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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
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