Kevin Tian
Assistant Professor
Designs algorithms for continuous optimization and robust high-dimensional statistics, such as semi-random sparse recovery.
Kevin Tian's lab at UT Austin works on learning theory & optimization and trustworthy & safe ML. 32 papers since 2023, 29 at top venues, mostly NeurIPS and COLT. 4 PhD students and 1 master's student. 2 alumni. Applications close .
At a glance
- papers, 2023–2026
- 8/ year
- at T1 venues
- 91%
- PhD students
- 4
- MS students
- 1
- alumni listed
- 2
Papers by yearfrom the lab homepage, 2023–2026
- 8 papers2026 · T1 8 · collecting
- 7 papers2025 · T1 7
- 8 papers2024 · T1 7
- 9 papers2023 · T1 7
T1 venuesOtherVenues: NeurIPS, COLT, SODA, FOCS, ICML
Research focuspaper titles that use each topic's words
- Learning theory & optimization7 papers
- recovery1 paper
- Trustworthy & safe ML0 papers
- designs algorithms0 papers
- continuous0 papers
Paper list
From the lab homepage.
20268 papers
- ICML (T1)Combinatorial Sparse PCA Beyond the Spiked Identity Model (opens in a new tab)
- COLT (T1)Functional Stochastic Localization (opens in a new tab)
- COLT (T1)On the Curse of Dimensionality in Private Sparse Covariance Estimation and PCA (opens in a new tab)
- NeurIPS (T1)Optimal Recalibration of an Online Predictor (opens in a new tab)
- NeurIPS (T1)Revisiting the Provable-Auditable Privacy Gap of DP-SGD (opens in a new tab)
- COLT (T1)Separating Oblivious and Adaptive Models of Variable Selection (opens in a new tab)
- COLT (T1)Simultaneous Blackwell Approachability and Applications to Multiclass Omniprediction
- NeurIPS (T1)Total Variation Distance Estimation in Autoregressive Models (opens in a new tab)
20257 papers
- SODA (T1)Eulerian Graph Sparsification by Effective Resistance Decomposition (opens in a new tab)
- NeurIPS (T1)More of the Same: Persistent Representational Harms Under Increased Representation (opens in a new tab)
- STOC (T1)Omnipredicting Single-Index Models with Multi-Index Models (opens in a new tab)
- NeurIPS (T1)Private Geometric Median in Nearly-Linear Time (opens in a new tab)
- FOCS (T1)Radial Isotropic Position via an Implicit Newton's Method (opens in a new tab)
- COLT (T1)Spike-and-Slab Posterior Sampling in High Dimensions (opens in a new tab)
- NeurIPS (T1)The Power of Iterative Filtering for Supervised Learning with (Heavy) Contamination (opens in a new tab)
20248 papers
- SOSAA CS guide to the quantum singular value transformation (opens in a new tab)
- COLT (T1)Black-Box k-to-1 PCA Reductions: Theory and Applications (opens in a new tab)
- COLT (T1)Closing the Computational-Query Depth Gap in Parallel Stochastic Convex Optimization (opens in a new tab)
- NeurIPS (T1)Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random (opens in a new tab)
- SODA (T1)Linear-Sized Sparsifiers via Near-Linear Time Discrepancy Theory (opens in a new tab)
- NeurIPS (T1)Private Stochastic Convex Optimization with Heavy Tails: Near-Optimality from Simple Reductions (opens in a new tab)
- NeurIPS (T1)Semi-Random Matrix Completion via Flow-Based Adaptive Reweighting
- NeurIPS (T1)Testing Calibration in Nearly-Linear Time (opens in a new tab)
20239 papers
- COLT (T1)Algorithmic Aspects of the Log-Laplace Transform and a Non-Euclidean Proximal Sampler (opens in a new tab)
- —Foundations of Computer Science (FOCS), 2023
- FOCS (T1)Matrix Completion in Almost-Verification Time (opens in a new tab)
- SODA (T1)Private Convex Optimization in General Norms (opens in a new tab)
- SPAAQuadratic Speedups in Parallel Sampling from Determinantal Distributions (opens in a new tab)
- ICML (T1)Quantum Speedups for Zero-Sum Games via Improved Dynamic Gibbs Sampling (opens in a new tab)
- NeurIPS (T1)Revisiting Area Convexity: Faster Box-Simplex Games and Spectrahedral Generalizations (opens in a new tab)
- COLT (T1)Semi-Random Sparse Recovery in Nearly-Linear Time (opens in a new tab)
- NeurIPS (T1)Structured Semidefinite Programming for Recovering Structured Preconditioners (opens in a new tab)
Where alumni went2 listed
Apply to UT AustinFall 2027
Computer Science PhD
- Round
- Single round (Dec 15)
- Opens
- GRE
- See program page
- English
- See program page
- Fee
- See program page
Not yet confirmed for this intake.
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