2022


AI to Eradicate Financial Crime

Michael Wellman

University of Michigan, Strategic Modeling of Fraud on the Payments Network

Chenhao Tan

University of Chicago, Generating Multimodal Explanations for Financial Decisions

Nihar Shah

Carnegie Mellon University, Outsourcing Development of Fraud-Detection AI while Preserving Data Privacy

Furong Huang

University of Maryland, Repelling Security Vulnerabilities in AI-augmented Financial Decision-Making Systems

Daniel Wichs

Northeastern University, Private Information Retrieval and Secure Computation over Big Data

Leandros Tassiulas

Yale University, Combining DeFi and AI for Intelligent DeFi applications

AI to Liberate Data Safely

Charalampos Papamanthou

Yale University, New Zero-Knowledge Arguments for Cryptocurrencies

Jun-Yan Zhu

Carnegie Mellon University, Large-Scale Dataset Distillation for Privacy-Preserving Machine Learning

Abhishek Jain

Johns Hopkins Univeresity, Crowd-Sourced Secure Machine Learning

Elaine Shi

Carnegie Mellon University, Scaling Privacy-Preserving AI to Big Data

Yevgeniy Dodis

New York University, Privacy and Integrity in the Web3

Muthuramakrishnan Venkitasubramaniam

Georgetown University, Lightweight Publicly Verifiable Distributed 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

Alessandro Abate

University of Oxford, Learning and Reasoning in Repeated Games with Partial Information

Dorsa Sadigh

Stanford University, Fair Gifting for Emergent Prosociality in Multi-Agent Coordination

Renyuan Xu

University of Southern Californi, Mean-field approximation for multi-agent systems: towards scalable AI-driven decision-making and simulation methods in financial markets

Judong Li

University of Virginia, Counterfactual Graph Generation for Explaining Financial Decisions

Alexandros Iosifidis

Aarhus University, Bayesian Learning of Deep Neural Networks for financial time-series and graph data analysis with class-imbalance

Paul Goldberg

University of Oxford, Price discovery via decentralised networks of trading agents

Mohammad M Ghassemi

Michigan State University, The Evolution of Private Capital Modeled as a Temporal Hyper-Graph

AI to Empower Employees

Himabindu Lakkaraju

Harvard University, Understanding and Mitigating Privacy Risks of Algorithmic Recourse

Lin Tan

Purdue University, Domain-specific Neural Networks for Improving Code Quality and Productivity

Zachary Lipton

Carnegie Mellon University, Interactive and Trustworthy Neural Summarization

Quanquan Gu

University of California, Los Angeles, Multi-Objective and Causal Reinforcement Learning for Responsible and Explainable AI in Finance

Chien-Ju-Ho

Washington University in St. Louis, Forming Representative Cohorts: Sequential Recruitment under Uncertainty

Gilad Asharov

Bar-Ilan University, FinSec: Secure Analytics over Financial Data

Xiaodan Zhu

Department of Electrical and Computer Engineering, Queen's University, Exploring Robust Reasoning Models for Financial Text

Vukosi Marivate

University of Pretoria, Topic classification modelling of code-mixed and code-switched language for low-resource South African languages

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

Pradeep Ravikumar

Carnegie Mellon University, Inferring Latent Causal Factors of Client Behavior

Jiajun Wu

Stanford University, Machine Visual Interpretation, Optimization, and Synthesis of Cognitive Workflows

Lingjia Tang

University of Michigan, Towards Personalized Intelligence at Scale

Vinayak Abrol

Indraprastha Institute of Technology Delhi, Sampling Rate Independent Descriptors for Improving Speech Data Analytics

Monica Lam

Stanford University, Neural, Self-Learning, Mixed-Initiative Conversational Assistants

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