Padé Approximants and the Anharmonic Oscillator
Desai, Krish. (2020). "Padé Approximants and the Anharmonic Oscillator." Yale University. MS Mathematics Thesis.
CV
Education
- Ph.D. in Physics, University of California, Berkeley, August 2020 – May 2025
- Dissertation: Machine learning methods for particle collider data
- Advisor: Prof. Benjamin Nachman
- M.S. in Mathematics, Yale University, August 2017 – May 2020
- B.S. in Mathematics (Intensive) with Distinction, Yale University, August 2017 – May 2020
- B.S. in Physics (Intensive) with Distinction, Yale University, August 2017 – May 2020
Work experience
- 2025 - Present: Postdoctoral Research Fellow
- Lawrence Berkeley National Laboratory
- Machine Learning Researcher in Physics Division
- Research focus: Machine learning methods for particle physics data analysis
- 2020 - 2025: Graduate Student Researcher
- University of California, Berkeley
- Department of Physics
- Research on neural networks for unfolding and symmetry discovery in high-energy physics
- Advisor: Prof. Benjamin Nachman
Skills
- Machine Learning
- Deep Learning (PyTorch, TensorFlow, JAX)
- Generative Models (GANs, Normalizing Flows, Diffusion Models)
- Probabilistic Inference and Uncertainty Quantification
- Programming Languages
- Python (Advanced)
- C++ (Proficient)
- Julia (Familiar)
- Physics & Data Analysis
- High Energy Physics (ROOT, Geant4)
- Statistical Methods (Unfolding, Hypothesis Testing)
- Particle Detector Simulation
- Mathematics
- Differential Geometry
- Group Theory and Symmetries
- Statistical Inference
Publications
Symmetry Discovery with Deep Learning
Desai, K., Nachman, B., & Thaler, J. (2021). Symmetry Discovery with Deep Learning. NeurIPS ML4PS 117 (2021)
Oblivious points on translation surfaces
Adelstein, I., Desai, K., Ji, A., & Zdeblick, G. (2022). Oblivious points on translation surfaces. Journal of Geometry, 113(1), 6.
SymmetryGAN
Desai, K., Nachman, B., & Thaler, J. (2022). SymmetryGAN. Physical Review D, 105(9), 096031.
Deconvolving Detector Effects for Distribution Moments
Desai, K., Nachman, B., & Thaler, J. (2022). Deconvolving Detector Effects for Distribution Moments. NeurIPS ML4PS, 43.
Multidimensional Deconvolution with Profiling
Zhu, H., Desai, K., Kuusela, M., Mikuni, V., Nachman, B., & Wasserman, L (2024) Multidimensional Deconvolution with Profiling. NeurIPS ML4PS (150).
Neural Posterior Unfolding
Acosta, F. T., Chan, J., Desai, K., Mikuni, V., Nachman, B., & Pan, J. (2024) Neural Posterior Unfolding. NeurIPS ML4PS (177).
Moment Unfolding
Desai, K., Nachman, B., & Thaler, J. (2024). Moment extraction using an unfolding protocol without binning. Physical Review D, 110(11), 116013.
Unbinned Inference with Correlated Events
Desai, K., Long, O., & Nachman, B. (2025). Unbinned Inference with Correlated Events. arXiv:2504.14072.
Machine Learning Methods for Cross Section Measurements
Desai, Krish. (2025). Machine Learning Methods for Cross Section Measurements. University of California, Berkeley. PhD Physics Dissertation.
Talks
Closed Geodesics on Translation Surfaces
Talk at Massachusetts Undergraduate Research Conference, Amherst, MA
Oblivious Points on Translation Surfaces
Talk at Young Mathematicians Conference, Columbus, OH
Symmetry Discovery using Machine Learning
Talk at American Physical Society, Virtual
Symmetry Discovery
Talk at Lawrence Berkeley National Laboratory, Physics Division Seminar, Virtual
SymmetryGAN
Talk at Machine Learning for Jets, Heidelberg, Germany
Symmetry Discovery and Deep Learning
Talk at Clarifai Perceive Deep Learning AI Conference, Virtual
Introduction to Symmetry Discovery and Deep Learning
Talk at Berkeley Compass Lecture, Berkeley, CA
Symmetry Discovery with Deep Learning
Talk at Thirty-Fifth Annual Conference on Neural Information Processing Systems, Virtual
Moment Unfolding using Deep Learning
Talk at American Physical Society, New York, NY
High Energy Physics Seminar
Talk at Korea Institute for Advanced Study, Seoul, South Korea
Moment Unfolding with Deep Learning
Talk at Machine Learning for Jets, New Brunswick, NJ
Deconvolving Detector Effects for Distribution Moments
Talk at Thirty-Sixth Annual Conference on Neural Information Processing Systems, New Orleans, USA
Moment extraction using an unfolding protocol without binning
Talk at PHY-STAT Unfolding Conference, Paris, France
CMS Seminar
Talk at CERN, Geneva, Switzerland
Multidimensional Deconvolution with Profiling
Talk at Thirty-Eighth Annual Conference on Neural Information Processing Systems, Vancouver, Canada
Neural Posterior Unfolding
Talk at Thirty-Eighth Annual Conference on Neural Information Processing Systems, Vancouver, Canada
Teaching
Service and leadership
- Currently signed in to 43 different slack teams