Naveed Asem is the Chief Data and Analytics Officer and Senior Vice President at Donnelley Financial Solutions (DFIN), a $1.2 billion company that provides software and services to support clients with regulatory reporting, filing, and compliance functions globally.

Naveed joined DFIN in 2016 as the head of data and analytics. He now leads a growing team of data architects, engineers, and data scientists who are focused on creating business value from data through the use of modern data management technologies, analytics and machine learning. The team is not only responsible for the implementation of DFIN’s enterprise data warehouse and data lakes, but they manage everything from data ingestion and curation, to the delivery of reporting, and filing of artifacts with regulatory bodies in the U.S. and EU.

Anasse Bari is a professor of computer science and director of the Predictive Analytics and AI research lab at New York University. Prof. Bari teaches computer science and leads a multidisciplinary research team that designs specialized Artificial Intelligence to help solve problems in healthcare, business, finance, politics and social good.

Leslie Barrett is a Senior Software Engineer at Bloomberg LP's Bloomberg Law division specializing in NLP and Machine Learning applied to legal and government text. Before Bloomberg she was Director of Search Technology at The Ladders Inc, an online resource for executive jobseekers and recruiters. Previously, she was Director of Language Technology at the Financial Times where she managed groups creating new online news search products and electronic news alerts. Leslie holds Ph.D. in Computational Linguistics from New York University. She has over 20 published papers in the fields of Natural Language Processing and Information Retrieval and holds 2 patents. She serves on the Program Committees for the International Conference on Computational Linguistics and Intelligent Text Processing and the International Workshop on Big Data for Financial News.

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.

Richard Boire's experience in predictive analytics and data science dates back to 1983, when he received an MBA from Concordia University in Finance and Statistics. 

His initial experience at organizations such as Reader’s Digest and American Express allowed  him to become a pioneer in the application of predictive modelling technology for all database and CRM type marketing programs. This extended to the introduction of models which targeted the acquisition of new customers based on return on investment.

With this experience, Richard formed his own consulting company back in 1994 which is now called the Boire Filler Group, a Canadian leader in offering  analytical and database services to companies seeking solutions to their existing predictive analytics or database marketing challenges.

Richard is a recognized authority on predictive analytics and is among a very few, select top five experts in this field in Canada, with expertise and knowledge that is difficult, if not impossible to replicate in Canada. This expertise has evolved into international speaking assignments and workshop seminars in the U.S., England, Eastern Europe, and Southeast Asia. 

Within Canada, he gives seminars on segmentation and predictive analytics for such organizations as Canadian Marketing Association (CMA), Direct Marketing News, Direct Marketing Association Toronto, Association for Advanced Relationship Marketing (AARM) and Predictive Analytics World (PAW).  His written articles have appeared in numerous Canadian  publications such as  Direct Marketing News, Strategy Magazine, and Marketing Magazine. He has taught applied statistics, data mining and database marketing at a variety of institutions across Canada which include University of Toronto, George Brown College, Seneca College, and currently Centennial College. Richard was  Chair at the CMA's Customer Insight and Analytics Committee and  sat on the CMA's Board of Directors from 2009-2012. He has chaired numerous full day conferences on behalf of the CMA (the 2000 Database and Technology Seminar as well as the  2002 Database and Technology Seminar and the first-ever Customer Profitability Conference  in 2005. He has most recently chaired the Predictive Analytics World conferences in both 2013 and 2014 which were held in Toronto.

He has co-authored white papers on the following topics: "Best Practices in Data Mining" as well as "Customer Profitability:  The State of Evolution among Canadian Companies."  In Oct. of 2014, his new book on "Data Mining for Managers-How to use Data (Big and Small) to Solve Business Problems" was published by Palgrave Macmillian.  In March of 2016, Boire Filler Group was acquired by Environics Analytics where his current role is senior vice-president of innovation.

Chakri Cherukuri is a senior researcher in the Quantitative Financial Research Group at Bloomberg LP in NYC. His research interests include quantitative portfolio management, algorithmic trading strategies, and applied machine learning. He has extensive experience in scientific computing and software development. Previously, he built analytical tools for the trading desks at Goldman Sachs and Lehman Brothers. He holds an undergraduate degree in mechanical engineering from the Indian Institute of Technology (IIT) Madras, India, and an MS in computational finance from Carnegie Mellon University.

