Sanjit A. Seshia
Professor
Develops formal methods for verified AI and cyber-physical systems, including the Scenic scenario language.
Sanjit A. Seshia's lab at UC Berkeley works on compilers & programming languages. 22 papers since 2023, 7 at top venues, mostly NeurIPS and AAAI. 11 PhD students and 1 master's student. 57 alumni, most often to Amazon and Google. Applications close .
At a glance
- papers, 2023–2026
- 6/ year
- at T1 venues
- 32%
- PhD students
- 11
- MS students
- 1
- alumni listed
- 57
Papers by yearfrom the lab homepage, 2023–2026
- 0 papers2026 · T1 0 · collecting
- 0 papers2025 · T1 0
- 12 papers2024 · T1 6
- 10 papers2023 · T1 1
T1 venuesOtherVenues: NeurIPS, AAAI, ASPLOS, CCS, Machine Learning
Research focuspaper titles that use each topic's words
- Compilers & programming languages3 papers
- verified2 papers
- cyber-physical systems1 paper
- cyber-physical1 paper
- formal methods0 papers
Paper list
From the lab homepage.
202412 papers
- RV40–58, Springer, October 2024
- AAAI (T1)An Eager Satisfiability Modulo Theories Solver for Algebraic Datatypes
- NeurologyAugmented Reality-based Physical Assessment (ARPA) for Remote Assessment of Patients with Prior Stroke: A Feasibility Study
- NeurIPS (T1)Compositional Automata Embeddings for Goal-Conditioned Reinforcement Learning
- ASPLOS (T1)Lifting Micro-Update Models from RTL for Formal Security Analysis
- Sun Oct 20, 23:17:03Patrick Riley (opens in a new tab)
- COLMScenicNL: Generating Probabilistic Scenario Programs from Natural Language
- CCS (T1)SemPat: From Hyperproperties to Attack Patterns for Scalable Analysis of Microarchitectural Security
- NFMSMT-Based Dynamic Multi-Robot Task Allocation
- NeurIPS (T1)Synthetic Programming Elicitation for Text-to-Code in Very Low-Resource Programming and Formal Languages
- ECOOPTenspiler: A Verified Lifting-Based Compiler for Tensor Operations
- NeurIPS (T1)Verified Code Transpilation with LLMs
202310 papers
- CAV3D Environment Modeling for Falsification and Beyond with Scenic 3.0
- ECOOPBuilding Code Transpilers for Domain-Specific Languages Using Program Synthesis
- RVCompositional Simulation-Based Analysis of AI-Based Autonomous Systems for Markovian Specifications
- RVLearning Monitor Ensembles for Operational Design Domains
- PACMPL (T1)Message Chains for Distributed System Verification
- FMCADModelling and Verification of Security-Oriented Resource Partitioning Schemes
- Machine LearningScenic: A Language for Scenario Specification and Data Generation
- Proceedings of Cyber-Physical Systems and Internet of Things WeekSymbiotic CPS Design-Space Exploration through Iterated Optimization
- TECSTowards Building Verifiable CPS using Lingua Franca
- IEEE Transactions on Computer Aided Design of Integrated Circuits and SystemsUlgen: A Runtime Assurance Framework for Programming Safe Cyber-Physical Systems
Where alumni went57 listed, 52% to industry
Industry 16Academia 15
Most often to
- Amazon
- Waymo
Also to
- Chalmers University
- NYU
- Radboud University
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.
Similar labsnearest by research summary
- USMIT
David Alexander Bruns-Smith
- Reinforcement learning
- CNTsinghua
Chao Shang
- Reinforcement learning
- GBCambridge
Zoubin Ghahramani
- Probabilistic & causal inference
- USNYU
Rumi Chunara
- Trustworthy & safe ML
- USUT Austin
Risto Miikkulainen
- Computational neuroscience & cognition
- GBUCL
Peter Orbanz
- Learning theory & optimization
Your notes
Save this lab to keep notes.
Data
Checked against the lab homepage.
- Collected
- Verified
- Papers
- The lab homepage
- Members
- Lab homepage
- Alumni
- Lab homepage
Tiers are venue classifications, not lab rankings.
UC Berkeleycloses