We no longer support this browser. Using a supported browser will provide a better experience.

Please update your browser.

Close browser message

As a global leader, we deliver strategic advice and solutions, including capital raising, risk management, and trade finance services to corporations, institutions and governments.

Learn more about our solutions:

  

Serving the world's largest corporate clients and institutional investors, we support the entire investment cycle with market-leading research, analytics, execution and investor services.

Learn more about our solutions:

  

We are a leader in investment management, dedicating to creating a strategic advantage for institutions by connecting clients with J.P. Morgan investment professionals globally.

Learn more about our solutions:

    

Our financial advisors create solutions addressing strategic investment approaches, professional portfolio management and a broad range of wealth management services.

Learn more about our solutions:

    

Leverages cutting-edge technologies and innovative tools to bring clients industry-leading analysis and investment advice.

Learn more:

    

The latest news and announcements.

Learn more:

    

For company information and brand assets for editorial use.

Learn more:

    

The latest news and announcements.

Learn more:

    

In a fast-moving and increasingly complex global economy, our success depends on how faithfully we adhere to our core principles: delivering exceptional client service; acting with integrity and responsibility; and supporting the growth of our employees.

Learn more:

    

J.P. Morgan is a global leader in financial services, offering solutions to the world's most important corporations, governments and institutions in more than 100 countries. As announced in early 2018, JPMorgan Chase will deploy $1.75 billion in philanthropic capital around the world by 2023. We also lead volunteer service activities for employees in local communities by utilizing our many resources, including those that stem from access to capital, economies of scale, global reach and expertise.

Learn more:

    

With over 50,000 technologists across 21 Global Technology Centers, globally, we design, build and deploy technology that enable solutions that are transforming the financial services industry and beyond.

Learn more:

    

Technology Banner

For general inquiries regarding JPMorgan Chase & Co. or other lines of business, please call +1 212 270 6000.

Learn more:

      

For general inquiries regarding JPMorgan Chase & Co. or other lines of business, please call +1 212 270 6000.

Learn more:

      

2022

Enhancing Privacy against Inversion Attacks in Federated Learning by using Mixing Gradients Strategies

Shaltiel Eloul, Fran Silavong, Sanket Kamthe, Antonios Georgiadis, Sean J. Moran

FedSyn: Synthetic Data Generation using Federated Learning

Monik Raj Behera, Sudhir Upadhyay, Suresh Shetty, Sudha Priyadarshini, Palka Patel, Ker Farn Lee

ST-FL: Style Transfer Preprocessing in Federated Learning for COVID-19 Segmentation

Antonios Georgiadis (J.P. Morgan), Varun Babbar (J.P. Morgan & University of Cambridge), Fran Silavong (J.P. Morgan), Sean Moran (J.P. Morgan), and Rob Otter (J.P. Morgan)

Proceedings of SPIE 12037, Medical Imaging 2022: Imaging Informatics for Healthcare, Research, and Applications, San Diego, CA, USA, April 2022

Paving the Way towards 800 Gbps Quantum-Secured Optical Channel Deployment in Mission-Critical Environments

Farzam Toudeh-Fallah, Marco Pistoia, Yasushi Kawakura, Navid Moazzami, David H. Kramer, Robert I. Woodward, Greg Sysak, Benny John, Omar Amer, Antigoni O. Polychroniadou, Jeffrey Lyon, Suresh Shetty, Tulasi D. Movva, Sudhir Upadhyay, Monik R. Behera, Joseph A. Dolphin, Paul A. Haigh, James F. Dynes., Andrew J. Shields

Senatus: A Fast and Accurate Code-To-Code Recommendation Engine

Fran Silavong (J.P. Morgan), Sean Moran (J.P. Morgan), Antonios Georgiadis (J.P. Morgan), Rohan Saphal (J.P. Morgan), Robert Otter (J.P. Morgan)

MSR '22: Proceedings of the 19th International Conference on Mining Software Repositories, Pittsburgh, PA, USA, May 2022

2021

Improving Streaming Cryptocurrency Transaction Classification via Biased Sampling and Graph Feedback

Shaltiel Eloul (J.P. Morgan), Sean Moran (J.P. Morgan), Jacob Mendel (J.P. Morgan)

ACSAC: Annual Computer Security Applications Conference, Virtual Event, USA, December 2021

Federated Learning using Smart Contracts on Blockchains, based on Reward Driven Approach

Behera, Monik Raj, Sudhir Upadhyay, and Suresh Shetty. "Federated Learning using Smart Contracts on Blockchains, based on Reward Driven Approach." arXiv preprint arXiv:2107.10243 (2021)

NISQ-HHL: Portfolio Optimization for Near-Term Quantum Hardware

Romina Yalovetzky, Pierre Minssen, Dylan Herman, Marco Pistoia Future Lab for Applied Research and Engineering, JPMorgan Chase Bank, N.A., 2021

Federated Learning using Peer-to-peer Network for Decentralized Orchestration of Model Weights

Behera, Monik Raj; upadhyay, sudhir; Shetty, Suresh; Otter, Robert (2021): Federated Learning using Peer-to-peer Network for Decentralized Orchestration of Model Weights. TechRxiv. Preprint.

