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Emily (Shuya) Feng

Privacy-Preserving Machine Learning Differential Privacy Large Language Model Security Federated Learning Trustworthy AI Deployment
University of Alabama at Birmingham (UAB) Department of Computer Science

About

Emily (Shuya) Feng is an Assistant Professor in the Department of Computer Science at the University of Alabama at Birmingham, starting in August 2025. Dr. Feng's research addresses fundamental challenges in AI security and privacy, encompassing privacy-preserving machine learning, differential privacy, large language model security, federated learning, and responsible AI. Dr. Feng's work bridges theoretical foundations and practical applications, tackling emerging threats in AI systems, including streaming data privacy, model security, and trustworthy AI deployment. She has published in top-tier conferences including IEEE S&P, NDSS, ACM KDD, CODASPY, WWW, and EMNLP.

Research Performance Summary

11
Total Papers
77
Total Citations
6
H-Index
2021-2025
Active Research Span

First Recorded Paper

Security analysis of block withholding attacks in blockchain

Year: 2021

Citations: 8

Venue: ICC 2021-IEEE International Conference on Communications

Latest Recorded Paper

KPIR-C: Keyword PIR with Arbitrary Server-side Computation

Year: 2025

Citations: 0

Venue: Cryptology ePrint Archive

Last 10 Years Publication Activity

This timeline shows the professor's yearly publication activity.

2025
5
2024
4
2022
1
2021
1

Publication Venues and Collaboration

Journal, Conference, and Book Publication Breakdown

Conference 7
Journal 0
Book 0

Top Coauthors

Feng Hong Wang

Research Impact by Period

2025-2026

Period Stats
Papers 5
Citations 22
Avg. Citations / Paper 4.4
H-Index 2

2020-2024

Period Stats
Papers 6
Citations 55
Avg. Citations / Paper 9.2
H-Index 5

Contact and Professional Links

Contact Information

fengs@uab.edu
2059345237

Detected Research Keywords

No research keyword data found.