I am a third year Ph.D. student in Statistics at the University of British Columbia. My research interests are Bayesian statistics and machine learning, and am currently working with Dr. Trevor Campbell from UBC’s Department of Statistics on developing fast and accurate large-scale Bayesian inference methods using data summarization techniques.

Apart from academics, I enjoy running and playing tennis. I have finished a half marathon race. I also work actively as a certified official (chair/line umpire) with the ITF, ATP, WTA, and Tennis Canada.

News

• [May, 2025] Our paper Tuning-free coreset Markov chain Monte Carlo via Hot DoG has been accepted to UAI 2025.
• [April, 2025] I received the 2024 Statistics Graduate Teaching Assistant Award.
• [January, 2024] Our paper Coreset Markov chain Monte Carlo has been accepted to AISTATS 2024.
• [April, 2023] Our paper MixFlows: principled variational inference via mixed flows has been accepted to ICML 2023.
• [September, 2022] Our paper Bayesian inference via sparse Hamiltonian flows has been accepted to NeurIPS 2022 with oral designation.
• [March, 2022] I will be starting my Ph.D. at UBC in September.
• [Septempber, 2020] Received the 2019 Nash Medal.
• [Feburay, 2020] I received an Honourable Mention of the 2020 CRA Outstanding Undergraduate Researcher Award.
• [July, 2019] I received the 2019 Dr John & Barbara Petkau Scholarship.

Publications

• Tuning-free coreset Markov chain Monte Carlo via Hot DoG [PMLR] [arXiv]
  Naitong Chen, Jonathan H. Huggins, Trevor Campbell
  Uncertainty in Artificial Intelligence, 2025
• Coreset Markov chain Monte Carlo [PMLR] [arXiv]
  Naitong Chen, Trevor Campbell
  International Conference on Artificial Intelligence and Statistics, 2024
• MixFlows: principled variational inference via mixed flows [PMLR] [arXiv]
  Zuheng Xu, Naitong Chen, Trevor Campbell
  International Conference on Machine Learning, 2023
• Bayesian inference via sparse Hamiltonian flows [NeurIPS] [arXiv] [oral]
  Naitong Chen, Zuheng Xu, Trevor Campbell
  Advances in Neural Information Processing Systems, 2022

Thesis

• Bayesian inference via sparse Hamiltonian flows [UBC library]
  Naitong Chen

Education

• Ph.D. in Statistics, University of British Columbia, 2022 - Present
• M.Sc. in Statistics, University of British Columbia, 2020 - 2022
• B.Sc. in Statistics, University of British Columbia, 2015 - 2020

Work

• Software Developer Co-op, SAP Vancouver, 2018
  Commenting and collaboration feature of SAP Analytics Cloud

Teaching

• Guest Lecturer, STAT 406, University of British Columbia, 2023
  Methods for Statistical Learning
• Teaching Assistant, STAT 406, University of British Columbia, 2022 - 2023
  Methods for Statistical Learning
• Teaching Assistant, STAT 406, University of British Columbia, 2022 - 2023
  Methods for Statistical Learning
• Teaching Assistant, STAT 344, University of British Columbia, 2024
  Sample Survey
• Teaching Assistant, STAT 305, University of British Columbia, 2024 - 2025
  Introduction to Statistical Inference
• Teaching Assistant, STAT 200, University of British Columbia, 2018 - 2019, 2023 - 2024
  Elementary Statistics for Applications

Awards

• 2024 Statistics Graduate Teaching Assistant Award
• 2022 Oral designation for our NeurIPS paper Bayesian inference via sparse Hamiltonian flows
• 2020 Honourable Mention of the CRA Outstanding Undergraduate Researcher Award
• 2019 Nash Medal
• 2019 Dr John & Barbara Petkau Scholarship