I am currently a Research Associate in Qualcomm AI Research. Before joining Qualcomm, I obtained Ph.D. from Duke University under the supervision of Professor Yiran Chen and Hai “Helen” Li in Duke CEI Lab.  I will join the Department of Electrical and Computer Engineering at University of Maryland, College Park as a tenure-track assistant professor. My research interests lie in the intersection of machine learning and edge computing, with a focus on building large-scale networked and trustworthy intelligent systems to solve practical problems in a collaborative, scalable, secure, and ubiquitous manner.

Openings: I’m looking for highly motivated Ph.D. and master students, and research interns to join my group. If you are interested, please send an email to ang.li630@duke.edu with you CV and transcripts attached.

News

• 2022/09: Our paper “FedSEA: A Semi-Asynchronous Federated Learning Framework for Extremely Heterogeneous Devices” has been accepted by SenSys 2022!
• 2022/09: Our paper “GraphFL: A Federated Learning Framework for Semi-Supervised Node Classification on Graphs” has been accepted by ICDM 2022!
• 2022/07: Very honored to co-chair the 3rd DistributedML workshop co-located with CoNEXT 2022. We welcome works at the intersection of distributed systems, machine learning, and networks, submission date is 09/16/2022. Participation is highly encouraged, see you there!
• 2021/09: Our paper “FL-WBC: Enhancing Robustness against Model Poisoning Attacks in Federated Learning from a Client Perspective” has been accepted by NeurIPS 2021!
• 2021/09: Our paper “FedMask: Joint Computation and Communication-Efficient Personalized Federated Learning via Heterogeneous Masking” has been accepted by SenSys 2021!
• 2021/08: Our paper “Hermes: An Efficient Federated Learning Framework for Heterogeneous Mobile Clients” has been accepted to MobiCom 2021!
• 2021/03: Our paper “Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective” has been accepted by CVPR 2021!
• 2021/01: Our paper “DeepObfuscator” has been accepted by IoTDI 2021!
• 2020/08: Ang received Best Student Paper Award from KDD’20.

Research Interests

• Machine Learning for mobile, IoT, and edge devices
• Federated learning
• Data-driven privacy-enhancing techniques