Guanyang Wang   王冠扬

Guanyang Wang Assistant Professor Department of Statistics Rutgers University, New Brunswick Contact Department of Statistics Office 453, Hill Center 110 Frelinghuysen Road Piscataway, NJ 08854 Email: guanyang.wang [at] rutgers [dot] edu

About me

Welcome! I am an assistant professor in the Department of Statistics at Rutgers University, New Brunswick.

My research lies broadly in MCMC methods, Bayesian Statistics, statistical machine learning and probability. I am also actively learning quantum computing recently. Feel free to contact me if you would like to chat about interests we may share. My research is partially supported by NSF DMS-2210849. Thank you, NSF!

I received my Ph.D. in Mathematics (Ph.D. minor in Statistics) from Stanford University in August 2020, advised by Prof. Persi Diaconis. Prior to that, I received my B.S. with Honors in Mathematics from University of Science and Technology of China (USTC) in Jun 2015.

My Erdős number is 2 with multiplicity 2 :) ( [1] and [2] )

People

I am lucky to work with many talented students. If you are looking for interns with strong quantitative and/or engineering background (e.g., data scientist, research scientist, quantitative researcher, machine learning engineer, etc), feel free to contact me.

• Yasa Syed (Statistics, third year Ph.D. student)

• Wei Yuan (Statistics, second year Ph.D. student)

• Budhaditya Halder (Statistics, second year Ph.D. student)

• Tianze Wang (Statistics, first year Ph.D. student)

• Yuchen Wei (Mathematics, fourth year Ph.D. student)

• Nilava Metya (Mathematics, first year Ph.D. student)

Recent News

• Paper Optimal randomized multilevel Monte Carlo for repeatedly nested expectations with Yasa Syed accepted in International Conference on Machine Learning (ICML) (Apr, 2023).

• Paper Unbiased Multilevel Monte Carlo methods for intractable distributions: MLMC meets MCMC with Tianze Wang accepted with minor revision in the Journal of Machine Learning Research (JMLR) (Mar, 2023).

• Paper Metropolis–Hastings transition kernel couplings with John O'Leary accepted in Annales de l'Institut Henri Poincaré (B) Probabilités et Statistiques (AIHP) (Jan, 2023).

• Together with Peng Zhang in the Computer Science department, we received the Adobe Data Science Research Award for project "Improving the Design of Randomized Controlled Trials via Discrepancy Theory”. (Sep, 2022)
  

• New preprint on Spectral telescope: Convergence rate bounds for random-scan Gibbs samplers based on a hierarchical structure with Qian Qin (Aug, 2022).

• Guanyang received the NSF award DMS-2210849 as PI (July, 2022).

• Guanyang awarded the ORAU Ralph E. Powe Junior Faculty Enhancement Award (June, 2022).

• New preprint on Repeated averages on graphs with Ramis Movassagh and Mario Szegedy (May, 2022).

Recent Research Works

• Optimal randomized multilevel Monte Carlo for repeatedly nested expectations
  Yasa Syed^**, Guanyang Wang
  International Conference on Machine Learning (ICML), 2023

• Spectral telescope: Convergence rate bounds for random-scan Gibbs samplers based on a hierarchical structure
  Qian Qin, Guanyang Wang^*
  Minor revision, Annals of Applied Probability (AoAP)

• Unbiased Multilevel Monte Carlo methods for intractable distributions: MLMC meets MCMC
  Tianze Wang ^**, Guanyang Wang
  Minor revision, Journal of Machine Learning Research (JMLR). [Code] [Slides]

• Prediction and Design of Protease Enzyme Specificity Using a Structure-Aware Graph Convolutional Network
  Changpeng Lu, Joseph H. Lubin, Vidur S. Sarma, Samuel Z. Stentz, Guanyang Wang, Sijian Wang, Sagar D. Khare
  In revision, Proceedings of the National Academy of Sciences (PNAS).

• Repeated averages on graphs
  Ramis Movassagh, Mario Szegedy, Guanyang Wang^*
  submitted

Miscellaneous

• Chinese Painting Generation Using Generative Adversarial Networks
  Guanyang Wang, Ying Chen, Yuan Chen
  CS231n Course Project, 2017. [Chinese Painting Dataset]