CMU NYC Tech & Entrepreneurship and Liquidnet Panel
present a panel discussion on effective implementation of AI addressing the following questions:
How can companies effectively implement AI across the firm, within the division, or even within a group.
How do you build an effective AI/ML team?
Where is AI/ML already implemented and what could it look like in 5 years?
Register by Thursday, September 19 via
6-6:30 p.m. Registration and Check-in
6:30-7:30 p.m. Panel Discussion (45 min), Q&A (15 min)
7:30-8 p.m. Networking
Panel Speakers: Andrew Arnold, Tom Doris, Manuela Veloso
Moderator: Evan Schnidman
Andrew Arnold (CS 2007, 2009) works on robust machine learning at Google Research, New York, & serves as an Adjunct Professor at New York University where he lectures on machine learning & natural language processing applied to quantitative trading & finance. Previously, he was a portfolio manager & research director at Cubist Systematic Strategies, applying machine learning to quantitative trading. Before that, he was variously a hedge fund cofounder, chief technology officer, quantitative portfolio manager, machine learning researcher & software engineer at Ophir Partners, Trexquant, WorldQuant, Merrill Lynch, Microsoft Research, IBM Research, Google & Bloomberg. He received his PhD in machine learning from Carnegie Mellon University & his BA in computer science from Columbia University.
Tom Doris, CEO of OTAS Technologies & Chief Data Scientist at Liquidnet. Tom leads Liquidnet's R&D program exploring the application of AI, machine learning & alternative data to the investment process. He is responsible for product development of OTAS, the market data analytics platform & realtime microstructure analysis & trading optimization platform, products used by the top global institutions & hedge funds worldwide to enhance decision making & improve performance. He holds a Ph.D in computer science for work in computational neuroscience.
Evan Schnidman, Ph.D., Founder & CEO, Prattle, a Liquidnet Company. Before starting Prattle, Evan taught at Brown University and Harvard University. Co-author of How the Fed Moves Markets, Evan is also widely published in macroeconomics, political economy, and finance publications. Along with being a respected academic, author, & researcher, Evan is also an experienced consultant for large corporations and financial institutions.
Manuela Veloso, Ph.D., (CS 1989, 1992) Managing Director, Head of AI Research, J.P. Morgan Manuela M. Veloso is the Head of J.P. Morgan AI Research, which pursues fundamental research in areas of core relevance to financial services, including data mining & cryptography, machine learning, explainability, and human-AI interaction. J.P. Morgan AI Research partners with applied data analytics teams across the firm as well as with leading academic institutions globally.
Professor Veloso is on leave from Carnegie Mellon University as the Herbert A. Simon University Professor in the School of Computer Science, & the past Head of the Machine Learning Department. With her students, she had led research in AI (robotics & machine learning). Professor Veloso is the Past President of AAAI, (Association for the Advancement of AI), & the co-founder, Trustee, & Past President of RoboCup. She is the receipient of the Einstein Chair of the Chinese Academy of Science, ACM/SIGART Autonomous Agents Research Award, an NSF Career Award, and Allen Newell Medal for Excellence in Research. Professor Veloso earned a BS & MS degrees in Electrical & Computer Engineering from Instituto Superior Tecnico in Lisbon, Portugal, a MA in Computer Science from Boston University, and MS & PhD in Computer Science from Carnegie Mellon University.
$5 per person.
This evening is generously hosted by Liquidnet.
Proceeds go towards future NY Tech and Entrepreneurship events.