Constantine Caramanis
Professor
Studies decision-making in large-scale systems, including robust optimization, high-dimensional statistics and learning theory.
Constantine Caramanis's lab at UT Austin works on learning theory & optimization and reinforcement learning. 17 papers since 2023, 13 at top venues, mostly NeurIPS and ICLR. 29 alumni, most often to Google and Apple. Applications close .
At a glance
- papers, 2023–2026
- 4/ year
- at T1 venues
- 76%
- PhD students
- 0
- MS students
- 0
- alumni listed
- 29
Papers by yearfrom the lab homepage, 2023–2026
- 0 papers2026 · T1 0 · collecting
- 5 papers2025 · T1 4
- 7 papers2024 · T1 5
- 5 papers2023 · T1 4
T1 venuesOtherVenues: NeurIPS, ICLR, AAAI, COLT, CVPR
Research focuspaper titles that use each topic's words
- Learning theory & optimization1 paper
- Reinforcement learning1 paper
- robust optimization0 papers
- high-dimensional statistics0 papers
- high-dimensional0 papers
Paper list
From the lab homepage.
20255 papers
- NeurIPS (T1)Anchored Diffusion Language Model
- ICLR (T1)Infilling Score: A Pretraining Data Detection Algorithm for Large Language Models
- In International Conference on Machine Learning (ICML).On Mitigating Affinity Bias through Bandits with Evolving Biased Feedback
- ICLR (T1)RB-Modulation: Training-Free Personalization of Diffusion Models Using Stochastic Optimal Control
- ICLR (T1)Semantic Image Inversion and Editing Using Rectified Stochastic Differential Equations
20247 papers
- CVPR (T1)Beyond First-Order Tweedie: Solving Inverse Problems Using Latent Diffusion
- AAAI (T1)Contextual Pandora’s Box
- IEEE Transactions on Information TheoryGlobal Optimality of the EM Algorithm for Mixtures of Two-Component Linear Regressions
- JMLR (T1)On the Computational and Statistical Complexity of over-Parameterized Matrix Sensing
- NeurIPS (T1)Optimization Can Learn Johnson Lindenstrauss Embeddings
- In International Conference on Machine Learning (ICML).Prospective Side Information for Latent MDPs
- NeurIPS (T1)RL in Latent MDPs Is Tractable: Online Guarantees via Off-Policy Evaluation
20235 papers
- COLT (T1)Beyond Uniform Smoothness: A Stopped Analysis of Adaptive SGD
- NeurIPS (T1)Logarithmic Bayes Regret Bounds
- NeurIPS (T1)Optimizing Solution-Samplers for Combinatorial Problems: The Landscape of Policy-Gradient Methods
- In International Conference on Machine Learning (ICML), 18057-82.Reward-Mixing MDPs with Few Latent Contexts Are Learnable
- NeurIPS (T1)Solving Linear Inverse Problems Provably via Posterior Sampling with Latent Diffusion Models
Where alumni went29 listed, 64% to industry
Industry 16Academia 9
Most often to
- Apple
- Meta
Also to
- Georgia Tech
- UT Austin
- Cornell University
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
- Lab homepage
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