I am a Computer Science Ph.D. student focusing on Machine Learning at University of Southern California, Los Angeles, USA. Previously, I was an R&D Team Manager and Staff Software Engineer at Tencent (2014-2018), a Team Leader and Senior Software Engineer at Baidu (2012-2014), and a Software Engineer at Huawei (2011-2012).
I have a strong background in Internet industrial level Research and Development, including cloud computing architecture, machine learning, AI computing platform, distributed systems, mobile computing, and embedded operating system. I have more than three years of experience in Internet R&D management, leading a team with 10-20 software engineers and researchers to build commercial Internet products. The Internet Products that I worked for include Tencent Cloud, Tencent WeChat Automotive / AI in Car, Tencent Games, Tencent Maps, Baidu Maps, and Huawei Smartphone.
Currently, my academic advisors are Professor Salman Avestimehr (USC, machine learning theory, distributed learning, federated learning), Professor Mahdi Soltanolkotabi (USC, convex/non-convex optimization, deep learning theory) and Professor Tong Zhang (HKUST, machine learning optimization, AutoML, CV/NLP); I also worked with Professor Murali Annavaram (USC, distributed training system).
In general, I am interested in ML+System. From the perspective of ML, my research interest is machine learning algorithms, modeling, systems and their applications on computer vision, natural language processing, and Data Mining. In the system domain, I am particularly interested in distributed systems, cloud computing, mobile computing, embedded operating systems. Currently, I am focusing on distributed and automated machine learning:
1. Large-scale distributed training algorithm and system for extremely large DNN models (Transformers, BERT, DLRM, Video Recognition, Vision+Language, etc)
2. Federated learning algorithms, models, systems, and analytics.
3. Automated machine Learning (AutoML), neural architecture search (NAS), Efficient Model Architecture Design.
5. Cutting-edge models and their applications, such as Transformers, Graph neural networks, GAN, etc.
6. Machine Learning Theory, Information Theory
7. Open source software; large-scale computer system architecture design.