Christian Elsasser is part of Swiss Re's P&C (Property & Casualty) Analytics unit that focusses on delivering data-analytics services and solutions to insurers. In his role he is managing projects that support Swiss Re's clients with data-driven insights – both for Personal Lines and Commercial Lines – based on external as well as internal data sets and analytics methods. In addition, he is responsible for the identification of new needs and opportunities of insurers in the area of data analytics and hence to define the strategy of the P&C Analytics unit.

Before joining Swiss Re he worked for five years at CERN as a physicist where he was responsible for the analysis and interpretation of data samples collected by the Large Hadron Collider (LHC).

Christian studied physics, economics, and computer science and holds an MSc degree from the University of Zurich. For his research at CERN he was awarded a PhD in natural science. He is currently also appointed as a lecturer in scientific computing and data analytics by the University of Zurich.

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.

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.

Keith Higdon serves as President of ESIS, Inc., with overall management responsibility for this business. He is based in Chicago.

ESIS is one of the industry’s oldest and largest risk management services companies, providing claim and risk management services to a wide variety of commercial clients in the U.S. and globally. ESIS maintains a sharp focus on helping its clients manage their total cost of loss, offering comprehensive and flexible programs and innovative approaches to claims administration. ESIS is committed to achieving measurable results through consistently superior execution, and employing data analytic and predictive modelling capabilities to track progress.

Previously, Mr. Higdon served as Senior Vice President of Partnership Services for ESIS where he oversaw the management and development of client partnerships across all ESIS lines of business. In addition, he has accountability for new client implementations, ESIS University, ESIS construction practice, and ESIS global initiatives. 

Mr. Higdon has 20 years of industry experience. He began his career in consulting conducting and managing auditing, program evaluation, and program design projects for workers compensation and integrated disability management programs to large employers and service providers. He left consulting for the third-party administrator (TPA) space where he held a variety of positions under information technology and client services developing and delivering differentiated products and services to clients. With a strong focus on information delivery, his previous TPA experience culminated in the management of four departments focusing on client reporting, predictive modeling, client-facing system enhancement and support, and loss control consulting and OSHA administration. Mr. Higdon holds two Bachelor of Science degrees in the social sciences from Northern Illinois University and a master’s degree in information technology and management from Illinois Institute of Technology. He is a board member, and former Chairman, for the Center for Employee Health Studies associated with the School of Public Health at the University of Illinois at Chicago. Mr. Higdon supports industry development through participation in regional and national conferences and has published on key topics including integrated disability management, the data lifecycle, and predictive modeling over the years. He is also a volunteer mentor and guest speaker at YearUp, a community college based program for economically disadvantaged students.

Connor is a Senior Data Scientist at Wells Fargo and led AI projects around credit card collections and fraud detection. Before Wells Fargo, he was a researcher at the National Science Foundation: Center for e-Design and worked on industrial/ manufacturing focused machine learning research projects with Boeing, John Deere, GE, and other companies. Connor holds a Ph.D. in Industrial Engineering from Pennsylvania State University. He also holds B.S. degrees in Industrial and Manufacturing Systems Engineering and Economics and a M.S. degree in Industrial Engineering from Iowa State University.

Abhishek Joshi ‘AJ’ is a Sr. Director in Visa’s consulting & analytics group. He is responsible for helping financial institutions with improving growth and profitability through advanced analytics techniques. AJ has diverse experience in employing analytics to solve business problems across multiple industries – Manufacturing & Engineering, Financial Services and Telecom. 

Seasoned industry recognized Data Analytics leader with over 25 years of experience in Information Management, Analytics and Enterprise Architecture Leadership. As Technology Leader and Head of Data Management delivered results for Fortune 100 Insurance, Financial Services and Retail companies. Proven track record of running complex IT operations, providing innovative solutions and developing business aligned strategies. Core expertise spans running Enterprise Architecture, Information Strategy, Business Intelligence and Master Data Management. 

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.

Richard Lee is Director of Data Science for John Hancock, the U.S. division of Toronto-based Manulife.

