Rahul Parhi
Assistant Professor
Studies the mathematics of neural networks using functional analysis and nonparametric statistics.
Rahul Parhi's lab at UCSD works on learning theory & optimization. 20 papers since 2023, 8 at top venues, mostly NeurIPS and JMLR. 5 PhD students. Applications close .
At a glance
- papers, 2023–2026
- 5/ year
- at T1 venues
- 40%
- PhD students
- 5
- MS students
- 0
- alumni listed
- —
Papers by yearfrom the lab homepage, 2023–2026
- 6 papers2026 · T1 4 · collecting
- 7 papers2025 · T1 3
- 2 papers2024 · T1 1
- 5 papers2023 · T1 0
T1 venuesOtherVenues: NeurIPS, JMLR, COLT, ICLR, TMLR
Research focuspaper titles that use each topic's words
- neural networks5 papers
- Learning theory & optimization3 papers
- nonparametric0 papers
- mathematics0 papers
- statistics0 papers
Paper list
From the lab homepage.
20266 papers
- SIAM ReviewCompositional Function Spaces for Deep Learning (opens in a new tab)
- NeurIPS (T1)Does Sparse Connectivity Improve Generalization? Convolutional Networks Below the Edge of Stability
- ICLR (T1)Generalization Below the Edge of Stability: The Role of Data Geometry (opens in a new tab)
- TMLR (T1)LoLA: Low-Rank Linear Attention with Sparse Caching (opens in a new tab)
- IEEE Transactions on Computational ImagingNonasymptotic Convergence Rates for Plug-and-Play Methods With MMSE Denoisers (opens in a new tab)
- NeurIPS (T1)Sharpness of Minima in Deep Matrix Factorization
20257 papers
- COLT (T1)A Gap Between the Gaussian RKHS and Neural Networks: An Infinite-Center Asymptotic Analysis (opens in a new tab)
- EMBCBrain-Body Coupling in Listening to Metronomic Sounds and Music (opens in a new tab)
- SIAM Journal on Mathematics of Data ScienceFunction-Space Optimality of Neural Architectures with Multivariate Nonlinearities (opens in a new tab)
- JMLR (T1)Random ReLU Neural Networks as Non-Gaussian Processes (opens in a new tab)
- NeurIPS (T1)Stable Minima of ReLU Neural Networks Suffer from the Curse of Dimensionality: The Neural Shattering Phenomenon (opens in a new tab)
- SampTAUpper Bounds on Averaged Sampling Numbers for General Model Classes (opens in a new tab)
- Applied and Computational Harmonic AnalysisWeighted Variation Spaces and Approximation by Shallow ReLU Networks (opens in a new tab)
20242 papers
20235 papers
- SampTAA Continuous Transform for Localized Ridgelets (opens in a new tab)
- IEEE Signal Processing MagazineDeep Learning Meets Sparse Regularization: A signal processing perspective (opens in a new tab)
- SampTAModulation Spaces and the Curse of Dimensionality (opens in a new tab)
- IEEE Transactions on Information TheoryNear-Minimax Optimal Estimation With Shallow ReLU Neural Networks (opens in a new tab)
- IEEE Signal Processing LettersThe Sparsity of Cycle Spinning for Wavelet-Based Solutions of Linear Inverse Problems (opens in a new tab)
Where alumni went
Alumni are not listed on the lab homepage.
Apply to UCSDFall 2027
UCSD CSE Computer Science PhD
- Round
- Single round
- Opens
- —
- GRE
- See program page
- English
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- Fee
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Not yet confirmed for this intake.
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Data
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- The alumni list could not be found on the lab site.
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