Tianhao Wang
Assistant Professor
Studies the theoretical foundations of deep learning at the intersection of optimization and statistics.
Tianhao Wang's lab at UCSD works on learning theory & optimization and data management & big data. 15 papers since 2023, 11 at top venues, mostly ICLR and ICML. Applications close .
At a glance
- papers, 2023–2026
- 4/ year
- at T1 venues
- 73%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom the lab homepage, 2023–2026
- 3 papers2026 · T1 3 · collecting
- 4 papers2025 · T1 3
- 6 papers2024 · T1 3
- 2 papers2023 · T1 2
T1 venuesOtherVenues: ICLR, ICML, NeurIPS, AISTATS, COLT
Research focuspaper titles that use each topic's words
- Learning theory & optimization5 papers
- Data management & big data0 papers
- theoretical0 papers
- intersection0 papers
- hal0 papers
Paper list
From the lab homepage.
20263 papers
- ICLR (T1)A Tale of Two Geometries: Adaptive Optimizers and Non-Euclidean Descent (opens in a new tab)
- ICLR (T1)Taming Polysemanticity in LLMs: Provable Feature Recovery via Sparse Autoencoders (opens in a new tab)
- TMLR (T1)Through the Judge’s Eyes: Inferred Thinking Traces Improve Reliability of LLM Raters (opens in a new tab)
20254 papers
- ICLR (T1)Can Neural Networks Achieve Optimal Computational-statistical Tradeoff? An Analysis on Single-Index Model (opens in a new tab)
- AISTATS (T1)How well can Transformers emulate in-context Newton’s method? (opens in a new tab)
- OPTProvable Benefit of Sign Descent: A Minimal Model Under Heavy-Tail Class Imbalance (opens in a new tab)
- ICML (T1)Structured Preconditioners in Adaptive Optimization: A Unified Analysis (opens in a new tab)
20246 papers
- Information and Inference: A Journal of the IMAApproximate Message Passing for orthogonally invariant ensembles: Multivariate non-linearities and spectral initialization (opens in a new tab)
- Annals of StatisticsMaximum likelihood for high-noise group orbit estimation and single-particle cryo-EM (opens in a new tab)
- ICLR (T1)The Marginal Value of Momentum for Small Learning Rate SGD (opens in a new tab)
- COLT (T1)Training dynamics of multi-head softmax attention for in-context learning: emergence, convergence, and optimality (opens in a new tab)
- Annals of Applied ProbabilityUniversality of Approximate Message Passing algorithms and tensor networks (opens in a new tab)
- NeurIPS (T1)Unveiling Induction Heads: Provable Training Dynamics and Feature Learning in Transformers (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
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Data
Some numbers could not be verified:
- The member list could not be found on the lab site.
- The alumni list could not be found on the lab site.
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- Members
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- Alumni
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