Shuang Li
Ph.D. candidate in Industrial Engineering
The H. Milton Stewart School of Industrial and Systems Engineering
Main Building 425E
Atlanta, GA 30318
Georgia Institute of Technology

Email: sli370@gatech.edu

Biography

I am a Ph.D. candidate in Industrial Engineering (specialization in Statistics) at Georgia Institute of Technology. I am very fortunate to work with Prof. Yao Xie and Prof. Le Song. I received B.E. in Automation from University of Science and Technology, China in 2011, and M.S. in Statistics from Georgia Institute of Technology in 2014.

I interned at Google in summer 2018, working on deep learning for user behavior modeling.

[Google Scholar] [Curriculum Vitae]

Research Interests

I am broadly interested in data science and statistics problems with applications in healthcare, smart city and information networks. Very often data collected from such domain are rich in event data, time series and spatial observations. I develop methods for the modeling, segmentation, detection, prediction, sequential analysis and decision making under such data. More specifically, I have been working on problems related to:

  • Generative and deep learning models for time series and point processes

  • Reinforcement learning and Markov decision process

  • Changepoint detection and sequential hypothesis test

News

Nov. 2018, I present "Scan B-statistic for Kernel Change-point Detection" and "Detecting Weak Changes in Dynamic Events over Networks" in 2018 INFORMS.

Oct. 2018, I have one paper "Detecting Weak Changes in Dynamic Events over Networks" selected for the finalists of 2018 INFORMS Social Media analytics student paper competition.

Sep. 2018, I have one paper "Scan B-statistic for Kernel Change-point Detection" selected for the finalists of 2018 INFORMS QSR Best student paper Competition.

Sep. 2018, I have one paper "Learning Temporal Point Processes via Reinforcement Learning" accepted by NIPS, spotlight (top 3.5%).

Awards

Publications

Journal

  • Scan B-statistic for Kernel Change-point Detection
    Shuang Li, Yao Xie, Hanjun Dai, and Le Song
           — accepeted by Sequential Analysis, in press.
           — Finalist of 2018 INFORMS QSR Best student paper Competition
           — accepted in part to NIPS 2015

  • Detecting Weak Changes in Dynamic Events over Networks
    Shuang Li, Yao Xie, Mehrdad Farajtabar, Apurv Verma, and Le Song
    IEEE Transactions on Signal and Information Processing over Networks, Vol. 3, No. 2, June 2017.
           — Finalist of 2018 INFORMS Social Media analytics Best student paper Competition

Book Chapter

Conference

Workshop

Preprint

Teaching Assistant

Services

Program Committee/External Reviewer for:
  • ICML: 2016, 2017, 2018, 2019

  • NIPS: 2017, 2018

  • AAAI: 2018, 2019

  • ICASSP: 2018, 2019

  • AISTATS: 2019