Anil Aswani
Associate Professor
Designs statistical and optimization methods that use data for decision-making and human-automation systems.
Anil Aswani's lab at UC Berkeley works on learning theory & optimization and reinforcement learning. 10 papers since 2023, 1 at top venues, mostly CDC and ACC. 6 PhD students. 8 alumni. Applications close .
At a glance
- papers, 2023–2026
- 3/ year
- at T1 venues
- 10%
- PhD students
- 6
- MS students
- 0
- alumni listed
- 8
Papers by yearfrom DBLP, 2023–2026
- 0 papers2026 · T1 0 · collecting
- 4 papers2025 · T1 0
- 3 papers2024 · T1 1
- 3 papers2023 · T1 0
T1 venuesOtherVenues: CDC, ACC, TAC
Research focuspaper titles that use each topic's words
- Learning theory & optimization4 papers
- Reinforcement learning3 papers
- optimization methods0 papers
- industrial engineering0 papers
- operations0 papers
Paper list
From DBLP.
20254 papers
- CHILLearning Interactions Between Continuous Treatments and Covariates with a Semiparametric Model (opens in a new tab)
- CHASEMatching-Based Off-Policy Evaluation for Reinforcement Learning Applied to Mechanical Ventilation (opens in a new tab)
- Manuf. Serv. Oper. Manag.Optimal Policy for Inventory Management with Periodic and Controlled Resets (opens in a new tab)
- CDCTensor Completion via Integer Optimization (opens in a new tab)
20243 papers
20233 papers
Where alumni went8 listed
Apply to UC BerkeleyFall 2027
UC Berkeley EECS Computer Science PhD
- Round
- Single round
- Opens
- —
- GRE
- not required
- English
- TOEFL/IELTS (non-English-country degrees)
- Fee
- See program page
Confirmed on the program page.
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Data
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- Papers
- DBLP
- Members
- Lab homepage
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- Lab homepage
Tiers are venue classifications, not lab rankings.
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