Organizing Committee:
Giulia Fanti
Giulia Fanti is an Assistant Professor of Electrical and Computer Engineering at Carnegie Mellon University. Her research interests span the security, privacy, and efficiency of distributed systems, with a focus on synthetic data generation. She has co-organized several conferences and workshops in the past, including as Workshop Chair for NDSS (2018-2019) and a Co-Organizer of the Synthetic Data for AI in Finance Workshop at ICAIF 2022. She has won multiple awards and is a member of NIST’s Information Security and Privacy Advisory Board. She is also a founding co-director of CyLab Africa alongside Assane Gueye.
Links to: Website, Email, Google Scholar
Guang Cheng
Guang Cheng is a Professor of Statistics and Data Science and Director of the Trustworthy AI Lab at UCLA. He received his BA in Economics from Tsinghua University in 2002, and PhD in Statistics from University of Wisconsin-Madison in 2006. His research interests include trustworthy AI, synthetic data and statistical machine learning. Cheng is an Institute of Mathematical Statistics Fellow, Simons Fellow in Mathematics, NSF CAREER awardee and was also a member in the Institute for Advanced Study, Princeton. Other than government grants, his lab is also sponsored by industry funding from such as Amazon, Meta and Adobe.
Links to: Website, Email, LinkedIn
Ali Hirsa
Ali Hirsa is a Professor, director of the Center for Artificial Intelligence in Business Analytics and Financial Technology, and director of the Financial Engineering Program at Columbia University in the City of New York. He is also Chief Scientific Officer at ASK2.ai and Managing Partner at Sauma Capital, LLC, a New York Hedge Fund.
Previously, he was Managing Director and Global Head of Quantitative Strategies at DV Trading and a Partner and Head of Analytical Trading Strategy at Caspian Capital Management, LLC. Ali has worked in a variety of quantitative positions at Morgan Stanley, Banc of America Securities, and Prudential Securities.
Ali is the author of “Computational Methods in Finance,” second edition, Chapman & Hall/CRC 2024, co-author of “An Introduction to Mathematics of Financial Derivatives,” third edition, Academic Press, and the editor-in-chief of the Journal of Investment Strategies. He is a frequent speaker at academic and practitioner conferences.
Ali received his PhD in Applied Mathematics from the University of Maryland at College Park under the supervision of Professors Howard C. Elman and Dilip B. Madan.
Links to: Website
Youssef Mroueh
Youssef Mroueh is a Principal Research Scientist in IBM since April 2015. He received his PhD in computer science in February 2015 from MIT, CSAIL, where he was advised by Professor Tomaso Poggio.
In 2011, he obtained his engineering diploma from Ecole Polytechnique Paris France, and a master of science in Applied Maths from Ecole des Mines de Paris.
He is interested in Deep Learning, synthetic data, Machine Learning, Optimal transport, multimodal learning, Statistical Learning Theory, Computer Vision and Artificial Intelligence.
Links to: Website
Robert E. Tillman
Robert Tillman is Senior Research Director, Optum AI, UnitedHealth Group, where he leads AI and disease prediction and AI for, clinical trials optimization. In synthetic data, Robert’s team is currently focused on data imputation and augmentation challenges with electronic healthcare records and synthesizing privacy-preserving longitudinal medical claims and electronic healthcare records. Other research includes developing large language foundation models for sequential healthcare data that can be applied to a range of disease prediction tasks and learning optimal synthetic control arms and digital twins for clinical trials. Previously, Robert was Research Director for Synthetic Data at J.P. Morgan AI Research and Head of Machine Learning at Index Exchange, a supply side ad exchange. He received his Ph.D. from Carnegie Mellon in 2011 where his dissertation research focused on causal inference and probabilistic graphical models.
Previous experience: Organizing committee for KDD 2023 Open Society Day, Organizing committee for the second Synthetic Data Finance Workshop in ICAIF 2023
Links to: Email, Website, DBLP
Vamsi K. Potluru (Designated Contact)
Vamsi Potluru is a Research Director at JP Morgan AI Research where he leads synthetic data research. Projects include high quality synthetic data for various financial problems such as credit card marketing, anti-money laundering detection and fair lending. Previously, he was a lead researcher at Comcast working on various projects in recommendations, search and speech domains involving sketching and bandit approaches among others. Prior to that he was a postdoctoral research fellow at Rutgers University after having obtained his PhD in matrix factorizations applied to brain imaging data.
Links to: Website, Email, Google Scholar, LinkedIn
Saheed Obitayo (Webmaster)
Saheed is a Senior AI Research Associate at J.P Morgan AI research. His research interests lie around statistical data analysis, modelling, and synthetic data generation. Prior to joining J.P Morgan, Saheed worked at Apple focusing on geospatial statistics & analysis and Maps data QA. Saheed holds a master’s degree in Geophysical Engineering & Applied Mathematics from Texas Tech University and a fellowship at Rice University with a concentration in Data Visualization & Analytics.