Assistant Professor Division of Natural and Applied Science, Data Science Duke Kunshan University, Kunshan, Jiangsu 215000, P.R. China Email: pg180@duke.edu [Resume] [Google Scholar] [中文主页]

About Me

I am an Assistant Professor of Data Science at Duke Kunshan University. My research lies at the intersection of parallel computing, stochastic optimization, data mining, and machine learning, with applications in route optimization, recommendation systems, and large-scale decision-making.

Prior to joining Duke Kunshan University, I received my Ph.D. in Applied Mathematics & Statistics from Stony Brook University in 2021, and my M.S. in Applied Mathematics & Statistics from Stony Brook University in 2018.

Research Interests

• Parallel computing and large-scale optimization
• Stochastic optimization and reinforcement learning
• Data mining and intelligent recommendation systems
• Machine learning applications in transportation and career planning

Educations

Ph.D. Stony Brook University (2018.12 ~ 2021.12) Supervised by Prof. Wei Zhu & Prof. Keli Xiao Department: Applied Mathematics & Statistics, Statistics Track Awards: AMS Graduate Award [Excellence in Research]

M.S. Stony Brook University (2017.8 ~ 2018.12) Department: Applied Mathematics & Statistics, Computational Applied Mathematics Track

Honors

• Best Oral Paper Award, International Conference on Brain Inspired Cognitive Systems (BICS), 2025
• Best Paper Award, Workshop on Information Technologies and Systems (WITS), 2024
• Best Paper Award, ACM TMC International Workshop, 2021

Work Experience

Samsung Research America

• Research Intern (2021.05 – 2021.08)

Duke Kunshan University

• Assistant Professor, Data Science (2022.07 – present)

Teaching Experience

Duke Kunshan University

• MATH 105: Calculus
• MATH 202: Linear Algebra
• STATS 303: Statistical Machine Learning

Stony Brook University

• AMS 560: Big Data Systems, Algorithms and Networks
• AMS 527: Numerical Analysis II; AMS 528: Numerical Analysis III
• AMS 510: Analytical Methods for Applied Mathematics and Statistics (Recitation Instructor; Mean Score: A-)

Publications

• From efficiency to equity: A multi-user paradigm in mobile route optimization.
  Pengzhan Guo*, Keli Xiao.
  Electronic Commerce Research and Applications, 2024. [Impact Factor: 5.94]

• Preference-constrained career path optimization: An exploration space-aware stochastic model.
  Pengzhan Guo, Keli Xiao, Hengshu Zhu and Qingxin Meng.
  ICDM, 2023. [CCF B]

• Intelligent Career Planning via Stochastic Subsampling Reinforcement Learning.
  Pengzhan Guo, Keli Xiao, Zeyang Ye, Hengshu Zhu and Wei Zhu.
  Scientific Report, 2022. [Impact Factor: 4.379]

• Route Optimization via Environment-Aware Deep Network and Reinforcement Learning
  Pengzhan Guo, Keli Xiao, Zeyang Ye and Wei Zhu.
  ACM Transactions on Intelligent Systems and Technology (TIST), 2021. [Impact Factor: 4.654]

• Weighted Aggregating Stochastic Gradient Descent for Parallel Deep Learning.
  Pengzhan Guo, Zeyang Ye, Keli Xiao and Wei Zhu.
  IEEE Transactions on Knowledge and Data Engineering (TKDE), 2020. [Impact Factor: 6.977]

• A Weighted Aggregating SGD for Scalable Parallelization in Deep Learning.
  Pengzhan Guo, Zeyang Ye and Keli Xiao.
  Proceedings of the 19th IEEE International Conference on Data Mining (ICDM-19). [CCF B]