Homepage - Zuobin Xiong, Ph.D.

Zuobin Xiong

(Wade-Giles: Tso-pin Hsiung)

Assistant Professor
Department of Computer Science
University of Nevada, Las Vegas

zuobin.xiong(at)unlv.edu

About Me

Curriculum Vitae

I am an Assistant Professor in the Department of Computer Science at University of Nevada, Las Vegas (UNLV) and Co-Director of the Information and Intelligent Security Lab. I received my Ph.D. in Computer Science from Georgia State University in 2023, under the supervision of Dr. Wei Li and Dr. Zhipeng Cai. My research lies at the intersection of artificial intelligence, cybersecurity, and privacy, with the overarching goal of developing secure, privacy-preserving, and trustworthy AI systems. My research has been published in leading conferences and journals, including ICML, AAAI, ECML, ICDM, ACM Computing Surveys (CSUR), IEEE Transactions on Industrial Informatics (TII), IEEE Transactions on Dependable and Secure Computing (TDSC), IEEE Transactions on Vehicular Technology (TVT), and IEEE Internet of Things Journal (IoT-J). I actively serve the academic community as an Associate Editor of IEEE Transactions on Neural Networks and Learning Systems (TNNLS), IEEE Networking Letters, and Elsevier's High-Confidence Computing. I also serve as a Program Committee for leading conferences and journals and have served as a panelist for the NSF Secure and Trustworthy Cyberspace (SaTC) program and other funding agencies.

Research Vision

We study how to make modern AI systems trustworthy and reliable under real-world constraints such as distributed data, adversarial environments, heterogeneous resources, and limited supervision via:

Distributed Machine Learning

Generative Models

Machine Unlearning

Trustworthy AI

Internet of Things (IoT)

Cybersecurity

💡🚀 I am looking for self-motivated students with strong mathematical and programming skills to work with me on the research projects described above. If you are interested in joining our research group, please email me your detailed CV, academic transcripts, and a writting sample in one PDF file with the subject line: "Your Name - PhD Applicantion for 20XX Fall/Spring".

Experience

University of Nevada Las Vegas

Assistant Professor
Department of Computer Science

2023.07 - Present
University of Southern California

Visiting Scholar, Supported by NSF
Department of Computer Science

2026.06 - 2026.08
University of Southern California

Visiting Scholar, Supported by NSF
Department of Computer Science

2025.07 - 2025.08

Education

Georgia State University

Ph.D. in Computer Science
Department of Computer Science

2018.08 - 2023.06
Harbin Engineering University

M.E. in Computer Science
Department of Computer Science

2016.09 - 2019.03
Northeast Forestry University

B.S. in Mathematics
Department of Mathematics

2012.09 - 2016.06

Awards & Grants

National Science Foundation

REU: Hands-On Research in Federated Learning Security through Red Team vs. Blue Team Exercises

Co-PI, $460,922

2026 - 2029
National Science Foundation

HSI: A Guided Pathway to Enhancing HSI Student Experience and Success in Generative AI with the Planting of Education Oriented GPU Cluster

PI, $200,000

2025 - 2027
National Science Foundation

EPSCoR Research Fellows: An Explainable AI Supported Performance Monitoring System in Distributed Sustainable Energy Networks

Sole PI, $300,000

2025 - 2027
NSF HDRFS Seed

Harnessing Data Revolution for Fire Science (HDRFS) Data Analytics Mentor

PI, $4,750

2025 - 2025
University of Nevada Las Vegas Foundation

Are You Ready for College? An Explainable AI-Supported Efficient Solution for College Students Mental Health Condition Detection and Beyond

PI, $35,000

2024 - 2026
South Korea IITP

Intelligent IoT Security - Next-Generation Cyber Defense Mechanisms and Vulnerability Exploration Using Language Models

Co-PI, $357,739

2024 - 2026
National Science Foundation

RII Track-2 FEC AI SUSTEIN Seed Grant

PI, $30,000

2023 - 2025

News

2026

📖 Our paper "AI4Fire: Evaluating Large Language Models on Wildfire Tasks" is available on Arxiv !

Oct 16

📖 Our paper "FAIRITHM: Unlearning Bias and Rewriting for Fairness" has been accepted to the International Journal of Human-Computer Interaction (IJHCI) !

