Faculty award recipients 2020 :click the link for Faculty award recipients 2020 page

Faculty Research Awards 2021

2021 JPMC AIR Faculty Research Award - Kick-off

AI to Eradicate Financial Crime

Engineer Bainomugisha

Makerere University

Generating Synthetic Datasets for Mobile Money Transactions for AI Research

Pan Li

Purdue University

Neural Modeling of Network Dynamics for Anomaly Detection and Recommendation in Financial Systems

Jure Leskovec

Stanford University

ROLAND 2.0: Graph Representation Learning for Transaction Networks

Milind Tambe

Harvard University

Policies for Supervisory Audits: A Security Games and Bandit approach

AI to Liberate Data Safely

Gilad Asharov

Bar-Ilan University

Ilan Komargodski

Hebrew University of Jerusalem

Scaling Secure Computation for Data Centers

Giulia Fanti

Carnegie Mellon University

Producing Privacy-Preserving, Synthetic Time Series Datasets with Generative Adversarial Networks

Yan Liu

University of Southern California

Time Series Synthesization: Models, Evaluation Metrics and Benchmark Dataset

Michael Mahoney

University of California, Berkeley

Interpretable machine learning methods for financial analytics

Heather Miller

Carnegie Mellon University

Distributed Data Structures for Federated Learning

Rafail Ostrovsky

University of California, Los Angeles

CEDRIC: seCurE anD pRIvate Computation

Daniela Rus

Massachusetts Institute of Technology

Auditable Debiased Decision Making

Dawn Song

University of California, Berkeley

PrivShare: Privacy-preserving Data Analysis over Multiple Data Sources

Shuran Song

Columbia University

Decoding Economic Trends with Human-in-the-loop Machine Perception

AI to Predict and Affect Economic Systems

Novella Bartolini

Sapienza University of Rome

Understanding interdependent market dynamics: vulnerabilities and opportunities

Fernando Fernandez

Universidad Carlos III de Madrid

Adversarial Reinforcement Learning: Avoiding Malicious Behaviours

Chelsea Finn

Stanford University

Rapid and Robust Adaptation to Temporal Distribution Shift

Nikolas Kantas

Imperial College London

Secure and Self-Optimizing Distributed Inference

Nathan Kallus

Cornell University

Offline Reinforcement Learning: Efficiency, Safety, Transparency, and Fairness

Sergey Levine

University of California, Berkeley

Offline Reinforcement Learning in Multi-Agent Networks: Smart Decisions from Logged Data

Rahul Savani

University of Liverpool

Robust Trading via Multi-Agent Adversarial Reinforcement Learning

Zhangyang Wang

University of Texas at Austin

Learning Optimizers Made Adaptable and Applicable to Multi-Agent Systems

AI to Empower Employees

Umut Acar

Carnegie Mellon University

Diderot: Building the Next Generation Education Platform

Giuseppe De Giacomo

Sapienza University of Rome

Resilience-based Generalized Planning and Strategic Reasoning

Subbarao Kambhampati

Arizona State University

Automated Extraction and Execution Support for Cognitive Workflows in Finance

Jay Pujara

University of Southern California

A Table Understanding Approach to Improving Quantitative Cognitive Workflows

Dorsa Sadigh

Stanford University

Learning and Leveraging Representations in Repeated Multi-Agent Interactions

Laurence Tratt

King’s College London

MIG: Migrating Languages

William Yang Wang

University of California, Santa Barbara

OpenFinQA: Open Financial Question Answering via Tables and Text

Diyi Yang

Georgia Tech

Scalable Modeling of Financial Documents for Improved
Decision-Making

Christina Lee Yu

Cornell University

Exploiting Low Rank Structure for Provably Efficient Reinforcement Learning

AI to Perfect Client Experience

Elias Bareinboim

Columbia University

Causal Reinforcement Learning for Optimal and Personalized Decision-Making

Sarit Kraus

Bar-Ilan University

Meta-agents for human-agent collaboration

Jundong Li

University of Virginia

Usable, Interpretable, and Fair Causal Effects Learning for Financial Applications

Nishant Mehta

University of Victoria

Attention pays: learning a structured model of client interest for improved financial product recommendations

Policy Compliance

Elefelious Getachew Belay

Addis Ababa Institute of Technology

Exploring AI and Machine Learning Technologies to track Policy Compliance of Highly Trusted Parties (HTPs) and incidents of Fraud at selected banking Intuitions in Ethiopia

Kamalakar Karlapalem

IIIT Hyderabad

Applied Semantics Extraction and Analytics over Banking Documents

Establish Ethical and Socially Good AI

Sebastian Angel

University of Pennsylvania

Private Federated Analytics with Efficient Key Management

Thomas Ristenpart

Cornell University

Improving Tech Abuse Interventions with IPV Survivors

Dana Dachman-Soled

University of Maryland

Joint Fairness and Privacy Design for Financial Machine Learning Algorithms

Julia Stoyanovich

New York University

Nutritional Labels for Financial Products and Credit Decisions: Strengthening Accountability Through Public Disclosure

Genevera Allen

Rice University

Improving Fairness and Interpretability of AI Systems through Minipatch Learning

Xia Hu

Rice University

Multi-Aspect Interpretation Framework for Understanding AI Models on Financial Adverse Actions

Lin Tan

Purdue University

Testing and Improving the Fairness and Correctness of AI Systems: A Variance Perspective