2021 Faculty Research Award kick-off

| 20:47

2021 JPMC AIR Faculty Research Award - Kick-off

| 20:47

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

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

Pan Li

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

AI to Liberate Data Safely

Gilad Asharov

Bar-Ilan University, 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

Ilan Komargodski

Hebrew University of Jerusalem, Scaling Secure Computation for Data Centers

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

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