Vishwak Srinivasan
Scholar

Vishwak Srinivasan

Google Scholar ID: MW4-PPgAAAAJ
Massachusetts Institute of Technology
OptimisationSamplingStatistical Machine Learning
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Citations & Impact
All-time
Citations
73
 
H-index
5
 
i10-index
5
 
Publications
9
 
Co-authors
0
 
Contact
No contact links provided.
Publications
3 items
Near-Optimal Private Linear Regression via Iterative Hessian Mixing
2026
Cited
0
Designing Algorithms for Entropic Optimal Transport from an Optimisation Perspective
2025
Cited
0
The Gaussian Mixing Mechanism: Renyi Differential Privacy via Gaussian Sketches
2025
Cited
0
Resume (English only)
Academic Achievements
  • - Publications:
  • * Fast sampling from constrained spaces using the Metropolis-adjusted Mirror Langevin algorithm (COLT 2024)
  • * High-accuracy sampling from constrained spaces with the Metropolis-adjusted Preconditioned Langevin Algorithm (ALT 2025)
  • * The Gaussian Mixing Mechanism: Renyi Differential Privacy via Gaussian Sketches (NeurIPS 2025)
  • * Designing Algorithms for Entropic Optimal Transport from an Optimisation Perspective (pre-print, under submission)
  • * Understanding two-scale criteria for Poincaré and log-Sobolev inequalities in the Euclidean case through Φ-entropies (pre-print)
  • - Reviewer for conferences: NeurIPS (2021, 2022 [Top Reviewer], 2023 [Top Reviewer], 2024, 2025), ICML (2022, 2023, 2024, 2025), AISTATS (2025), COLT (2025), AAAI (2026)
Research Experience
  • - Teaching Assistant at MIT: 6.7830 (prev. 6.435) - Bayesian Modelling and Inference [Spring 2025], 6.7810 (prev. 6.438) - Algorithms for Inference [Fall 2023]
  • - Teaching Assistant at Carnegie Mellon University: 10-725 - Convex Optimisation [Spring 2020, Fall 2020]
Education
  • - PhD: Massachusetts Institute of Technology, EECS department, advised by Ashia Wilson
  • - MS: Carnegie Mellon University, Machine Learning Department
  • - BS: Indian Institute of Technology Hyderabad, major in Computer Science and Engineering, graduated with honors
Background
  • - Research Interests: optimisation and sampling, optimal transport, statistical learning theory
  • - Professional Field: Computer Science and Engineering
  • - Brief Introduction: PhD student in the EECS department at MIT, advised by Ashia Wilson, and also closely work with Andre Wibisono at Yale University.
Miscellany
  • - Personal Interests: Recreational mathematics
  • - Other Professional Service: EECS Communication Lab Fellow (2024-), EECS Graduate Student Association (2022-2023), MIT Graduate Student Council as EECS Department Representative (2022-2024), Ashdown House Coffee Hour Committee (2021-2023)
  • - Served on the MIT EECS PhD Admissions Committee (2024), CMU MLD MS Admissions Committee (2020)
Co-authors
0 total
Co-authors: 0 (list not available)