Guanyang Wang
Scholar

Guanyang Wang

Google Scholar ID: fnDzqzIAAAAJ
Rutgers University
StatisticsProbabilityMarkov Chain Monte CarloMachine Learning
Citations & Impact
All-time
Citations
380
 
H-index
9
 
i10-index
8
 
Publications
20
 
Co-authors
18
list available
Resume (English only)
Academic Achievements
  • Papers published:
  • - Diffusion Models and Generative AI
  • - Antithetic Noise in Diffusion Models
  • - CCS: Controllable and Constrained Sampling with Diffusion Models via Initial Noise Perturbation
  • - Quantum speedup of non-linear Monte Carlo problems
  • - On importance sampling and independent Metropolis-Hastings with an unbounded weight function
  • - Spectral gap bounds for reversible hybrid Gibbs chains
  • - Repeated averages on graphs
  • - A phase transition in sampling from Restricted Boltzmann Machines
  • - Connecting Quantum Computing with Classical Stochastic Simulation
  • - Differentially Private Range Queries with Correlated Input Perturbation
  • Awards and Grants:
  • - NSF DMS-2210849
  • - NSF FET-2403007
  • - Adobe Data Science Research Award
Research Experience
  • Currently an Assistant Professor in the Department of Statistics at Rutgers University, New Brunswick. Organizes a weekly online seminar on Monte Carlo methods.
Education
  • B.S. in Mathematics from the University of Science and Technology of China (USTC) in June 2015; Ph.D. in Mathematics (Ph.D. minor in Statistics) from Stanford University in August 2020, advised by Prof. Persi Diaconis.
Background
  • Research interests include Monte Carlo methods, generative AI, quantum computing, and probability. Encourages students with a strong programming background to get in touch.
Miscellany
  • Erdős number is 2