2020

Federated Learning using Distributed Messaging with Entitlements for Anonymous Computation and Secure Delivery of Model

Behera, Monik Raj; upadhyay, sudhir; Otter, Robert; Shetty, Suresh (2020): Federated Learning using Distributed Messaging with Entitlements for Anonymous Computation and Secure Delivery of Model. TechRxiv. Preprint.

Heuristics for Link Prediction in Multiplex Networks

Robert E. Tillman (J.P. Morgan), Vamsi Potluru (J.P. Morgan), Jiahao Chen (J.P. Morgan), Prashant Reddy (J.P. Morgan), Manuela Veloso (J.P. Morgan)

In Proceedings of ECAI'20, European Conference on Artificial Intelligence, Santiago de Compostela, Spain, June, 2020

Classifying and Understand Financial Data Using Graph Neural Network

Xiaoxiao Li (Yale University), Joao Saude (J.P. Morgan), Prashant Reddy (J.P. Morgan), Manuela Veloso (J.P. Morgan)

AAAI-20 Workshop on Knowledge Discovery from Unstructured Data in Financial Services, February, 2020

2019

InverseNet: Solving Inverse Problems of Multimedia Data with Splitting Networks

Qi Wei (J.P. Morgan), Kai Fan (Alibaba DAMO Academy), Wenlin Wang (Duke University), Tianhang Zheng (SUNY at Buffalo), Chakraborty Amit (Siemens Corporate Technology), Katherine Heller (Google Brain), Changyou Chen (SUNY at Buffalo), Kui Ren (Zhejiang University)

ICME’19 Regular Paper, Shanghai, China, July 2019

Towards Inverse Reinforcement Learning for Limit Order Book Dynamics

Jacobo Roa-Vicens, Cyrine Chtourou (J.P. Morgan), Angelos Filos, Yarin Gal (University of Oxford) Francisco Rul-lan, Ricardo Silva (University College London) In ICML Workshop 'AI in Finance: Applications and Infrastructure for Multi-Agent Learning’ at the 36th International Conference on Machine Learning, ICML 2019, Long Beach, CA, USA, 2019.

(arXiv:1906.04813v1 [cs.LG] 11 Jun 2019)

Model-based Reinforcement Learning for Predictions and Control for Limit Order Books

Haoran Wei (University of Delaware), Yuanbo Wang (Twitter), Lidia Mangu (J.P. Morgan), Keith Decker (University of Delaware)

NeurIPS 2019 Workshop on Robust AI in Financial Services: Data, Fairness, Explainability, Trustworthiness, and Privacy, Vancouver, Canada, December 2019

Adversarial recovery of agent rewards from latent spaces of the limit order book

Jacobo Roa-Vicens (J.P. Morgan), Yuanbo Wang (Twitter), Virgile Mison (J.P. Morgan), Yarin Gal (University of Oxford)

NeurIPS 2019 Workshop on Robust AI in Financial Services: Data, Fairness, Explainability, Trustworthiness, and Privacy, Vancouver, Canada, December 2019

Classifying and Understand Financial Data Using Graph Neural Network

Sumitra Ganesh (J.P. Morgan); Nelson Vadori (J.P. Morgan); Mengda Xu (J.P. Morgan); Prashant Reddy (J.P. Morgan); Manuela Veloso (J.P. Morgan)

NeurIPS'19 Workshop on Robust AI in Financial Services, Vancouver, Canada, December, 2019

Get Real: Realism Metrics for Robust Limit Order Book Market Simulations

Svitlana Vyetrenko (J.P. Morgan); David Byrd (Georgia Institute of Technology); Nick Petosa (Georgia Institute of Technology); Mahmoud Mahfouz (J.P. Morgan); Danial Dervovic (J.P. Morgan); Tucker Balch (J.P. Morgan)

NeurIPS'19 Workshop on Robust AI in Financial Services, Vancouver, Canada, December, 2019

Latent Bayesian Inference for Robust Earnings Estimates

Chirag Nagpal (Carnegie Mellon University); Robert E Tillman (J.P. Morgan AI Research); Prashant Reddy (J.P. Morgan); Manuela Veloso (J.P. Morgan)

NeurIPS'19 Workshop on Robust AI in Financial Services, Vancouver, Canada, December, 2019

