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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