香港中文大学（深圳）24年 PhD/MPhil/Postdoc 多媒体网络系统/大模型优化/联邦学习

Openings


香港中文大学（深圳）王方鑫教授课题组招收24年入学（Spring/Fall）博士、硕士、Postdoc、RA，方向为多媒体网络与系统，3D视频系统，大模型优化，以及联邦学习等。主页请见 这里


Introduction of Professor

Fangxin Wang is an assistant professor at The Chinese University of Hong Kong, Shenzhen (CUHKSZ). He received his Ph.D., M.Eng., and B.Eng. degree all in Computer Science and Technology from Simon Fraser University, Tsinghua University, and Beijing University of Posts and Telecommunications, respectively. Before joining CUHKSZ, he was a postdoctoral fellow at the University of British Columbia. Dr. Wang's research interests include Multimedia Systems and Applications, 3D Volumetric Video System, Large Model Adaptation and Optimization, and Distributed Machine Learning. He leads the intelligent networking and multimedia lab (INML) at CUHKSZ. He has published more than 50 papers at top journal and conference papers, including INFOCOM, Multimedia, VR, ToN, TMC, IOTJ, etc. He was selected in the 8th Young Elite Scientist Sponsorship Program, CUHKSZ Presidential Young Scholar, and a recipient of SFU Dean's Convocation Medal for Academic Excellence. He served as the TPC chairs of IEEE Satellite 2023, Associate Editor of Transactions on Mobile Computing, TPC members of IWQoS, ICC, BigCom and reviewer of many top conference and journals.


Research directions
Generally, our group has two major research direction as follows. Applicants with backgorund/interest in one of the following will be preferred.
- Multimedia Networking and System: We work to improve the multimedia service and quality of experience from the pespective of networking, communication and system.
        - Immersive Video Streaming: To explore how to deliver good streaming for on-demand, live, realtime and immersive services, with a focus on networking metrics such as latency, bandwidth and loss.
        - 3D Volumetric Video System: To build holistic, practical, light-weight 3D volumetric video systems and provide fully interactive and photorealistic experience.
- Edge Intelligence: We work to merge AI and edge network, empowering more intelligent edge computing services with AI capacity, and also enhancing AI models with edge optimization.
        - Large Model Adaptation: To strengthen the adaptation ability of large models in networking, communication and system fields.
        - Distributed ML system/optimization: To solve the problems from the intersection of distributed ML, federated learning, and edge computing.


Qualification and requirements

PhD and MPhil Students: I have multiple PhD and MPhil positions. Please apply here
- Holding a Bachelor\/Master degree with CS\/CE\/EE\/EIE\/Math from a top tier university (985/211 or equivalent).
- Passion and determination in our research and related project.
- Qualified academic performance and good hands-on ability.
- Applicants with related publication or research experience or competition award will be preferred.
- Fluent English writing ability.

Undergraduate RA: I always encourage UG student to participate or even lead research projects.
- For CUHKSZ students, just feel free to contact me if you are interested in our projects. Drop me an email introducing yourself with your CV and transcript.
- For non-CUHKSZ students, the RA position is usually full-time. RA with strong performance will have a clear advantage towards PhD application.


How to apply

Drop me an email introducing yourself with CV, transcript and ranking (bachelor and master if applicable), publications (if any), award and language certificate. Please indicate clearly which position you would like to apply. The email title should be  [PhD/MPhil/Postdoc/RA Application]Name-University-Major] for better management.