Richard leads the Advanced Analytics & AI group, which supports operations decision analytics across all U.S. businesses.

In his current role, Richard finds opportunities for efficiencies in Life Insurance as well as Long Term Care Insurance operations. Much of his focus is on innovation to enhance the relevance and understanding of analytics and its impact on operations decision-making.

Prior to his current role, Richard has spent 15 years at John Hancock in various analytics roles

Victor S.Y. Lo is a seasoned Big Data, Marketing, Risk, and Finance leader with over 25 years of extensive consulting and corporate experience employing data-driven solutions in a wide variety of business areas, including Customer Relationship Management, Market Research, Advertising Strategy, Risk Management, Financial Econometrics, Insurance, Product Development, Transportation, and Human Resources. He is actively engaged with causal inference and is a pioneer of Uplift/True-lift modeling, a key subfield of data science.

Victor has managed teams of quantitative analysts in multiple organizations. He currently leads the AI and Data Science Center of Excellence, Workplace Investing at Fidelity Investments. Previously he managed advanced analytics/data science teams in Personal Investing, Corporate Treasury, Managerial Finance, and Healthcare and Total Well-being at Fidelity Investments. Prior to Fidelity, he was VP and Manager of Modeling and Analysis at FleetBoston Financial (now Bank of America), and Senior Associate at Mercer Management Consulting (now Oliver Wyman).

For academic services, Victor has been a visiting research fellow and corporate executive-in-residence at Bentley University. He has also been serving on the steering committee of the Boston Chapter of the Institute for Operations Research and the Management Sciences (INFORMS) and on the editorial board for two academic journals. He is also an elected board member of the National Institute of Statistical Sciences (NISS). Victor earned a master’s degree in Operational Research and a PhD in Statistics, and was a Postdoctoral Fellow in Management Science. He has co-authored a graduate level econometrics book and published numerous articles in Data Mining, Marketing, Statistics, Analytics, and Management Science literature, and is completing a graduate level book on causal inference in business.

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.

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.

Andreas is an Executive Director at Goldman Sachs Quantitative Execution Services, focusing on signal research for execution algorithms. Andreas has received a PhD in Information Engineering at the University of Cambridge, working on the interface of stochastic control theory and Bayesian machine learning. Andreas also holds a BA and an MEng degree in Electrical and Information Sciences from Trinity College, University of Cambridge, during which he has received the G-Research and TTP awards.

Mohammad is currently a Senior Data & Applied Scientist at Microsoft, and Instructor at Stanford University. He is a former Data Scientist at Apple and previously worked for Samsung, Bosch, General Electric and UCLA Research Labs. He received a PhD in Computer Science from the University of California, Riverside and B.Sc. from University of Tehran. Mohammad is the author of the book, ‘Applications of Mining Massive Time Series Data'. He has also been a keynote speaker at more than 40 Data Summits/Conferences around the globe. 

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.

Michael Steliaros is the global head of Quantitative Execution Services at Goldman Sachs. He is responsible for the research, development and implementation of quantitative processes for portfolio and electronic trading as well as managing the bank's relations with the quantitative client base. Previously, Michael held a variety of senior roles at BofAML in London and New York, most recently running the global agency portfolio trading and quantitative equity businesses. Earlier in his career, he spent a decade on the buy-side (most notably BGI and Winton) building quant stock-selection models and managing global market neutral equity portfolios. Michael received a bachelor's degree in Economics & Econometrics from the University of Nottingham, and an MSc and PhD in Finance from City University (CASS) Business School in London.

Bill joined Safety National in 2008, held several different positions within Safety National, in pricing, product development, reserving and risk until being named Senior Vice President, Advance Analytics and Practical Applications in 2023. Bill’s focus is on research and strategic use of third party data, creating innovative predictive analytics capabilities via new tools, new technology and insurtech capabilities to build a pipeline of projects for the Data Analytics department to develop and operationalize.

Prior to joining Safety National, Bill held various executive actuarial roles with global and regional carriers. Bill has been a speaker or panelist at various insurance and tech industry conferences and has contributed to articles on industry-related topics. Bill chaired the American Property Casualty Insurance Association ERM Committee 2022-2023.