# Biography

I am an assistant professor in the Department of Computer Science and Engineering, University of Connecticut (UConn). Before that, I was a research staff member at NEC Labs America in Princeton, NJ, since July 2016. In June 2016, I received my Ph.D. degree in the Department of Electrical and Computer Engineering from University of California San Diego (UCSD) with the guidance of Prof. David A. Meyer. My thesis committee includes Prof. Lawrence Saul, Prof. Nuno Vasconcelos, Prof. Gert Lanckriet, and Prof. Julian McAuley. I also work closely with Prof. Dacheng Tao from the University of Sydney.

I have broad research interests in machine learning, data mining, deep learning, federated learning, and related applications for time series representation, similarity search, prediction/forecasting, and anomaly detection (with data from IoT devices, healthcare, smart city, environmental science, etc.). I am also interested in graph representation learning with applications to link prediction, node classification, recommendation, dynamic systems, etc.

Recruiting: Looking for Ph.D. students to jointly work with Prof. Bing Wang at UCONN CSE! If you are interested in working on machine learning/deep learning/reinforcement learning/federated learning, please send me an email with your CV and transcript.

News
Feb 2023 One paper is accepted to Annual Conference on Information Sciences and System (CISS) 2023, Congratulations to Yushan!
Jan 2023 Two papers are accepted to ICLR 2023! Congratulations to Chang, Yang, and all collaborators!
Dec 2022 Our tutorial proposal about “Continual Graph Learning” is accepted to WWW 2023! Congratulations to Xikun, Yushan, and Zijie!
Dec 2022 I am invited to serve as an Associate Editor for Neurocomputing journal (IF=5.719)!
Dec 2022 I will serve as a Senior PC for IJCAI 2023!
Nov 2022 I am invited to give a talk about “Continual Graph Learning” at the CS department of University of Central Florida on November 17th, 2022!
Nov 2022 Our tutorial proposal about “Continual Graph Learning” is accepted to SDM 2023! Congratulations to Xikun, Yushan, and Zijie!
Nov 2022 One paper is accepted to Smart Health and another paper gets accepted to Computational and Structural Biotechnology Journal! Congratulations to all collaborators!
Oct 2022 One paper is accepted to IEEE International Conference on Big Data! Congratulations to Wei and all co-authors!
Oct 2022 I am invited to give a talk about “Harnessing Deep Neural Networks for Multivariate Time Series Analysis” at the CS department of University of Georgia on Oct 28th, 2022! Link
Oct 2022 I am honored to received another Gift Fund from NEC Labs America (NECLA) as Sole PI! Thanks for the support, NECLA!
Sep 2022 Two papers are accepted to NeurIPS 2022 (one to the main track and one to the dataset and benchmark track)! Congratulations to Yang, Xikun, and all collaborators!
Sep 2022 One paper about Continual Graph Learning (CGL) is accepted to ICDM 2022! Congratulations to Xikun!
More News…

### Interests

• Machine Learning
• Data Mining
• Deep Learning
• Time Series Analysis
• Graph Representation Learning
• Federated Learning

### Education

• Ph.D. in ECE, 2016

University of California, San Diego (UCSD)

• MPhil, 2010

The Hong Kong Polytechnic University

• B.Eng, 2007

University of Science and Technology of China (USTC)