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Faculty Research Awards 2022
2022 JPMC AIR Faculty Research Award - Kick-off
AI to Eradicate Financial Crime
Leandros Tassiulas
Yale University
Combining DeFi and AI for Intelligent DeFi applications
Chenhao Tan
University of Chicago
Generating Multimodal Explanations for Financial Decisions
Michael Wellman
University of Michigan
Strategic Modeling of Fraud on the Payments Network
Daniel Wichs
Northeastern University
Private Information Retrieval and Secure Computation over Big Data
Furong Huang
University of Maryland
Repelling Security Vulnerabilities in AI-augmented Financial Decision-Making Systems
Nihar Shah
Carnegie Mellon University
Outsourcing Development of Fraud-Detection AI while Preserving Data Privacy
AI to Liberate Data Safely
Charalampos Papamanthou
Yale University
New Zero-Knowledge Arguments for Cryptocurrencies
Yevgeniy Dodis
New York University
Privacy and Integrity in the Web3
Abhishek Jain
JOHNS HOPKINS UNIVERSITY
Crowd-Sourced Secure Machine Learning
Muthuramakrishnan
Venkitasubramaniam
Georgetown University
Lightweight Publicly Verifiable Distributed Privacy-Preserving Machine Learning
Elaine Shi
Carnegie Mellon University
Scaling Privacy-Preserving AI to Big Data
Jun-Yan Zhu
Carnegie Mellon University
Large-Scale Dataset Distillation for Privacy-Preserving Machine Learning
Steven Wu
Carnegie Mellon University
Advancing Privacy-Preserving Data Sharing with Synthetic Data Generation
AI to Predict and Affect Economic Systems
Judong Li
University of Virginia
Counterfactual Graph Generation for Explaining Financial Decisions
Renyuan Xu
University of Southern California
Mean-field approximation for multi-agent systems: towards scalable AI-driven decision-making and simulation methods in financial markets
Alessandro Abate
University of Oxford
Learning and Reasoning in Repeated Games with Partial Information
Paul Goldberg
University of Oxford
Price discovery via decentralised networks of trading agents
Dorsa Sadigh
Stanford University
Fair Gifting for Emergent Prosociality in Multi-Agent Coordination
Mohammad M Ghassemi
Michigan State University
The Evolution of Private Capital Modeled as a Temporal Hyper-Graph
Alexandros Iosifidis
Aarhus University
Bayesian Learning of Deep Neural Networks for financial time-series and graph data analysis with class-imbalance
AI to Empower Employees
Chien-Ju-Ho
Washington University in St. Louis
Forming Representative Cohorts: Sequential Recruitment under Uncertainty
Vukosi Marivate
University of Pretoria
Topic classification modelling of code-mixed and code-switched language for low-resource South African languages
Quanquan Gu
University of California, Los Angeles
Multi-Objective and Causal Reinforcement Learning for Responsible and Explainable AI in Finance
Lin Tan
Purdue University
Domain-specific Neural Networks for Improving Code Quality and Productivity
Himabindu Lakkaraju
Harvard University
Understanding and Mitigating Privacy Risks of Algorithmic Recourse
Xiaodan Zhu
Department of Electrical and Computer Engineering, Queen's University
Exploring Robust Reasoning Models for Financial Text
Zachary Lipton
Carnegie Mellon University
Interactive and Trustworthy Neural Summarization
Gilad Asharov
Bar-Ilan University
FinSec: Secure Analytics over Financial Data
Sarit Kraus
Bar Ilan University
Explanations of AI-Based Resource Allocations
AI to Perfect Client Experience
William Yeoh
Washington University in St. Louis
Improving Client Experience Through Goal Recognition and Explainable Assistance in Adaptive Systems
Lingjia Tang
University of Michigan
Towards Personalized Intelligence at Scale
Monica Lam
Stanford University
Neural, Self-Learning, Mixed-Initiative Conversational Assistants
Jiajun Wu
Stanford University
Machine Visual Interpretation, Optimization, and Synthesis of Cognitive Workflows
Vinayak Abrol
Indraprastha Institute of Technology Delhi
Sampling Rate Independent Descriptors for Improving Speech Data Analytics
Pradeep Ravikumar
Carnegie Mellon University
Inferring Latent Causal Factors of Client Behavior
Policy Compliance
David Byrd
Bowdoin College
Multi-Agent Market Simulation to Reduce Inadvertent Adoption of Malappropriate Behaviors in Intelligent Trading Algorithms
Establish Ethical and Socially Good AI
Odest Chadwicke Jenkins
University of Michigan
Semantic Frame Mapping for Building-wide Perception and Affordance Execution
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