Ping Xu (徐平)

Dr. Ping Xu is an Assistant Professor at the Computer Science department of Georgia State University (GSU). Before joining GSU, she worked as an assistant professor at the University of Texas Rio Grande Valley. She received her Ph.D. in Electrical and Computer Engineering from George Mason University advised by Prof. Zhi (Gerry) Tian. 

Her research interests span the areas of machine learning and optimization, signal processing, dynamical systems, and cooperative control. She is looking for motivated undergraduate and graduate students. If you are interested, please contact her and include your research interest, CV, transcripts, as well as writing samples (if any) in your email.  

News

• July. 2025:  I will join the Department of Computer Science at GSU as an assistant professor.

• Feb. 2025: One paper accepted by CISS 2025. See you in March!

• Oct. 2024: One paper accepted by NeurIPS 2024 Mathematics of Modern Machine Learning (M3L) Workshop. 

• Sept. 2024: Our paper on "Byzantine-Robust Decentralized Federated Learning via Local Performance Checking" is accepted by the 31st International Conference on Neural Information Processing. 

• Sept. 2024:  Our paper on "TS-FedNBS: Federated Edge Computing with Enhanced Robustness" is accepted by IEEE TCCC Workshop on Advanced Optimization and Learning for Distributed and Intelligent Systems (AOL4DIS).

• Aug. 2024: It is my great honor to be appointed as the Olegario Vazquez Rana Faculty Fellow in Science and Technology for FY25. 

• Jun. 2024: Collaborated to give a tutorial at the IEEE ICC 2024 conference in Denver and presented our paper at the IEEE ICMC 2024 conference in Qingdao. 

• May. 2024: Our paper on "Decentralized Federated Learning for Meta Computing" is accepted for presentation at IEEE ICMC 2024.

• May. 2024: Congratulations to Ethan Villalobos for wining the third place in Best Poster Award!

• Mar. 2024: Our paper on "Robust Distributed Learning Against Both Distributional Shifts and Byzantine Attacks" is accepted for publication at IEEE Transactions on Neural Networks and Learning Systems. 

• Jan. 2024: Three papers are accepted by American Society of Mechanical Engineers (ASME) 2024 Joint Rail Conference (JRC2024).

• Dec. 2023: Our paper on "Communication-Efficient Decentralized Dynamic Kernel Learning" is accepted for presentation at ICASSP 2024.

• Dec. 2023: I will present our work on "H-nobs: Achieving Certified Fairness and Robustness in Distributed Learning on Heterogeneous Datasets" at NeurIPS 2023. 

• Aug. 2023: Our paper on "QC-ODKLA: Quantized and Communication-Censored Online Decentralized Kernel Learning via Linearized ADMM" is accepted for publication at IEEE Transactions on Neural Networks and Learning Systems. 

• Aug. 2022: I was honored to be named a “Rising Star in EECS” 2022. See you in Austin!

• May 2022: I received the Outstanding Academic Achievement Award 2022 from GMU College of Computing and Engineering!