On the Importance of Opponent Modeling in Auction Markets

Mahmoud Mahfouz (J.P. Morgan), Angelos Filos (J.P. Morgan), Cyrine Chtourou (J.P. Morgan), Joshua Lockhart (J.P. Morgan), Samuel Assefa (J.P. Morgan), Manuela Veloso (J.P. Morgan), Danilo Mandic (Imperial College), Tucker Balch (J.P. Morgan)

NeurIPS'19 Workshop on Robust AI in Financial Services, Vancouver, Canada, December, 2019

Some people aren’t worth listening to: periodically retraining classifiers with feedback from a team of end users

Joshua Lockhart (J.P. Morgan); Samuel Assefa (J.P. Morgan); Tucker Balch (J.P. Morgan); Manuela Veloso (J.P. Morgan)

ICML'19 Workshop on AI in Finance, Long Beach, CA, June, 2019

How to Evaluate Trading Strategies: Single Agent Market Replay or Multiple Agent Interactive Simulation?

Tucker Hybinette Balch (J.P. Morgan); Mahmoud Mahfouz (J.P.Morgan); Joshua Lockhart (J.P. Morgan); Maria Hybinette (University of Georgia); David Byrd (Georgia Institute of Technology)

ICML'19 Workshop on AI in Finance, Long Beach, CA, June, 2019

Risk-Sensitive Compact Decision Trees for Autonomous Execution in Presence of Simulated Market Response

Svitlana Vyetrenko (J.P. Morgan); Shaojie Xu (Georgia Institute of Technology)

ICML'19 Workshop on AI in Finance, Long Beach, CA, June, 2019

Small Memory Robust Simulation of Interactive Protocols over Oblivious Noisy Channels

Hubert Chan, Zhibin Liang (Hong Kong U.), Antigoni Polychroniadou (J.P. Morgan), Elaine Shi (Cornell)

ACM - SIAM'19 Symposium on Discrete Algorithms, San Diego, CA, January, 2019

Trading via Image Classification

Naftali Cohen (J.P. Morgan), Tucker Balch (J.P. Morgan), Manuela Veloso (J.P. Morgan)

arXiv:1907.10046 [cs.CV], October, 2019

The Effect of Visual Design in Image Classification

Naftali Cohen (J.P. Morgan), Tucker Balch (J.P. Morgan), Manuela Veloso (J.P. Morgan)

arXiv:1907.09567 [cs.CV], August, 2019

2018

Idiosyncrasies and challenges of data driven learning in electronic trading

Vangelis Bacoyannis, Vacslav Glukhov, Tom Jin, Jonathan Kochems, Doo Re Song (J.P. Morgan)

NIPS 2018 Workshop on Challenges and Opportunities for AI in Financial Services (FEAP-AI4Fin 2018), Montréal, Canada, December, 2018

Deep Hedging: Hedging Derivatives Under Generic Market Frictions Using Reinforcement Learning

Hans Buehler, Lukas Gonon, Josef Teichmann, Ben Wood, Baranidharan Mohan, Jonathan Kochems (J.P. Morgan)

NIPS 2018 Workshop on Challenges and Opportunities for AI in Financial Services (FEAP-AI4Fin 2018), Montréal, Canada, December, 2018

Sensitivity based Neural Networks Explanations

Kay Giesecke (Stanford University), Virgile Mison (J.P. Morgan), Tao Xiong (J.P. Morgan), Lidia Mangu (J.P. Morgan)

NeurIPS 2018 Workshop on Challenges and Opportunities for AI in Financial Services: the Impact of Fairness, Explainability, Accuracy, and Privacy, Montréal, Canada, December 2018

LMVP: Video Predictor with Leaked Motion Information

Dong Wang (Duke University) , Yitong Li (Duke University) , Wei Cao (Tsinghua University) , Liqun Chen (Duke University) , Qi Wei (J.P. Morgan), Lawrence Carin (Duke University)

NeurIPS'18 Workshop on Modeling and Decision-Making in the Spatiotemporal Domain, Montréal, Canada, December 2018

 

2017

An Inner-loop Free Solution to Inverse Problems using Deep Neural Networks

Qi Wei (J.P. Morgan), Kai Fan, Lawrence Carin, Katherine A. Heller (Duke University)

NIPS'17 Regular Paper, Long Beach, CA, December 2017

 

 

*Equal contribution by the authors

The [papers/presentations] on this page were prepared for informational purposes by various [technology and engineering] groups within JPMorgan Chase & Co. and its affiliates (“J.P. Morgan”), and is not a product of the Research Department of J.P. Morgan. J.P. Morgan makes no representation and warranty whatsoever and disclaims all liability, for the completeness, accuracy or reliability of the information contained herein. This document is not intended as investment research or investment advice, or a recommendation, offer or solicitation for the purchase or sale of any security, financial instrument, financial product or service, or to be used in any way for evaluating the merits of participating in any transaction, and shall not constitute a solicitation under any jurisdiction or to any person, if such solicitation under such jurisdiction or to such person would be unlawful.