Shangyin Tan
I am a fifth-year Ph.D. student at UC Berkeley EECS working with Professor Koushik Sen and Matei Zaharia in the Sky Lab. My research interests center around agents, compound AI system, and a little bit of programming languages.
Previously
I was a student researcher at Google DeepMind (legacy Google Brain), collaborating with Dan Zheng, Ningning Xie, and Gordon Plotkin. I did my undergrad at Purdue University, working with Guannan Wei and Tiark Rompf on building symbolic execution compilers with staging.
Outside of my hacking job, I am an hiker/backpacker, trail runner, and alpine skier.
I am open to collaborating on a few projects. Feel free to drop me an email, especially if you are an undergrad! Find me at \(\text{shangyin}\ at\ \text{berkeley.edu}\), Twitter, or Github. Here is my CV (last updated Aug 21, 2026).
Preprints (Work in Progress)
- Recovery-Bench: Evaluating Agentic Recovery from Mistakes
Shangyin Tan, Kevin Lin, Koushik Sen, Matei Zaharia
NeurIPS 2025 Workshop on Evaluating the Evolving LLM Lifecycle - Choix: Choice-based Learning in Jax
Shangyin Tan*, Dan Zheng*, Gordon Plotkin, Ningning Xie
Workshop on ML for Systems at NeurIPS 2023
[paper] [code] - DSPy Assertions: Computational Constraints for Self-Refining Language Model Pipelines
Arnav Singhvi*, Manish Shetty*, Shangyin Tan*, Christopher Potts, Koushik Sen, Matei Zaharia, Omar Khattab
[paper] [code]
Publications
- optimize_anything: Unified Text Optimization can Outperform Specialized Systems
Lakshya A Agrawal*, Donghyun Lee*, Shangyin Tan*, Wenjie Ma, Karim Elmaaroufi, Rohit Sandadi, Sanjit A. Seshia, Koushik Sen, Dan Klein, Ion Stoica, Joseph E. Gonzalez, Omar Khattab, Alexandros G. Dimakis, Matei Zaharia
The ACM Conference on AI and Agentic Systems, 2026
[paper] - Parallel Environments for Agents
Shangyin Tan*, Jialin Zhang*, Matei Zaharia
The ACM Conference on AI and Agentic Systems, 2026 - Automatically Learning Skills for Coding Agents
Shangyin Tan*, Lakshya A Agrawal*, Rohit Sandadi, Dan Klein, Koushik Sen, Alexandros G. Dimakis, Matei Zaharia
The ACM Conference on AI and Agentic Systems, 2026 - Terminal-Bench: Benchmarking Agents on Hard, Realistic Tasks in Command Line Interfaces
Mike A. Merrill, …, Shangyin Tan, …, Ludwig Schmidt
International Conference on Learning Representations (ICLR 2026)
[paper] - GEPA: Reflective Prompt Evolution Can Outperform Reinforcement Learning
Lakshya A Agrawal, Shangyin Tan, Dilara Soylu, Noah Ziems, Rishi Khare, Krista Opsahl-Ong, Arnav Singhvi, Herumb Shandilya, Michael J Ryan, Meng Jiang, Christopher Potts, Koushik Sen, Alexandros G. Dimakis, Ion Stoica, Dan Klein, Matei Zaharia, Omar Khattab
International Conference on Learning Representations (ICLR 2026)
[paper] - Programming Large Language Models with Algebraic Effect Handlers and the Selection Monad
Shangyin Tan, Guannan Wei, Koushik Sen, Matei Zaharia
The 1st Workshop on Language Models for Programming Languages (LMPL 2025)
[paper] - LangProBe: a Language Programs Benchmark
Shangyin Tan, Lakshya A Agrawal, Arnav Singhvi, Liheng Lai, Michael J Ryan, Dan Klein, Omar Khattab, Koushik Sen, Matei Zaharia
The 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP 2025)
[paper] [code] - S*: Test Time Scaling for Code Generation
Dacheng Li, Shiyi Cao, Chengkun Cao, Xiuyu Li, Shangyin Tan, Kurt Keutzer, Jiarong Xing, Joseph E. Gonzalez, Ion Stoica
The 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP 2025)
[paper] - SlimFit: Memory-Efficient Fine-Tuning of Transformer-based Models Using Training Dynamics
Arash Ardakani, Altan Haan, Shangyin Tan, Doru Thom Popovici, Alvin Cheung, Costin Iancu, Koushik Sen
The 2024 Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 2024)
[paper] - ItyFuzz: Snapshot-Based Fuzzer for Smart Contract.
Chaofan Shou, Shangyin Tan, Koushik Sen
The ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA) 2023
[paper] [code] - Compiling Parallel Symbolic Execution with Continuations.
Guannan Wei, Songlin Jia, Ruiqi Gao, Haotian Deng, Shangyin Tan, Oliver Bračevac, Tiark Rompf
The IEEE/ACM International Conference on Software Engineering (ICSE) 2023
[acm dl] [code] - INTENT: Interactive Tensor Transformation Synthesis.
Zhanhui Zhou, Man To Tang, Qiping Pan, Shangyin Tan, Xinyu Wang, Tianyi Zhang
Symposium on User Interface Software and Technology (UIST) 2022
[paper] [tool] - Towards Partially Evaluating Symbolic Interpreters for All.
Shangyin Tan, Guannan Wei, Tiark Rompf.
The ACM SIGPLAN Workshop on Partial Evaluation and Program Manipulation (PEPM 2022)
[paper] [tool] - LLSC: A Parallel Symbolic Execution Compiler for LLVM IR.
Guannan Wei, Shangyin Tan, Oliver Bračevac, Tiark Rompf.
Proceedings of The 29th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE 2021)
[acm dl] [tool] - Compiling Symbolic Execution with Staging and Algebraic Effects.
Guannan Wei, Oliver Bračevac, Shangyin Tan, Tiark Rompf.
Proceedings of the ACM on Programming Languages, Volume 4 (OOPSLA 2020).
[acm dl] [code]
Teaching - Purdue University
- CS 182 (Discrete Math), UndergradTA, Spring - Summer ‘20
- CS 252 (System Programming), UTA, Spring - Summer ‘20
- CS 381 (Algorithm), UTA, Fall ‘20
- CS 390CP (Competitive Programming), UTA, Spring ‘19 - Spring ‘20
Quote
"Simplicity is prerequisite for reliability."-- Edsger W. Dijkstra
"A composition is always more than the sum of its parts."-- Yo-Yo Ma