim has a background in physics and several years academic experience before moving into data science. As a data scientist, Tim has experience in leading data science teams in the entertainment and computer vision spaces and currently oversees work in advertising, user behaviors, and recommendations.

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.

Drew Smith is the Vice President of Global Data and Analytics for Little Caesar Enterprises and Ilitch Holdings where he leads the vision, strategy, and execution of enterprise data and analytics across a diverse array of leading brands in QSR, transport and logistics, food processing, property development, as well as sports and entertainment, with the aim enabling data-driven decisioning.  In his most recent role prior Drew worked for the International Institute for Analytics (IIA) where he led the Analytics Leadership Consortium, working with CDOs, VPs and Directors from Fortune 500 companies across several sectors.  Before the IIA Drew held several positions at IKEA leading: the national commercial analytics functions based in the US HQ, a global divisional analytics function based in the Global Product Development HQ in Sweden, as well as the first global enterprise analytics function based at the Global Retail HQ in the Netherlands.

Drew has a Bachelor’s in History and Political Science from Boston University and an MBA from The Smeal College of Business at Penn State.

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.

Harish Srigiriraju is a Principal Engineer at Verizon and serves as the head of Analytics & Data Science for Verizon Cloud by managing a team of data analysts and data scientists. He leads technology implementation and feature development for Verizon Cloud, one of the biggest products for Verizon. He has expertise in leveraging advanced analytics, data systems and machine learning to improve software products.

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.

Tejaswi Tenneti is a Senior Manager and Tech Lead at Instacart. His team is responsible for building ML models for user intent understanding, neural text modeling and multi-objective ranking for search and recommendation use cases across multiple content types like products and recipes. He graduated with a master's degree in CS from Stanford University with a specialization in Artificial Intelligence. He has over a decade of experience in leading search and discovery efforts across multiple domains like e-commerce, points of interest in maps, job search and enterprise.

Yentai Wan is the Director of Network Planning & Optimization in UPS Corporate Industrial Engineering group. His primary responsibilities are to (a) improve network planning processes, (b) generate network efficiencies and (c) support strategic initiatives across the enterprise. He joined UPS in 2007 as an Enterprise Network Planning Manager in Corporate Transportation.

Yentai was born and raised in Taipei City, Taiwan. He came to US in 2000 for advanced education and received his PhD of Industrial Engineering and Operations Research from Georgia Institute of Technology. He is passionate about applying Operations Research and Machine Learning with real world applications. Yentai is a Industry Advisory Board member of The Georgia Tech Supply Chain and Logistics Institute. 

Director of Analytics & Growth at RingCentral, Fmr Sr. Mgr. Electronic Arts and Director of Data Sciences at WeVideo, Ryan Withop is a three time top conference speaker, specializing in User Behavior, Conversion and Product-Led Growth for subscription services.