Jianwei Shen
Ph.D. Candidate
Department of Computer Science
University of Arizona
Recent News
- [Apr 2024]Paper “Efficient Variational Sequential Information Control” accepted to AISTATS 2024!
- [Feb 2022]Paper “Privacy-preserving training of tree ensembles over continuous data” published in PoPETS 2022
- [Jan 2021]Paper “High performance logistic regression for privacy-preserving genome analysis” published in BMC Medical Genomics
- [Nov 2019]Two papers accepted to ACM SIGSPATIAL 2019 on GPS trace analysis
About
I am a Ph.D. candidate in the Department of Computer Science at University of Arizona, working with Dr. Jason Pacheco. My research focuses on machine learning, POMDP, especially Information-theoretic guided POMDPs.
Prior to attending the University of Arizona, I worked with Dr. Martine De Cock and Dr. Anderson Nascimento, on the topic of Privacy-preserving machine learning, at the University of Washington Tacoma, where I received my M.S. in Computer Science in 2020. In the meantime, I also worked with Dr. Mohamed Ali, on the topic of map-matching.
Selected Publications
Efficient Variational Sequential Information Control
International Conference on Artificial Intelligence and Statistics (AISTATS), 2024
Authors: Jianwei Shen, Jason L. Pacheco
High performance logistic regression for privacy-preserving genome analysis
BMC Medical Genomics, 2021
Authors: Martine De Cock, Rafael Dowsley, Anderson C. A. Nascimento, Davis Railsback, Jianwei Shen, Ariel Todoki
Privacy-preserving training of tree ensembles over continuous data
Proceedings on Privacy Enhancing Technologies (PoPETS), 2022
Authors: S Adams, C Choudhary, M De Cock, R Dowsley, D Melanson, Jianwei Shen, et al.
Research
Sequential Information Control
Developing efficient variational methods for sequential information control problems in partially observable Markov decision processes (POMDPs).
Privacy-Preserving Machine Learning
Creating secure and privacy-preserving methods for training machine learning models, particularly for healthcare and genomic data analysis.
Geospatial Data Analysis
Developing techniques for analyzing and cleaning GPS traces, with applications in map-matching and transportation systems.
Working Experience
Graduate Teaching Assistant
University of Arizona, 2025 Spring
CSC 460: Database Design
Graduate Teaching Assistant
University of Arizona, 2025 Spring
CSC 380: Introduction to Data Science
Graduate Research Assistant
University of Arizona, 2020 - Present
Research on sequential information control and variational methods for POMDPs.
Research Assistant
University of Washington Tacoma, 2019 - 2020
Developed privacy-preserving machine learning methods for healthcare and genomic data.
Research Assistant
University of Washington Tacoma and Microsoft, Summer 2019
Worked on geospatial data analysis and map-matching algorithms for GPS traces.
Software Engineer
X.D. Network Inc., 2016-2018
Worked on data visualization and data analysis websites.