Faculty award recipients 2019 :click the link for Faculty award recipients 2019 page

Faculty Research Awards 2020

AI to Eradicate Financial Crime

Trustworthiness of Data and Network

Austin R Benson

Cornell University

Pattern-based Heterogeneous Graph Clustering at Scale

Contacts: Manuela Veloso, Vamsi Potluru

Trustworthiness of Data and Network

Jure Leskovec

Stanford University

Rok Sosic

Stanford University

ROLAND: Representation Learning and Anomaly Detection in Financial Networks

Contacts: Prashant Reddy, Daniel Borrajo, Vamsi Potluru

Trustworthiness of Data and Network

Leandros Tassiulas

Yale University

Distributed Ledgers for Enhancing the Trust and Performance of Financial Networks

Contacts: Prashant Reddy, Vamsi Potluru, Parisa Hassanzadeh

Trustworthiness of Data and Network

Austin R Benson

Cornell University

Pattern-based Heterogeneous Graph Clustering at Scale

Contacts: Manuela Veloso, Vamsi Potluru

Trustworthiness of Data and Network

Jure Leskovec

Stanford University

Rok Sosic

Stanford University

ROLAND: Representation Learning and Anomaly Detection in Financial Networks

Contacts: Prashant Reddy, Daniel Borrajo, Vamsi Potluru

Trustworthiness of Data and Network

Leandros Tassiulas

Yale University

Distributed Ledgers for Enhancing the Trust and Performance of Financial Networks

Contacts: Prashant Reddy, Vamsi Potluru, Parisa Hassanzadeh

Trustworthiness of Data and Network

Naoki Masuda

University at Buffalo

A. Erdem Sariyuce

University at Buffalo

Detecting Fraudulent Transactions in Online Marketplaces Using Temporal Network Motifs

Contacts: Prashant Reddy, Rob Tillman

Trustworthiness of Data and Network

Tom Goldstein

University of Maryland, College Park

Furong Huang

University of Maryland, College Park

Robust, Private and Fair ML for Financial Models

Contacts: Dan Magazzeni, Naftali Cohen

AI to Liberate Data Safely

Data Privacy Preserving Machine Learning

Daniela Rus

MIT CSAIL

Secure Private Computing Using Coresets

Contacts: Tucker Balch, Antigoni Polychroniadou

Data Privacy Preserving Machine Learning

Huijia Lin

University of Washington

Stefano Tessaro

University of Washington

Secure Data Analytics with a Single Untrusted Server

Contacts: Dan Magazzeni, Antigoni Polychroniadou

Data Privacy Preserving Machine Learning

Rafael Pass

Cornell University

Elaine Shi

Cornell University

CryptML: Cryptographic Machine Learning

Contacts: Tucker Balch, Antigoni Polychroniadou, Ben Diamond

Data Privacy Preserving Machine Learning

Rafail Ostrovsky

UCLA

SECURE: SEcure CompuUtation for fRaud dEtection

Contacts: Tucker Balch, Antigoni Polychroniadou, Ben Diamond

Data Privacy Preserving Machine Learning

Tal Malkin

Columbia University

MAGIC: Machine Learning Through a Cryptographic Lens

Contacts: Tucker Balch, Antigoni Polychroniadou

Data Privacy Preserving Machine Learning

Fabio Caccioli

University College London

Network Methods for the Generation of Synthetic Datasets

Contacts: Sammy Assefa, Danial Dervovic

Synthetic Data Generation

Giulia Fanti

Carnegie Mellon University

Vyas Sekar

Carnegie Mellon University

Producing Privacy-Preserving, Synthetic Time Series Datasets with Generative Adversarial Networks

Contacts: Sammy Assefa, Rob Tillman

Synthetic Data Generation

Rachel Cummings

Georgia Tech

Differentially Private Synthetic Data Generation

Contacts: Manuela Verloso, Naftali Cohen

Synthetic Data Generation

Yan Liu

University of Southern California

HR-Neural ODE: Multivariate Multiresolution Time Series Synthesizer via Neural Ordinal Differential Equations

