About me

I’m Liting Chen, a first-year Ph.D. student specializing in Operations Management and Retail Management at McGill University supervised by Prof. Maxime Cohen and Prof. Sentao Miao.

My academic journey has been focused on pioneering research in intelligent decision-making. At Microsoft Research Asia and Google Cloud, I’ve applied my expertise in real-world settings, developing big-data solutions. My work encompasses contributions to cloud optimization, network optimization, and the practical application of academic research in industry.

I welcome the chance to collaborate and engage in meaningful discussions with experts in technology and research. Please feel free to contact me if you’re interested in exploring collaborative ventures.


Conservative State Value Estimation for Offline Reinforcement Learning
Liting Chen, Jie Yan, Zhengdao Shao, Lu Wang, Qingwei Lin, Saravan Rajmohan, Thomas Moscibroda, Dongmei Zhang
Advances in Neural Information Processing Systems (NeurIPS), 2023

Scalable Vertiport Hub Location Selection for Air Taxi Operations in a Metropolitan Region
Liting Chen, Sebastian Wandelt , Weibin Dai, Xiaoqian Sun
INFORMS Journal on Computing, 2022

Solving the Batch Stochastic Bin Packing Problem in Cloud: a Chance-constrained Optimization Approach
Jie Yan, Yunlei Lu, Liting Chen, Si Qin, Yixin Fang, Qingwei Lin, Thomas Moscibroda, Saravan Rajmohan, Dongmei Zhang
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2022

A Surrogate Objective Framework for Prediction+ Programming with Soft Constraints
Kai Yan, Jie Yan, Chuan Luo, Liting Chen, Qingwei Lin, Dongmei Zhang
Advances in Neural Information Processing Systems (NeurIPS), 2021


  • McGill University, Montreal, Canada (2023.9-present)
    PhD student, Operations Management and Retail Management
  • Beihang University, Beijing, China (2020.9-2023.1)
    Master of Traffic Information Engineering and Control
  • Beihang University, Beijing, China (2016.9-2020.6)
    Bachelor of Electronic Information Engineering

Industry Experience

  • Research Associate, Microsoft Research Asia (Jan. 2023 – Sep. 2023)
    • Derived a policy from a static dataset; the paper is published in NeurIPS.
    • Focused on using LLM for decision making.
  • Customer Engineer Intern, Google Cloud (June 2022 – Sep. 2022)
    • Earned certifications as a Google Associate Cloud Engineer, Professional Cloud Architect, and Professional Machine Learning Engineer.
    • Hands-on big-data engineering and analytics: developed a blockchain information collection and analysis platform on Google Cloud.
  • Research Intern, Microsoft Research Asia (May 2021 – May 2022)
    • Analyzed Prediction+Optimization framework; the paper is published in NeurIPS.
    • Studied the bin packing problem in resources deployment in cloud; the paper is published in KDD.
  • Outreach Intern, Outreach Group, Didi Chuxing (June 2020 – Sep. 2020)
    • Focused on research collaboration and program management to strengthen ties between industry, university, and research.

Academic Service

Reviewer for NeurIPS2023, ICLR2024, and ICML2024

Honors and Awards

NeurIPS 2023 Scholar Award
NeurIPS 2023 Top Reviewer
Star of tomorrow intern award in Microsoft Research Asia
National Scholarship (2018-2019)
National Scholarship (2020-2021)
1st place in Women’s Powerlifting competition at Beihang University (2022)