Speakers

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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