Xiaomin Ouyang

I will be joining the Department of Computer Science & Engineering, Hong Kong University of Science and Technology (HKUST) in Fall 2024 as a tenure-track Assistant Professor. I am actively looking for highly motivated students to join my group. See openings for more details. Please fill out this form and email me your CV/transcript if you are interested in. Thanks!

I am currently a postdoctoral researcher at Networked & Embedded Systems Laboratory of UCLA ECE department, working with Prof. Mani Srivastava. I obtained my Ph.D. degree from Information Engineering, The Chinese University of Hong Kong in 2023, advised by Prof. Guoliang Xing and co-advised by Prof. Jianwei Huang. I also work closely with Prof. Jiayu Zhou at Michigan State University.

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News

  • May 2024: I will be attending CPS-IoT Week in Hong Kong during May 13-May 16. We are organizing the FMSys Workshop 2024 co-located with CPS-IoT Week. I will also join in the CPS-IoT Career Forum. You're cordially invited to join us at the workshop and Forum!
  • May 2024: Give a seminar talk at College of Computing and Data Science of NTU, hosted by Prof. Rui Tan.
  • April 2024: Selected as one of mHealth Scholars.

Research

My research interest is building AI-powered mobile and IoT systems, with a primary focus on developing efficient machine learning and sensing systems for smart health applications.

  • Machine learning systems for IoT: addresses real-world challenges for advancing ML in mobile/IoT systems, such as distributed and imperfect IoT data, scalability, limited resources, and real-world system dynamics.
  • Smart health: design and deploy real-world IoT systems for personalized health monitoring and intervention, e.g., developing multi-modal federated learning systems for monitoring digital biomarkers of Alzheimer’s Disease.
  • Mobile Sensing: enhance sensing quality with physics-strengthened AI techniques, e.g., exposing texture information from ToF cameras for sensing in the dark.
Key words of my recent research topics: Multi-Modal Sensing and Learning, Federated Learning Systems, Large Language Models, Activity Recognition, Digital Biomarkers, ToF Depth Sensing Systems.

Selected Awards

Major Publications

LLMSense: Harnessing LLMs for High-level Reasoning Over Spatiotemporal Sensor Traces

Xiaomin Ouyang, Mani Srivastava

[SenSys-ML 2024] The 3rd Workshop on Machine Learning on Edge in Sensor Systems

ADMarker: A Multi-Modal Federated Learning System for Monitoring Digital Biomarkers of Alzheimer’s Disease

Xiaomin Ouyang, Xian Shuai, Yang Li, Li Pan, Xifan Zhang, Heming Fu, Sitong Chen, Xinyan Wang, Shihua Cao, Jiang Xin, Hazel Mok, Zhenyu Yan, Doris Yu, Timothy Kwok, Guoliang Xing

[MobiCom 2024] In the 30th Annual International Conference On Mobile Computing And Networking (Winter Acceptance ratio: 48/207=23.1%)

Mozart: A Mobile ToF System for Sensing in the Dark through Phase Manipulation

Zhiyuan Xie*, Xiaomin Ouyang* (*co-first authors), Li Pan, Wenrui Lu, Guoliang Xing, Xiaoming Liu

[MobiSys 2023] In the 21th Annual International Conference on Mobile Systems, Applications, and Services (Acceptance ratio: 41/198=20.7%)

Best Paper Award (1 out of 198 submissions)

[ paper] [ slides] [ codes]

Harmony: Heterogeneous Multi-Modal Federated Learning through Disentangled Model Training

Xiaomin Ouyang, Zhiyuan Xie, Heming Fu, Sitong Cheng, Li Pan, Neiwen Ling, Guoliang Xing, Jiayu Zhou, Jianwei Huang

[MobiSys 2023] In the 21th Annual International Conference on Mobile Systems, Applications, and Services (Acceptance ratio: 41/198=20.7%)

[ paper] [ slides] [ codes] [datasets]

Cosmo: Contrastive Fusion Learning with Small Data for Multimodal Human Activity Recognition

Xiaomin Ouyang, Xian Shuai, Jiayu Zhou, Ivy Wang Shi, Zhiyuan Xie, Guoliang Xing, Jianwei Huang

[MobiCom 2022] In the 28th Annual International Conference On Mobile Computing And Networking (Acceptance ratio: 56/314=17.8%)

[ paper] [ slides] [ codes]

ClusterFL: A Similarity-Aware Federated Learning System for Human Activity Recognition

Xiaomin Ouyang, Zhiyuan Xie, Jiayu Zhou, Jianwei Huang, Guoliang Xing

[MobiSys 2021] In the 19th Annual International Conference on Mobile Systems, Applications, and Services (Acceptance ratio: 36/166=21.6%)

[ paper] [ video] [ slides] [datasets] [codes]

Other Publications

Teaching Experience

    Mentering Experience

  • Pengrui Quan/Gaofeng Dong/Pragya Sharma/Jason Wu, Ph.D. Students at UCLA (with Prof. Mani Srivastava)
  • Yolanda Lau, Ph.D. Student at Department of Psychology, University College London (invited in the thesis committee)
  • Yang Li, Ph.D. Student at CUHK (with Prof. Guoliang Xing)
  • Zihan Li, Undergraduate Student at CUHK-SZ (a first-author paper under submission)
  • Shangcheng Jin, Visiting Undergraduate Student at CUHK (final year project)
  • Kaiwei Liu, Visiting Undergraduate Student at CUHK (final year project)
  • Qidong Zhai and Nan Zhang, Master Students at CUHK (final year projects)
  • Hoiying Siu and Jiaying Cheng, Undergraduate Students at CUHK (final year projects)
  • Teaching Assistant

  • IERG3310: Computer Networks, 2019 Fall/2020 Spring/2021 Spring/2022 Spring, CUHK
  • IERG1810: Electronic Circuit Design Laboratory, 2020 Fall/2021 Fall, CUHK

Professional Services

    Organizing Committee Member

  • TPC Co-Chair of FMSys Workshop 2024
  • Web Chair of ACM/IEEE IPSN 2024
  • Organizer of N2Women (Networking Networking Women) Meeting at ACM MobiSys 2023
  • Technical Program Committee Member

  • IEEE ICDCS 2024
  • ACM MobiCom 2024 Artifact Evaluation
  • ACM MobiSys 2024 Artifact Evaluation
  • ACM MobiSys 2024 Rising Star Forum
  • ACM Ubicom/ISWC 2024 Notes and Briefs
  • ACM/IEEE IoTDI Posters/Demos Program, 2023 and 2024
  • ACM SenSys 2022 Shadow Program
  • Invited Reviewer

  • IEEE INFOCOM 2022, ACM IMWUT/UbiComp 2022, 2023, 2024, ACM KDD 2021
  • IEEE Transactions on Mobile Computing (TMC), IEEE/ACM Transactions on Networking (ToN), ACM Transactions on Sensor Networks (TOSN), IEEE Internet of Things Journal (IoTJ), International Journal of Computer Vision (IJCV), IEEE Transactions on Network and Service Management (TNSM)

Modified from Jon Barron