Hello and welcome!

I am a tenure-track Assistant Professor in the Data Science and Analytics (DSA) Thrust at the Information Hub, The Hong Kong University of Science and Technology (Guangzhou).

I lead the Sustainable Computing (SusCom) Lab, where we apply machine learning and data science techniques to address computational sustainability challenges, particularly focusing on AI infrastructure. Our current research interests include:

  • Energy-efficient AI model serving, with a special emphasis on large language models (LLMs);
  • Computational resource management, including scheduling, dispatching, and orchestrating, in cloud and edge environments.

We are also interested in developing (real) intelligent and practical solutions for power monitoring, modeling, and control in smart homes & buildings. Typical research problems we are tackling include:

  • Non-intrusive load monitoring (NILM) for smart homes;
  • Integrating LLM agents into building energy systems (BESs).
Recruitment: I am actively seeking self-motivated PhD students, RAs, and Interns to join my research group. If you are interested, please send your CV and transcripts to my email below.

Email: guomingtang [at] hkust-gz [dot] edu [dot] cn

News

  • Nov. 2024: Our paper on real-world NILM system deployment won the Best Paper Award of SustainCom’24.
  • Sept. 2024: Our work on NILM systems got accepted to SustainCom’24.
  • Jun. 2024: Our work on low-carbon edge computing system got accepted to ICPP’24.
  • Mar. 2024: One paper got accepted to IEEE TPDS.
  • Jan. 2024: Two papers got accepted to IEEE Network and TMC, respectively.
  • Dec. 2023: One Paper got accepted to IEEE TPDS.
  • Nov. 2023: Two papers got accepted to IEEE TGCN and IoT-J, respectively.
  • Aug. 2023: One survey paper got accpeted to ACM Computing Surveys.
  • Aug. 2023: Three papers got accepted to IEEE IoT-J.
  • May. 2023: One paper got accepted to ICDCS’23.
  • May. 2023: FedNILM was published by IEEE TGCN.
  • Apr. 2023: HyEdge got accepted to ACM TIOT.