Qi Xia
Department of Computer ScienceMcGlothlin-Street Hall
College of William and Mary
Williamsburg, VA 23185-8795
Born in Bengbu, China and raised in Zhumadian, China, Qi Xia received his Bachelor's Degree of Statistics from University of Science and Technology of China in 2016. Now he is pursuing his Ph.D Degree of Computer Science in The College of William and Mary advised by Prof. Qun Li.
2012-2016
Hefei, China
B.S. in Statistics, University of Science and Technology of China
2016-2021
Williamsburg, VA, USA
Ph.D. in Computer Science, The College of William and Mary
Aug. 2021 - Now
Software engineer, machine learning in LinkedIn Ads AI team, Sunnyvale, CA
Auto-placement.
June 2020 - Aug. 2020
Machine learning engineer intern in LinkedIn Ads AI team, Sunnyvale, CA
Built an auto bidding system for LinkedIn Audience Network.
Aug. 2019
IJCAI 19 in Macau, China
Present FABA: An Algorithm for Fast Aggregation against Byzantine Attacks in Distributed Neural Networks.
May 2019 - Aug. 2019
Software engineer intern in Uber AdTech Targeting team, Palo Alto, CA
Built an uplift random forest model on spark for advertisement targeting.
Oct. 2018
SEC 18 in Bellevue, WA
Present A Privacy-Preserving Deep Learning Approach for Face Recognition with Edge Computing.
Aug. 2018 - May. 2019
William and Mary
Teaching Assistant for Algorithms.
Jul. 2018
HotEdge 18 in Boston, MA
Present eSGD: Communication Efficient Distributed Deep Learning on the Edge.
Sep. 2016 - May 2018
William and Mary
Teaching Assistant for Discrete Structure.
Aug. 2015 - Feb. 2016
University of Science and Techonology of China
Teaching Assistant for Computational Methods.
Jul. 2015 - Aug. 2016
Hong Kong University of Science and Technology
Research Intern
Feb. 2015 - Jun. 2015
University of Science and Technology of China
Teaching Assitant for Linear Algebra.
Dec. 2021
Defending Against Byzantine Attacks in Quantum Federated Learning
Qi Xia, Zeyi Tao, Qun Li (The 17th International Conference on Mobility, Sensing and Networking)
Dec. 2021
Efficient Privacy-Preserving Federated Learning for Resource-Constrained Edge Devices
Jindi Wu, Qi Xia, Qun Li (17th International Conference on Mobility, Sensing and Networking)
Dec. 2021
QuantumFed: A Federated Learning Framework for Collaborative Quantum Training
Qi Xia, Qun Li (2021 IEEE Global Communications Conference)
Dec. 2021
CE-SGD: Communication-Efficient Distributed Machine Learning
Zeyi Tao, Qi Xia, Qun Li, Songqing Chen (2021 IEEE Global Communications Conference)
Sep. 2021
ToFi: An Algorithm to Defend against Byzantine Attacks in Federated Learning
Qi Xia, Zeyi Tao, Qun Li (17th EAI International Conference on Security and Privacy in Communication Networks)
June 2021
Neuron Manifold Distillation for Edge Deep Learning
Zeyi Tao, Qi Xia, Qun Li (2021 IEEE/ACM 29th International Symposium on Quality of Service)
Mar. 2021
A Survey of Federated Learning for Edge Computing: Research Problems and Solutions
Qi Xia, Winson Ye, Zeyi Tao, Jindi Wu, Qun Li (High-Confidence Computing)
Feb. 2021
Privacy Issues in Edge Computing
Qi Xia, Zeyi Tao, Qun Li (Fog/Edge Computing For Security, Privacy, and Applications, Springer)
Oct. 2020
Defenses against Byzantine Attacks in Distributed Deep Neural Networks
Qi Xia, Zeyi Tao, Qun Li (Transactions on Network Science and Engineering)
Aug. 2019
FABA: An Algorithm for Fast Aggregation against Byzantine Attacks in Deep Neural Networks
Qi Xia, Zeyi Tao, Zijiang Hao, Qun Li (2019 International Joint Conferences on Artificial Intelligence)
July, 2019
A Survey of Virtual Machine Management in Edge Computing
Zeyi Tao, Qi Xia, Zijiang Hao, Cheng Li, Lele Ma, Shanhe Yi, Qun Li (Proceedings of the IEEE)
Byzantine Tolerant Algorithms for Federated Learning
Under submission