I am Ang Li (李昂), a Ph.D. student in the Department of Electrical and Computer Engineering at Duke University under the supervision of Professor Yiran Chen and Hai “Helen” Li in Duke CEI Lab My primary research focuses on deep learning systems on mobile and IoT platform. I received Ph.D. in Computer Science from University of Arkansas in 2018, M.E. in Software Engineering from Peking University in 2013 and B.S. in Computer Science from Henan University in 2010.
I am currently on the academic job market.
Research Interests
- Machine Learning for mobile, IoT, and edge systems
- Federated learning
- Data-driven privacy-enhancing techniques
Awards
- ACM KDD Best Student Paper Award, 2020
- ACM/IEEE Symposium on Edge Computing (SEC) Best Student Poster Award, 2019
- ACM/IEEE Symposium on Edge Computing (SEC) Student Travel Grant, 2019
- 1st Place Graduate Poster Presentations in Computer Science track of 100th Annual Meeting of the Arkansas Academy of Science
- IEEE International Conference on Sensing, Communication and Networking (SECON) Student Travel Grant, 2016
- IEEE Military Communications Conference (MILCOM) Student Travel Grant, 2015
Selected Publications
- FedMask: Joint Computation and Communication-Efficient Personalized Federated Learning via Heterogeneous Masking
Ang Li, Jingwei Sun, Xiao Zeng, Mi Zhang, Hai Li and Yiran Chen
ACM Conference on Embedded Networked Sensor Systems (SenSys, acceptance ratio: 17.9%=25/139), 2021. - Hermes: An Efficient Federated Learning Framework for Heterogeneous Mobile Clients
Ang Li, Jingwei Sun, Pengcheng Li, Yu Pu, Hai Li and Yiran Chen,
ACM Conference On Mobile Computing And Networking (MobiCom, acceptance ratio: 17.4%=52/299), 2021. - TIPRDC: Task-Independent Privacy-Respecting Data Crowdsourcing Framework with Anonymized Intermediate Representations
Ang Li, Yixiao Duan, Huanrui Yang, Yiran Chen and Jianglei Yang,
ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (ACM KDD 2020, Best Student Paper Award, acceptance ratio: 16.9%=216/1279, video, slides, code). - MVStylizer: An Efficient Edge-Assisted Video Photorealistic Style Transfer System for Mobile Phones
Ang Li, Chungpeng Wu, Yiran Chen and Bin Ni,
International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing (ACM MobiHoc 2020, acceptance ratio: 15%=30/196, slides).
Industrial Experience
- Alibaba DAMO Academy, Research Intern, Sunnyvale, 06/2020-12/2020, 08/2021-10/2021
- Postal Savings Bank of China, Associate Manager, Beijing, 07/2013-07/2014
- NBA China, Summer Intern, Digital Media Group, Beijing, 07/2012-09/2012
