Hi, my name is Chris. I received my double B.S. in Computer Science and Mathematics from Delaware State University. Currently, I am a PhD candidate in Computer Science at the University of Illinois at Chicago, working with Professor Elena Zheleva.
Currently, my main focus is in the realm of causal inference, particularly using machine learning for estimating heterogeneous treatment effects.
I'm also interested in applying causal inference and machine learning for applications to social science, privacy, social networks.
Improving Data-driven Heterogeneous Treatment Effect Estimation Under Structure Uncertatinty
C. Tran E. Zheleva
To be published in the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2022
Heterogeneous Peer Effects in the Linear Threshold Model
C. Tran E. Zheleva
Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2022
[Preprint PDF]
Heterogeneous Effects of Software Patches in a Multiplayer Online Battle Arena Game
Y. He, C. Tran, J. Jiang, K. Burghardt, E. Ferrara, E. Zheleva, K. Lerman
16th International Conference on the Foundations of Digital Games (FDG), 2021
[PDF]
Helping Users Automatically Find and Manage Sensitive, Expendable Files in Cloud Storage
M. T. Khan, C. Tran, S. Singh, D. Vasilkov, C. Kanich, B. Ur, E. Zheleva
Proceedings of the USENIX Security Symposium (USENIX), 2021
[PDF]
We developed an app based on this paper! Learn whats taking up space or hidden in your Google Drive: https://cloudsweeper.app/
Heterogeneous Threshold Estimation for Linear Threshold Modeling
C. Tran, E. Zheleva
KDD Workshop on Mining and Learning with Graphs (MLG), 2020 (Contributed Talk)
[PDF]
Paths to Empathy: Heterogeneous Effects of Reading Personal Stories Online
M. Roshanaei, C. Tran, S. Morelli, C. Caragea, E. Zheleva
IEEE Conference on Data Science and Advanced Analytics (DSAA), 2019
[PDF]
Moving Beyond Set-It-And-Forget-It Privacy Settings on Social Media
M. Mondal, G. Yilmaz, N. Hirsch, M. Khan, M. Tang, C. Tran, C. Kanich, B. Ur, E. Zheleva
ACM Conference on Computer and Communications Security (CCS), 2019
[PDF]
Learning Triggers for Heterogeneous Treatment Effects
C. Tran, E. Zheleva.
Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2019
[PDF] [Code]
Making Retrospective Data Management Usable (Poster)
N. Hirsch, C. Kanich, M. Khan, X. Liu, M. Mondal, M. Tang, C. Tran, B. Ur, W. Wang, G. Yilmaz, E. Zheleva.
14th Symposium On Usable Privacy and Security (SOUPS), August 2018
Privacy Preservation in Shared Images (a survey) [PDF] [Slides]
C. Tran
In fulfillment of the UIC CS PhD qualifying exam, April 2018
Smart Information Flow Technologies (SIFT), Minneapolis, MN
Research Intern, May 2019 - November 2019
- Modeling and identifying factors for gender bias in data
- Learning behavior in swarm data
- Novel recommendations for document data
STATS Perform (formerly STATS LLC), Chicago, IL
Artificial Intelligence (AI) Intern, May 2018 - August 2018
- Leverage deep learning models to predict ball ownership and movement from tracking data in basketball
Teaching Assistant
Introdution to Machine Learning (CS412)
Fall 2018, Spring 2021
University of Illinois at Chicago
Teaching Assistant
Mathematical Foundations of Computing (CS 151)
Spring 2017, Fall 2017, Spring 2018
University of Illinois at Chicago
Teaching Assistant
Program Design I (CS 111)
Summer 2017
University of Illinois at Chicago
Teaching Assistant
C/C ++ Programming for Engineers with MatLab (CS 109)
Fall 2016
University of Illinois at Chicago
