Speakers

Ali Hirsa is a Professor of Professional in the Department of Industrial Engineering and Operations research at Columbia University. He received his PhD in Applied Mathematics from the University of Maryland at College Park. He is also the Chief Scientific Officer ASK2.ai and Managing Partner at Sauma Capital, LLC, a New York Hedge Fund. Previously Ali was Managing Director and Global Head of Quantitative Strategy at DV Trading, LLC, and a Partner and Head of Analytical Trading Strategy at Caspian Capital Management, LLC. Prior to joining Caspian, he worked in a variety of quantitative positions at Morgan Stanley, Banc of America Securities, and Prudential Securities. Ali was also a Fellow at Courant Institute of New York University in the Mathematics of Finance Program from 2004 to 2014. His research interests are algorithmic trading, machine learning, deep learning, data mining, optimization, and computational and quantitative finance. His focus has been on machine learning applications in finance, specifically in asset management, and also on developing learning algorithms for signal extraction from data.

Steven Wu is an Assistant Professor in the School of Computer Science at Carnegie Mellon University with an appointment in the Institute for Software Research and affiliated appointments with thr Machine Learning Department and the Human-Computer Interaction Institute. Prior to joining CMU's faculty, Wu received a Ph.D. in Computer Science in 2017 from the University of Pennsylvania. where his doctoral dissertation titled, “Data Privacy Beyond Differential Privacy” received Penn’s Morris and Dorothy Rubinoff Award for best thesis. Before joining CMU, he was an assistant professor of computer science and engineering  at the University of Minnesota for two years. Before that, Wu spent a year as a post-doctoral researcher at Microsoft Research-New York City in the machine learning and algorithmic economics groups. Wu works on algorithms and machine learning. His recent work focuses on how to make machine learning better aligned with societal values, especially privacy and fairness, and how to make machine learning more reliable and robust when algorithms interact social and economic dynamics. He studies these questions using methods and models from machine learning, statistics, optimization, differential privacy, game theory, and mechanism design.

Youssef Mroueh is a research staff member 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, Machine Learning, Optimal transport, multimodal learning, Statistical Learning Theory, Computer Vision and Artificial Intelligence. 

Breann Zickafoose is an Executive Director & Assistant General Counsel at JPMorgan Chase & Co. Prior to that, Breann received her JD in law at University of Dayton.

Irina Moore is an executive with 20 years of experience in the financial services industry, specializing in quantitative modeling and financial analysis. She has a strong track record of leading technical talent and translating quantitative research into business decisions. Irina is an effective leader who excels in building from scratch or turning around complex organizations, motivating teams, and driving change. Her areas of expertise include financial and quantitative modeling, asset valuation and investment analysis, statistical analysis, stress testing and capital planning, economic capital modeling, and decisions under uncertainty. She has held various leadership positions at JPMorgan Chase & Co., GE Capital, and GE Aerospace.

Sharone Hutterer is an Accomplished Data Protection Leader with experience in the design and implementation of effective and efficient processes to manage data protection risks. Sharone currently is a Data Privacy Risk Executive Director at JPMorgan Chase & Co.

Maarten Van Segbroeck is a principal scientist at Gretel.ai. He received his PhD in electrical engineering in 2010 from KU Leuven. He is interested in signal processing, Machine Learning and and Artificial Intelligence. 

Tobias Hann joined MOSTLY AI in 2019 and became CEO in 2020. He is a technology enthusiast with a deep technical understanding of software, data and machine learning, and has a passion for customer centricity and innovative product development. Tobias holds a PhD from the Vienna University of Economics and Business, and an MBA from the Haas School of Business, UC Berkeley, and is currently based in New York. Prior to joining MOSTLY AI, he worked as a management consultant with the Boston Consulting Group and as Co-Founder/MD of three start-ups. Tobias’ leadership and consulting experience spans 15 years in the US, Europe, and the Middle East, across diverse industries including enterprise software, insurance, transportation, education, and telecommunication.