The AAAI-2023 Workshop on
Multimodal AI for Financial Forecasting

Feb 14, 2023: 8:30 AM-12:30 PM

Location: Washington DC, USA

MANUELA M. VELOSO, J.P. Morgan AI Research

Bio

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 and 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.

Dr. Veloso is on leave from Carnegie Mellon University as the Herbert A. Simon University Professor in the School of Computer Science, and the past Head of the Machine Learning Department. With her students, she had led research in AI, with a focus on robotics and machine learning, having concretely researched and developed a variety of autonomous robots, including teams of soccer robots, and mobile service robots. Her robot soccer teams have been RoboCup world champions several times, and the CoBot mobile robots have autonomously navigated for more than 1,000km in university buildings. Dr. Veloso is the Past President of AAAI, (the Association for the Advancement of Artificial Intelligence), and the co-founder, Trustee, and Past President of RoboCup. Professor Veloso has been recognized with a multiple honors, including being a Fellow of the ACM, IEEE, AAAS, and AAAI. She is the recipient of several best paper awards, the Einstein Chair of the Chinese Academy of Science, the ACM/SIGART Autonomous Agents Research Award, an NSF Career Award, and the Allen Newell Medal for Excellence in Research. Dr. Veloso earned a Bachelor and Master of Science degrees in Electrical and Computer Engineering from Instituto Superior Tecnico in Lisbon, Portugal, a Master of Arts in Computer Science from Boston University, and Master of Science and PhD in Computer Science from Carnegie Mellon University.

More information on the work can be found here.

RUIMENG HU, University of California, Santa Barbara

Bio

Prof. Ruimeng Hu is an Assistant Professor at the University of California, Santa Barbara, with a joint appointment in Mathematics and Statistics and Applied Probability. Before this, she worked at the Columbia University as a Term Assistant Professor.

Prof. Hu's current research interests lie in the interdisciplinary area of machine learning, financial mathematics, and game theory. She specializes in mathematical deep learning, reinforcement learning, mean-field games on networks, portfolio optimization under stochastic environments, multiscale modeling in financial markets, systemic, sequential algorithm design and its application to stochastic control problems, and stochastic partial differential equations.

More information on the work can be found here.

MIHAI CUCURINGU, University of Oxford

Bio

Prof. Mihai Cucuringu is an Associate Professor in the Department of Statistics, and an Affiliate Faculty in the Mathematical Institute at University of Oxford. He is also a Stipendiary Lecturer in Statistics at Merton College, University of Oxford, and a Turing Fellow at The Alan Turing Institute in London.

Prof. Mihai Cucuringu is interested in the development and mathematical & statistical analysis of algorithms for data science, network analysis, and certain computationally-hard inverse problems on large graphs, with applications to various problems in machine learning, statistics, finance, and engineering, often with an eye towards extracting structure from time-dependent data which can be subsequently leveraged for prediction purposes.

More information on the work can be found here.

GAUTAM SHROFF, TCS Research India

Bio

Dr. Gautam Shroff is Vice President and Chief Scientist in Tata Consultancy Services and heads TCS Research. He has published over 90 research papers in the areas of computational mathematics, parallel computation, distributed systems, software architecture, software engineering, big data, information fusion, virtual reality as well as artificial intelligence including machine learning, deep learning, Bayesian inference and natural language processing.

Dr. Gautam Shroff completed his B.Tech degree in Electrical Engineering from IIT Kanpur in 1985, and Ph.D in Computer Science from Rensselaer Polytechnic Institute Troy, NY in 1990. Dr. Shroff had been on the faculty of the California Institute of Technology, Pasadena, USA (1990 - 91) and thereafter of the Department of Computer Science and Engineering at Indian Institute of Technology, Delhi, India (1991 - 1997). He has also held visiting positions at NASA Ames Research Center in Mountain View, CA, and at Argonne National Labs in Chicago.

More information on the work can be found here.

IVO VIGAN, Bloomberg

Bio

Dr. Ivo Vigan is a Senior ML Researcher & a Team Lead in Bloomberg’s AI Engineering group. For the past seven years, he has been building products at Bloomberg that apply natural language processing and machine learning technologies to the financial domain. He holds a Ph.D. in theoretical computer science from the City University of New York on a Fulbright scholarship.

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