Purnamrita Sarkar
Associate Professor
Studies statistical machine learning on networks, community detection and theory of streaming and online learning algorithms.
Purnamrita Sarkar's lab at UT Austin works on learning theory & optimization, recognition, detection & segmentation and graph mining & networks. 17 papers since 2023, 17 at top venues, mostly NeurIPS and COLT. 5 alumni, most often to Amazon and Google DeepMind. Applications close .
At a glance
- papers, 2023–2026
- 4/ year
- at T1 venues
- 100%
- PhD students
- 0
- MS students
- 0
- alumni listed
- 5
Papers by yearfrom the lab homepage, 2023–2026
- 6 papers2026 · T1 6 · collecting
- 5 papers2025 · T1 5
- 5 papers2024 · T1 5
- 1 papers2023 · T1 1
T1 venuesOtherVenues: NeurIPS, COLT, ICML, AISTATS, Operations Research
Research focuspaper titles that use each topic's words
- Learning theory & optimization2 papers
- Graph mining & networks1 paper
- Recognition, detection & segmentation0 papers
- data sciences0 papers
- community0 papers
Paper list
From the lab homepage.
20266 papers
- ICML (T1)Combinatorial Sparse PCA Beyond the Spiked Identity Model
- NeurIPS (T1)Low-Dimensional Adaptation of Rectified Flow: A Diffusion and Stochastic Localization Perspective
- NeurIPS (T1)Minimax-Optimal Kernel Two-sample Testing in Sub-quadratic Time
- AISTATS (T1)On the Convergence and Straightness of Rectified Flow
- COLT (T1)On the Curse of Dimensionality in Private Sparse Covariance Estimation and PCA
- NeurIPS (T1)One-Shot Private Confidence Regions via Resampling
20255 papers
- UAI (T1)Beyond Sin-Squared Error: Linear Time Entrywise Uncertainty Quantification for Streaming PCA
- NeurIPS (T1)Dimension-free Score Matching and Time Bootstrapping for Diffusion Models
- NeurIPS (T1)Low-precision streaming PCA
- ICML (T1)Optimal Transfer Learning for Missing Not-at-Random Matrix Completion
- COLT (T1)Spike-and-Slab Posterior Sampling in High Dimensions
20245 papers
- Operations Research (T1)Incentive-Aware Models of Financial Networks
- NeurIPS (T1)Keep or toss? A nonparametric score to evaluate solutions for noisy ICA
- NeurIPS (T1)Oja's algorithm for Sparse PCA
- NeurIPS (T1)On Differentially Private U-statistics
- NeurIPS (T1)Transfer Learning for Latent Variable Network Models
20231 paper
- NeurIPS (T1)Streaming PCA for Markovian Data
Where alumni went5 listed, 100% to industry
Industry 4Academia 0
Most often to
- Amazon
- Google DeepMind
- Meta
Apply to UT AustinFall 2027
Computer Science PhD
- Round
- Single round (Dec 15)
- 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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- Papers
- The lab homepage
- Members
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