Gang Huang

Gang Huang 

Gang Huang, Ph.D.
Senior Researcher
Zhejiang Lab
Hangzhou, Zhejiang, China, 311121



I am currently a Senior Researcher (equiv. Associate Professor) at Zhejiang Lab, leading a research section for scientific artificial intelligence. I completed the doctoral training at Zhejiang University and Argonne National Laboratory.


We are actively hiring motivated and energetic researchers/engineers. Visiting scholars and interns are also welcome. Please send me an email if you are interested.

Research Interests

My research interests lie at the intersection of electrical engineering, computer science, and operations research. A common thread in my research is designing reliable and computationally efficient algorithms for mission-critical tasks. Currently, I am working on developing scientific artificial intelligence methods to leverage the power of data and knowledge, with applications in energy and transportation systems.

Latest News

  • 07/2022: One patent for optimal power flow is granted.

  • 06/2022: Our paper ‘‘Compound Batch Normalization for Long-tailed Image Classification’’ is accepted by the 30th ACM International Conference on Multimedia (MM '22).

  • 04/2022: Our paper ‘‘Federated Learning on Heterogeneous and Long-Tailed Data via Classifier Re-Training with Federated Features’’ is accepted by the 31st International Joint Conference on Artificial Intelligence (IJCAI '22).

  • 04/2022: I am invited to serve as a Program Committee Member for the 2022 European Conference on Machine Learning & Principles and Practice of Knowledge Discovery in Databases (ECML '22).

  • 03/2022: I am invited to serve as a Committee Member for the 2022 International Conference on Smart Grid and Energy Systems (SGES '22).

  • 02/2022: Our paper ‘‘Coordinated System Frequency Control with a Hybrid Knowledge-Data Driven Algorithm’’ is accepted by Proceedings of the CSEE.

  • 02/2022: One patent for autonomous driving is granted.

  • 01/2022: Our paper ‘‘Crossmodal Transformer Based Generative Framework for Pedestrian Trajectory Prediction’’ is accepted by the 39th IEEE Conference on Robotics and Automation (ICRA '22).

  • 12/2021: I am invited to serve as a Reviewer for Zhejiang Lab Open Fund.

  • 10/2021: I am invited to serve as a Reviewer for CCAI Innovation Grants.

  • 10/2021: I am invited to give a talk at VALSE 2021.

  • 09/2021: One patent for optimal power flow is granted.

  • 08/2021: I am elected as a Committee Member for CCF-Hangzhou.

  • 08/2021: Our work is presented at KDD 2021.

  • 07/2021: Our work is presented at ICML 2021.

  • 06/2021: Our paper ‘‘Learning Optimal Power Flow with Infeasibility Awareness’’ is accepted by the 38th International Conference on Machine Learning Workshop (ICML '21).

  • 05/2021: Our paper ‘‘AliCG: Fine-grained and Evolvable Conceptual Graph Construction for Semantic Search at Alibaba’’ is accepted by the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '21).

  • 05/2021: I am invited to serve as a Reviewer for NSFC.

  • 04/2021: Our paper ‘‘Cascading Imbalance in Coupled Gas-Electric Energy Systems’’ is accepted by Energy.

  • 03/2021: Our paper ‘‘Smart Grid Dispatch Powered by Deep Learning: A Survey’’ is accepted by Frontiers of Information Technology and Electronic Engineering.

  • 01/2021: Our paper ‘‘Serverless Distributed Learning for Smart Grid Analytics’’ is accepted by Chinese Physics B.