Contacts: Sammy Assefa, Jiahao Chen

Synthetic Data Generation

Yarin Gal

University of Oxford

Uncertainty Aware Data-driven Generative Models and Multi-agent Simulators

Contacts: Sammy Assefa, Josh Lockhart

AI to Predict and Affect Economic Systems

Simulated Multi-Agent Systems

Chelsea Finn

Stanford University

Continuous Meta-Reinforcement Learning in Non-Stationary Environments

Contacts: Sumitra Ganesh, Nelson Vadori

Simulated Multi-Agent Systems

Fernando Fernández

Universidad Carlos III de Madrid

Learning Similarity Metrics Between Simulation and the Real World

Contacts: Sumitra Ganesh, Svitlana Vyetrenko, Nelson Vadori

Simulated Multi-Agent Systems

Henry Lam

Columbia University

Calibrating Large-Scale Simulation Models via Distributionally Robust Optimization

Contacts: Tucker Balch, Danial Dervovic

Simulated Multi-Agent Systems

Michael Wellman

University of Michigan

Uday Rajan

University of Michigan

Michael Barr

University of Michigan

Gabriel Rauterberg

University of Michigan

Multiagent Modeling of the Financial Payments System

Contacts: Sammy Assefa, Svitlana Vyetrenko

Simulated Multi-Agent Systems

Michael Wooldridge

Oxford University

Opponent Modeling in Adaptive Markets

Contacts: Sumitra Ganesh, Nelson Vadori

Simulated Multi-Agent Systems

Sarit Kraus

Bar-Ilan University

Agents Supporting Large-scale Environments of Teams of People and Computer Systems –Y2

Contacts: Manuela Veloso, Sammy Assefa

Simulated Multi-Agent System

Sergey Levine

UC Berkeley

Multi-Agent Modeling with Inverse RL and POMDP Models

Contacts: Sumitra Ganesh, Svitlana Vyetrenko

AI to Move Employees Up the Value Chain

Cognitive Workflow Learning

Jay Pujara

University of Southern California

Craig Knoblock

University of Southern California

Supporting Cognitive Workflows with Hybrid Knowledge Graphs

Contacts: Sameena Shah, Daniel Borrajo

Cognitive Workflow Learning

Kamalakar Karlapalem

IIIT Hyderabad

Guided Discovery of Cognitive Steps within a Task

Contacts: Manuela Veloso, Natraj Raman

Cognitive Workflow Learning

Stephanie Rosenthal

Carnegie Mellon University

Reid Simmons

Carnegie Mellon University

Timely Suggestions for Improving Data Analyst Cognitive Workflows

Contacts: Prashant Reddy, Daniel Borrajo, Vamsi Potluru

Cognitive Workflow Learning

William Yang Wang

UC Santa Barbara

Combining Knowledge Base and Unstructured Text for Open-Domain Financial Question Answering

Contacts: Sameena Shah, Rob Tillman

Cognitive Workflow Learning

Yun Fu

Northeastern University

Reinforced Graph-Structured Expert Model for Business Intelligence

Contacts: Dan Magazzeni, Rob Tillman

Establish Ethical and Socially Good AI

AI for Fairness

L. Elisa Celis

Yale University

Fair AI for the Long Haul: Interventions and Tradeoffs

Contacts: Dan Magazzeni, Jiahao Chen

AI for Fairness

Lin Tan

Purdue University

Testing AI Systems for Fairness, Accuracy, and Performance

Contacts: Sameena Shah, Jiahao Chen

AI for Fairness

Nika Haghtalab

Cornell University

Fair Machine Learning: Dynamics, Economics, and Privacy

Contacts: Dan Magazzeni, Jiahao Chen

AI for Fairness

Novella Bartolini

Sapienza University of Rome

The Impact of Trading Strategies and Market Rules on Fairness of Financial Markets

Contacts: Tucker Balch, Svitlana Vyetrenko

AI for Fairness

Xi Chen

New York University

Yuan Zhou

UIUC

Distributional Outcome Fairness-aware Decision-making with Financial Applications

Contacts: Sameena Shah, Parisa Hassanzadeh