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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
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