Sep 16

📖 Our paper "Machine Learning over Encrypted Data: A Survey of Fully Homomorphic Encryption for AI Systems" has been accepted to the Artificial Intelligence Review (AIR) !

Sep 14

📖 Our paper "GONE: Structural Knowledge Unlearning via Neighborhood-Expanded Distribution Shaping" has been accepted to the Empirical Methods in Natural Language Processing (EMNLP 2026) in Budapest!

Aug 21

📖 Our paper "Membership is Ownership: A Robust Ownership Verification Framework for Diffusion Models" has been accepted to the IEEE International Conference on Data Mining (ICDM 2026). See you in Shenyang, China this winter!

Aug 16

I will be visiting the University of Southern California (USC) in Los Angeles as a visiting scholar this summer, and I am looking forward to meeting my collaborators and exploring new opportunities for collaboration.

May 31

📖 Our paper "Watch Your Step: Information Injection in Diffusion Models via Shadow Timestep Embedding" has been accepted to the International Conference on Machine Learning (ICML 2026). See you in Seoul, South Korea this summer!

Apr 29

📖 Two papers are accepted to the International Conference on Computer Communications and Networks (ICCCN 2026). See you in Hawaii!

Apr 26

⭐ Our NSF REU project "Hands-On Research in Federated Learning Security through Red Team vs. Blue Team Exercises" is selected for funding by National Science Foundation.

Apr 20

Our benchmark paper "GONE: Structural Knowledge Unlearning via Neighborhood-Expanded Distribution Shaping" is available on Arxiv.

Mar 20

Selected Publications (view all )

Co-UPP: A Co-optimized UAV Path Planning Framework for Balancing Truth Discovery and Environmental Sensing in Mobile CrowdSensing

TVT 2026

Ziqiang Zhang, Yingjie Wang, Haojun Teng, Wenhan Hou, Zuobin Xiong, Zhipeng Cai

IEEE Transactions on Vehicular Technology (TVT) 2026

Research Vision

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Experience

Education

Awards & Grants

News

Selected Publications (view all )

Co-UPP: A Co-optimized UAV Path Planning Framework for Balancing Truth Discovery and Environmental Sensing in Mobile CrowdSensing

Co-UPP: A Co-optimized UAV Path Planning Framework for Balancing Truth Discovery and Environmental Sensing in Mobile CrowdSensing

FAIRITHM: Unlearning Bias and Rewriting for Fairness

FAIRITHM: Unlearning Bias and Rewriting for Fairness

Machine Learning over Encrypted Data: A Survey of Fully Homomorphic Encryption for AI Systems

Machine Learning over Encrypted Data: A Survey of Fully Homomorphic Encryption for AI Systems

GONE: Structural Knowledge Unlearning via Neighborhood-Expanded Distribution Shaping

GONE: Structural Knowledge Unlearning via Neighborhood-Expanded Distribution Shaping

Membership is Ownership: A Robust Ownership Verification Framework for Diffusion Models

Membership is Ownership: A Robust Ownership Verification Framework for Diffusion Models

Watch Your Step: Information Injection in Diffusion Models via Shadow Timestep Embedding

Watch Your Step: Information Injection in Diffusion Models via Shadow Timestep Embedding

A Survey of Machine Unlearning in Generative AI Models: Methods, Applications, Security, and Challenges

A Survey of Machine Unlearning in Generative AI Models: Methods, Applications, Security, and Challenges

Appro-Fun: Approximate Machine Unlearning in Federated Setting

Appro-Fun: Approximate Machine Unlearning in Federated Setting

Exact-Fun: An Exact and Efficient Federated Unlearning Approach

Exact-Fun: An Exact and Efficient Federated Unlearning Approach

Federated Generative Model on Multi-Source Heterogeneous Data in IoT

Federated Generative Model on Multi-Source Heterogeneous Data in IoT

Towards Neural Network-Based Communication System: Attack and Defense

Towards Neural Network-Based Communication System: Attack and Defense

A Self-Supervised Purification Mechanism for Adversarial Samples

A Self-Supervised Purification Mechanism for Adversarial Samples

Generative Adversarial Networks: A Survey Toward Private and Secure Applications

Generative Adversarial Networks: A Survey Toward Private and Secure Applications

Privacy Threat and Defense for Federated Learning With Non-i.i.d. Data in AIoT

Privacy Threat and Defense for Federated Learning With Non-i.i.d. Data in AIoT

All publications