Ambuj Tewari
Professor, Statistics
Studies machine learning theory and sequential decision making, with applications in chemistry and psychiatry.
Ambuj Tewari's lab at Michigan works on learning theory & optimization, reinforcement learning and proteins, drugs & materials. 67 papers since 2023, 41 at top venues, mostly NeurIPS and AISTATS. 8 PhD students and 2 master's students. 88 alumni. Applications close .
At a glance
- papers, 2023–2026
- 17/ year
- at T1 venues
- 61%
- PhD students
- 8
- MS students
- 2
- alumni listed
- 88
Papers by yearfrom the lab homepage, 2023–2026
- 18 papers2026 · T1 10 · collecting
- 20 papers2025 · T1 11
- 19 papers2024 · T1 13
- 10 papers2023 · T1 7
T1 venuesOtherVenues: NeurIPS, AISTATS, ICML, COLT, TMLR
Research focuspaper titles that use each topic's words
- Learning theory & optimization28 papers
- Reinforcement learning23 papers
- Proteins, drugs & materials1 paper
- sequential decision0 papers
- psychiatry0 papers
Paper list
From the lab homepage.
202618 papers
- COLT (T1)A characterization of list language identification in the limit
- PNAS (T1)A semantic-based community model for high-fidelity tuning of olfactory mixture distances
- Analytical MethodsAvoiding and reducing microplastic false positives from dry glove contact
- NeurIPS (T1)Compute aligned training: Optimizing for test time inference
- AISTATS (T1)Conformal robust control of linear systems
- ICLR (T1)Continuum transformers perform in-context learning by operator gradient descent
- SIAM/ASA Journal on Uncertainty QuantificationDistribution-free robust predict-then-optimize in function spaces
- NeurIPS (T1)From non-convex to strongly convex: Curvature-adaptive FTPL for online optimization
- S. Ejaz Ahmed, Pierre Alquier, Yi Li, and Shuangge Ma, editors, Statistical Foundations and Applications of Artificial Intelligence, Machine Learning and Deep Learning. SpringerIf generative AI is the answer, what is the question?
- ACS Measurement Science AuImproved microplastic identification from simultaneously collected photothermal infrared and Raman spectra using multi-view conformal prediction
- TMLR (T1)Learning to partially defer for sequences
- NeurIPS (T1)Offline constrained reinforcement learning under partial data coverage
202520 papers
- ICML (T1)A computationally efficient algorithm for infinite-horizon average-reward linear MDPs
- ICLR (T1)A theoretical framework for partially-observed reward states in RLHF
- Proceedings of the International Conference on Algorithmic Learning TheoryA unified theory of supervised online learnability
- TMLR (T1)An asymptotically optimal algorithm for the convex hull membership problem
- NeurIPS (T1)Conformal prediction for ensembles: Improving efficiency via score-based aggregation
- TMLR (T1)Controlling statistical, discretization, and truncation errors in learning Fourier linear operators
- Journal of Computational Chemistry, 46(1):e70005Examining the impact of local constraint violations on energy computations in DFT
- COLT (T1)Generation through the lens of learning theory
- NeurIPS (T1)Generator-mediated bandits: Thompson sampling for GenAI-powered adaptive interventions
- Bernoulli, 31(2):1206-1229High-dimensional variable selection with heterogeneous signals: A precise asymptotic perspective
- Analytical Chemistry, 97(33):18136-18143Identifying microplastics in laboratory and atmospheric aerosol mixtures via optical photothermal infrared and Raman microspectroscopy
- AISTATS (T1)Learning infinite-horizon average-reward linear mixture MDPs of bounded span
202419 papers
- JMLR (T1)A characterization of multioutput learnability
- ICML (T1)A primal-dual algorithm for offline constrained reinforcement learning with linear MDPs
- AISTATS (T1)A primal-dual-critic algorithm for offline constrained reinforcement learning
- COLT (T1)Apple tasting: Combinatorial dimensions and minimax rates
- Eric Laber, Bibhas Chakraborty, Erica E. M. Moodie, Tianxi Cai, and Mark van der Laan, editors, Handbook of Statistical Methods for Precision Medicine. Chapman & Hall/CRCBandit algorithms for precision medicine
- AISTATS (T1)Conformal contextual robust optimization
- Environmental Science & Technology, 58(49):21740-21749Enhancing confidence in microplastic spectral identification via conformal prediction
- Wong, Kaitlin J. Flynn, Rong Chai, Claire Dubin, Antonio Parraga-Leo, Camilla Wibrand, Samuel S. Minot, Boris Oskotsky, Gaia Andreoletti, Idit Kosti, Julie Bletz, Amber Nelson, Jifan Gao, Zhoujingpeng Wei, Guanhua Chen, Zheng-Zheng Tang, Pierfrancesco Novielli, Donato Romano, Ester Pantaleo, Nicola Amoroso, Alfonso Monaco, Mirco Vacca, Maria De Angelis, Roberto Bellotti, Sabina Tangaro, Zehua Wang, Jiaming Yao, Akhil Goel, Jiangyue Mao, Huiqian Wang, Yuci Zhang, Ambuj Tewari, Abigail Kuntzleman, Isaac Bigcraft, Stephen Techtmann, Daehun Bae, Eunyoung Kim, Jongbum Jeon, Soobok Joe, Kevin R. Theis, Sherrianne Ng, Yun S. Lee, Patricia Diaz-Gimeno, Phillip R. Bennett, David A. MacIntyre, Gustavo Stolovitzky, Susan V. Lynch, Jake Albrecht, Nardhy Gomez-Lopez, Roberto Romero, David K. Stevenson, Nima Aghaeepour, Adi L. Tarca, James C. Costello, and Marina Sirota. Microbiome preterm birth DREAM challenge: Crowdsourcing machine learning approaches to advance preterm birth research. Cell Reports MedicineHa, Ronald J
- Automatica, 164:111635Joint learning of linear time-invariant dynamical systems
- Proceedings of International Conference on Algorithmic Learning TheoryMulticlass online learnability under bandit feedback
- AISTATS (T1)Offline policy evaluation and optimization under confounding
- NeurIPS (T1)On the computational complexity of private high-dimensional model selection
202310 papers
- Experimental Gerontology, 173:112107A meta-analysis of RNA-seq studies to identify novel genes that regulate aging
- AISTATS (T1)An optimization-based algorithm for non-stationary kernel bandits without prior knowledge
- Journal of Medical Internet Research, 25:e43664Exploring the relationship between privacy and utility in mobile health: A simulation of federated learning, differential privacy, and external attacks
- UAI (T1)Learning in online MDPs: Is there a price for handling the communicating case?
- ICML (T1)Learning mixtures of Markov chains and MDPs
- Journal of Chemical Information and ModelingMachine learning strategies for reaction development: Toward the low-data limit
- COLT (T1)Multiclass online learning and uniform convergence
- NeurIPS (T1)On proper learnability between average- and worst-case robustness
- NeurIPS (T1)On the learnability of multilabel ranking
- ICML (T1)Thompson sampling for high-dimensional sparse linear contextual bandits
Where alumni went88 listed
Apply to MichiganFall 2027
Michigan CSE Computer Science PhD
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