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Artificial Intelligence Research
About
Our AI Research team is comprised of experts in various fields of AI. They pursue primary research in areas relative to our research pillars as well as concrete problems related to financial services. They partner with various internal teams to accelerate the adoption of AI within the firm. They also work with leading faculty around the world on areas of mutual interest.

Manuela Veloso, PhD
Head of AI Research, JPMorgan Chase & Co.
Dr. Manuela M. Veloso is the firmwide Head of 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. The team 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, 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.
Professor Veloso is the Past President of AAAI, 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 AAAI, AAAS, ACM, IEEE. 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.

Sameena Shah, PhD
AI Research Director
Dr. Sameena Shah is a Managing Director in the AI Research organization at J.P. Morgan. She is a highly accomplished technology leader with over 20 years of educational and industry experience in engineering, AI, and leading development teams that created top AI technologies in the world for financial, news, commodities and legal businesses.
Previously, Sameena was Managing Director, Head of Data Science at S&P Global Ratings where she led the firm’s strategy and development for Augmented Intelligence. Prior to that, Sameena worked at Thomson Reuters for seven years in roles of increasing responsibility that involved building state of the art AI systems that resulted in business growth and operational efficiencies. Sameena is also the Founder and CEO of Aylan Analytics LLC, and has worked at Yahoo! Research, a NYC based hedge fund, an International hedge fund, and a global startup.
Sameena has a PhD in Distributed Machine Learning and a Masters in Computer Science from IIT Delhi. She is the winner of the top PhD in the country award, Cloudera top AI/ML application award, several best paper awards and recognitions. She has contributed 41 Publications, and 11 Patents

Tucker Balch, PhD
AI Research Director
Dr. Balch is a Research Director at J.P. Morgan AI Research and a professor of Interactive Computing at Georgia Tech (on leave). He is interested in problems concerning multi-agent social behavior in domains ranging from financial markets to tracking and modeling the behavior of ants, honeybees and monkeys. He co-founded Lucena Research, an investment software firm that applies Machine Learning and Big Data approaches to investment problems. Balch has published 120 peer-reviewed articles.
His work has been covered by the Wall Street Journal, CNN, New Scientist, Institutional Investor, and the New York Times. His graduated students work at NASA/JPL, Boston Dynamics, Goldman Sachs, Morgan Stanley, Citadel, AQR, and BlackRock. Before his career in computing, Tucker was an F-15 pilot in the US Air Force.

Daniele Magazzeni, PhD
AI Research Director
Dr. Daniele Magazzeni is a Research Director at J.P. Morgan AI Research and he is the Head of the firmwide Explainable AI Center of Excellence. His main research interests are in AI Planning and ML for efficient resource allocation and processes optimization, and Explainable AI.
Daniele is the current President of the International Conference on Automated Planning and Scheduling (ICAPS).
Daniele is Associate Professor (on leave) at King’s College London, where he was Co-Director of the UK Center for Doctoral Training in Safe and Trusted AI, and Head of the Human-AI-Teaming Lab.
He is a frequent tutorial and keynote speaker at AI Conferences.

Andrea Stefanucci
Head of Product Management, AI Research at J.P. Morgan
Andrea Stefanucci is Head of Product Management, AI Research at J.P. Morgan in the New York office. Andrea has 15 years of experience in strategy, innovation, AI and product management in the financial services industry.
Previously, Andrea was a Senior Engagement Manager at McKinsey and Company, providing strategic consulting to some of the world’s largest financial institutions. Prior to that, Andrea worked at Samsung, Bain and Accenture in internal strategy, innovation and management consulting roles.
Andrea holds an MS in Computer Engineering from University of Pisa and an MBA from INSEAD.

Daniel Borrajo, PhD
AI Research Director
Dr. Daniel Borrajo is a Research Director at J.P. Morgan AI Research. He is also a Professor at Universidad Carlos III de Madrid (on leave), where he was Head of the Computer Science Department and Head of the Planning and Learning Group.
He has more than 35 years of experience of work on AI, from the research side as well as developing AI solutions for companies. His main research interests are in the integration of the two main AI paradigms: model-based (e.g. AI Planning) and model-free (e.g. Machine learning).
He has been Program Chair of AI-related international conferences, regularly serves in the program committee of leading international AI conferences, and he is currently Associate Editor of the Artificial Intelligence Journal.

Jessica Staddon, PhD
AI Research Director
Dr. Jessica Staddon is a Research Director at J. P. Morgan AI Research. Dr. Staddon has spent more than 20 years leading teams at Google, Xerox PARC, Bell Labs and RSA Labs in security, privacy and safety research. Most recently at Google she worked on enterprise tools for security, analytics and compliance, and tools for enforcing YouTube content policies and ads quality.
Dr. Staddon frequently serves on the program committees of leading security conferences, is the co-editor of the SocioTechnical Department of IEEE Security & Privacy magazine and co-founded the AISec Workshop that has been running for more than 14 years. She is an adjunct professor in the Computer Science Department of N. C. State and holds more than 35 patents. Her PhD is in mathematics from UC Berkeley.

Sumitra Ganesh, PhD
AI Research Director
Dr Sumitra Ganesh leads the Multi-agent Learning & Simulation group at JPMorgan AI Research. Her team’s research focuses on modeling complex economic systems, efficient policy learning and mechanism design. Sumitra has led the development of a multi-agent simulation platform that uses reinforcement learning to learn agent behaviors in a scalable manner. The simulation platform developed by her team is being used across multiple use cases (market simulation, operational processes, consumer loan markets) for counterfactual analysis and strategy optimization.
Prior to joining AI Research, Sumitra led the X-asset Client Intelligence team in the Corporate & Investment Bank at J.P.Morgan where she worked with sales and product teams to improve client experience. Her team developed the first personalization engine for JPMorgan Markets and machine learning products to improve workflow for Equities sales. Prior to joining JPMorgan in 2016, Sumitra was part of Franchise Analytics Strats at Goldman Sachs, where she spearheaded the use of machine learning for sales applications. Sumitra has a PhD in Electrical Engineering and Computer Science from U.C. Berkeley. Her thesis was focused on recognizing goal-directed human actions from 3D visual data by using inverse learning to infer the goal of the action from observed motion trajectories.
Meet the Team
The AI Research team is comprised of diverse practitioners with a range of experience levels and areas of expertise.

Life as an AI Researcher & Machine Learning Engineer
Our office is a place where you can solve real-world problems using state of the art machine learning methods and cutting-edge AI research.
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