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).

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.

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.

Peggy is a Fellow of the Casualty Actuarial Society, a Member of the American Academy of Actuaries, and a Principal and Consulting Actuary with Milliman.  She has 30 years of experience in the insurance industry specializing in predictive model development and review, including the development of models for use in ratemaking, underwriting, retention, and other operational uses for homeowners, residential property, and commercial insurance, using a variety of data sources and predictive modeling techniques. Prior to joining Milliman, Peggy was Director of Analytics and Insights at the Allstate Research and Planning Center in Menlo Park, California. 

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.

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.

Dr. Om Deshmukh is Head of Data Sciences and Innovation at Envestnet. Om and team drive foundational data sciences initiatives to mine actionable insights from the peta-bytes of data that flows through their network. Om is a Ph.D. in Machine Learning from University of Maryland, College Park. He has 50+ international publications (several best paper awards) and 50+ patents (filed/granted). In 2019, his data science team at Envestnet-Yodlee was recognized as one of the top 10 data science teams to work at in India. In 2017, he was recognized as one of the top 10 data scientists in India.  His team won the Govt of India National Award for the Best Accessible Technology (2008). He spent close to a decade in IBM Research and Xerox Research driving various state-of-the-art Machine Learning initiatives for global technical research, technology strategy and start-up partnerships. 

Om is a well-known Machine Learning and Data Sciences authority in industry and academia, with several active collaborations across leading academic and not-for-profit institutions.

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.

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.

Hussain Jiwani is quantitative analyst at CHS Inc. He has been with CHS since 2014. He is responsible for developing analytics and forecasting models to improve profitability and manage risk across several fronts. Hussain's demonstrated ability to extrapolate and interpret vast amounts of data adds tremendous value to CHS, its owners and customers.

His work experience is broad and deep, from fixed income and equity derivatives to futures and options. Prior to joining CHS, he spent 11 years as a senior quantitative research analyst with Waterstone Capital Management, Plymouth, Minn., where his research and risk management analysis on convertible and distressed bonds helped fuel the startup hedge funds growth from under $100 million to $1.5 billion. He also held quantitative research analyst positions with DRW Trading Group and JPMorgan Chase.

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.

Carrie (Caimei) Lu is a Senior Data Scientist at Safety National Safety National Casualty Corporation. She has worked in data science domain for over 10 years. She is an expert of using data analytics and machine learning technologies to generate business insights from large amounts of industry data, and solve challenging business problems where data holds the key. At Safety National, Carrie Lu works with insurance business stakeholders to improve and optimize claim and underwriting operations by applying predictive models developed on internal and external insurance data. Carrie Lu holds Ph.D. in Information Science from Drexel University. She has over 15 published papers in the fields of Data Mining and Machine Learning.

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.

Julia is a Fraud Detection and Risk Management expert, innovator, startup advisor, mentor and a speaker. Currently she is a Product lead at Walmart Global tech focusing on mitigating fraud for Mobile payments and Marketplace. Prior to this, Julia worked with Fiserv, Signifyd, ThreatMetrix, LexisNexis Risk Solutions and helped Fortune 50 Tech and E-Commerce companies such as Microsoft, Intuit, Ebay, Chegg and others to save millions of dollars in fraud losses.

Julia holds a Bachelor’s Degree in Sociology and Geography from the Hebrew University of Jerusalem, Software Programming Certificate from John Bryce Institute, MBA from HaUniversita Ha-Ptuha of Israel, and Strategic Decision and Risk Management Diploma from Stanford University.

Roosevelt Mosley is a principal and consulting actuary with Pinnacle Actuarial Resources and has been in the property/casualty industry since 1994. His skill set includes predictive analytics applications for all insurance functions, ratemaking and product development, competitive analysis and litigation support.

He has served as a member of the Casualty Actuarial Society’s (CAS) and Society of Actuaries’ Joint Committee on Inclusion, Equity and Diversity, the board of trustees of the Actuarial Foundation and the CAS Public Relations Advisory Committee. He has also served as a member of the American Academy of Actuaries (AAA) Racial Equity Task Force.

He is the current president-elect of the CAS, has served as vice president of marketing and communications and on the board of directors of CAS, a member of the board of directors of the International Association of Black Actuaries Foundation, and a member of CAS and AAA governance task forces. 

Mei Najim currently works as an Applied Analytics Manager at HSBC and teaches part-time as a Data Analytics Lecturer at University of Chicago. Mei has over 18 years of hands-on analytics experience in banking (collections, agent performance, and financial crime), insurance (claim management, underwriting, pricing, reserving, and catastrophe risk management), and consulting.

Since 2007, Mei has mainly been working, leading, and implementing various large scale data analytics and predictive analytics projects to develop analytics capability for financial organizations. She has extensive statistics, machine learning, and data mining experience dealing with large and complex data sets.  She is an analytics thought leader with a positive influence and a clear vision for how analytics can transform business strategy through techniques, communication, and leadership to devise innovative data-driven solutions. 
Mei has been a frequent speaker at various industry conferences to share her expertise in predictive analytics, machine learning, and data science. She holds a BS in actuarial science from Hunan University and two MS degrees in applied mathematics and in statistics, from Washington State University. She is a member of the American Statistical Association and a Certified Specialist in Predictive Analytics (CSPA) of the Casualty Actuarial Society.

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.

Tope is an Actuary at Safety National Casualty Corporation, where he works in Enterprise Risk Management (ERM). In addition to his ERM work, Tope has also worked on Safety Nationals IFRS Implementation team, providing actuarial support, developing illustrative models for internal documentation and reference purposes, and contributing to the teams data quality effort. In prior roles at MetLife and Assurant Employee Benefits, Tope worked in Asset-Liability Management (ALM), Deferred Acquisition Costs (DAC), and Financial Reporting. Tope is an Associate of the Society of Actuaries (ASA) and holds a M.S. degree in Applied Mathematics from the University of Missouri Columbia.

Ted is a tech generalist, inventor and practitioner of ML and DS, with experience in robotics and a background in Mechanical Engineering. He currently works at Google in Cloud Trust and Safety, where he uses his skills to help the platform enhance customer trust while preventing fraud and abuse. No matter if he is working on the factory floor, the lab or the office, Ted seeks opportunities to grow a business by applying technology in novel ways.

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.

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.

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).

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.

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. 

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.