CV
Krish Desai, PhD
Summary
PhD in Physics from University of California, Berkeley. Machine Learning Researcher at Lawrence Berkeley National Laboratory.
Education
- Ph.D. in Physics2020-08 — 2025-05University of California, Berkeley
- M.S. in Mathematics2017-08 — 2020-05Yale University
- B.S. in Mathematics (Intensive) with Distinction2017-08 — 2020-05Yale University
- B.S. in Physics (Intensive) with Distinction2017-08 — 2020-05Yale University
Work Experience
- Machine Learning Researcher2020-09 — 2025-05Lawrence Berkeley National LaboratoryResearch at the intersection of machine learning and high energy physics. Development of novel computational methods for analyzing particle physics data. Collaboration with international teams on ATLAS experiment data analysis.
- Investment Analyst Intern2023-06 — 2023-08Bridgewater AssociatesSystematic trading research and execution. Development of Bayesian Hierarchical Networks for market liquidity prediction and transaction cost minimization.
- PhD Research Intern2022-05 — 2022-08Microsoft ResearchTheoretical and computational research on non-local field theory from matrix models. Collaboration with Jaron Lanier on applications to optimization problems.
- Software Developer Intern2020-05 — 2020-07Purple Gaze Inc.Development of AI-driven glint detection algorithms for eye-tracking software. Real-time image processing pipeline implementation in Python and C++.
Skills
Programming Languages
- Python
- Julia
- C
- MATLAB
Machine Learning
- TensorFlow/Keras
- PyTorch
- scikit-learn
- Deep Learning
- Bayesian Methods
- Generative Models
Data Science
- Statistical Inference
- Bayesian Statistics
- Monte Carlo Methods
- Unfolding
- Deconvolution
Physics & Mathematics
- Particle Physics
- Quantum Field Theory
- Stochastic Calculus
- Operator Theory
- Differential Geometry
Computing
- High Performance Computing
- Git
- Docker
Publications
- Machine Learning Methods for Cross Section Measurements2025University of California, Berkeley
- Unbinned Inference with Correlated Events2025arXiv
- Moment Unfolding2024Physical Review D
- Neural Posterior Unfolding2024NeurIPS ML4PS
- Multidimensional Deconvolution with Profiling2024NeurIPS ML4PS
- Deconvolving Detector Effects for Distribution Moments2022NeurIPS ML4PS
- SymmetryGAN2022Physical Review D
- Oblivious points on translation surfaces2021Journal of Geometry
- Symmetry Discovery with Deep Learning2021NeurIPS 2021
- Padé Approximants and the Anharmonic Oscillator2020Yale University
Presentations
- Neural Posterior Unfolding2024Thirty-Eighth Annual Conference on Neural Information Processing SystemsVancouver, Canada
- Multidimensional Deconvolution with Profiling2024Thirty-Eighth Annual Conference on Neural Information Processing SystemsVancouver, Canada
- CMS Seminar2024CERNGeneva, Switzerland
- Moment extraction using an unfolding protocol without binning2024PHY-STAT Unfolding ConferenceParis, France
- Deconvolving Detector Effects for Distribution Moments2022Thirty-Sixth Annual Conference on Neural Information Processing SystemsNew Orleans, USA
- Moment Unfolding with Deep Learning2022Machine Learning for JetsNew Brunswick, NJ
- High Energy Physics Seminar2022Korea Institute for Advanced StudySeoul, South Korea
- Moment Unfolding using Deep Learning2022American Physical SocietyNew York, NY
- Symmetry Discovery with Deep Learning2021Thirty-Fifth Annual Conference on Neural Information Processing SystemsVirtual
- Introduction to Symmetry Discovery and Deep Learning2021Berkeley Compass LectureBerkeley, CA
- Symmetry Discovery and Deep Learning2021Clarifai Perceive Deep Learning AI ConferenceVirtual
- SymmetryGAN2021Machine Learning for JetsHeidelberg, Germany
- Symmetry Discovery2021Lawrence Berkeley National Laboratory, Physics Division SeminarVirtual
- Symmetry Discovery using Machine Learning2021American Physical SocietyVirtual
- Closed Geodesics on Translation Surfaces2019Massachusetts Undergraduate Research ConferenceAmherst, MA
- Oblivious Points on Translation Surfaces2019Young Mathematicians ConferenceColumbus, OH
Teaching
- Introduction to Mathematical PhysicsFall 2023University of California, BerkeleyRole: Associate Instructor
- Data Science Applications in PhysicsFall 2022University of California, BerkeleyFall 2024Role: Associate Instructor
- Introduction to Computational Techniques in PhysicsFall 2022University of California, BerkeleySummer 2023Role: Associate InstructorSummer 2024Fall 2024
- Introductory PhysicsSpring 2022University of California, BerkeleyRole: Head Associate Instructor
- Physics for Scientists and EngineersFall 2020University of California, BerkeleySpring 2021Role: Associate InstructorSummer 2021
Languages
- English
- French
- Hindi
- Gujarati
Honors and Fellowships
- Election to Sigma Xi2025Scientific Research Honor Society, Full Membership
- Election to Sigma Pi Sigma2021Physics Honor Society, Lifetime Membership
- Howard L. Schultz Prize2020Yale UniversityThe most outstanding graduating senior in physics at Yale
- George J. Schulz Summer Fellowship2020Yale UniversityExcellence in physical science research
- Howard Robert Topol Fellowship2019Yale UniversityExcellence in mathematical research
Service and Leadership
- Invited Journal Peer Reviewer2025Nature, Scientific Reports
- Invited Journal Peer Reviewer2025Journal of High Energy Physics
- Invited Conference Peer Reviewer2022, 2024NeurIPS
- Committee Member2021 — 2024UC Berkeley Physics Faculty Search