Ph.D. Dissertations – 2026: UC Berkeley
Accounting for Data Shifts in Vision Models
Devin Guillory [advisor: Trevor Darrell]
AI-Assisted Signal Extraction and Misuse Detection in Internet Systems
Julien Piet [advisor: David Wagner and Vern Paxson]
Algorithmic Pursuits of Structure: Monotone Operators, Robust Estimation, and Automated Discovery
Zihao Chen [advisor: Laurent El Ghaoui]
An Implantable Fluorescence Imager for Monitoring Response to Cancer Immunotherapy
Micah Roschelle [advisor: Ali Niknejad and Mekhail Anwar]
Analysis and Operation of Flying Capacitor Multilevel Converters: Single-Phase Applications and Fundamental Electromagnetic Interference Scaling
Francesca Giardine [advisor: Robert Pilawa-Podgurski]
Architectural Techniques for Scalable Specialization in GPUs
Hansung Kim [advisor: Sophia Shao]
Aspects of Local Time Processes with Applications
Devon Ding [advisor: Venkat Anantharam]
Automating Hardware and Software Optimization for Tensor Processing Accelerators
Charles Hong [advisor: Sophia Shao]
Building Open Source Inference Serving Systems
Simon Mo [advisor: Ion Stoica and Joseph Gonzalez]
Collaborative Language Agents
Jessy Lin [advisor: Daniel Klein and Anca Dragan]
Confidence-Aware Planning for the Safe Deployment of Deep Learning-Enabled Robot Navigation Systems
Sara Pohland [advisor: Claire Tomlin]
Decoupling Retinal Input from its Physiological Constraints
Hannah Doyle [advisor: Ren Ng]
Dynamical Modeling and Control of the Flying Capacitor Multilevel Converter in High-Density, High-Efficiency AC/DC and DC/AC Applications
Rod Bayliss [advisor: Robert Pilawa-Podgurski]
Embodied Intelligence from Autonomous Experience
Toru Lin [advisor: Jitendra Malik and Alexei (Alyosha) Efros]
Enhancing User Interface Design Tools with AI-Driven Evaluation
Peitong Duan [advisor: Björn Hartmann]
From Simulation to Reality: An End-to-End Pipeline for Reproducible Robot Learning
Kevin Zakka [advisor: Pieter Abbeel]
Generalizable and Scalable Robot Learning in the Physical World
Fangchen Liu [advisor: Pieter Abbeel]
Inferring Perturbation Effects on Gene Regulation and Disease
Ruchir Rastogi [advisor: Nir Yosef and Nilah Ioannidis]
Inferring Perturbation Effects on Gene Regulation and Disease
Ruchir Rastogi [advisor: Nir Yosef and Nilah Ioannidis]
Interpreting and Controlling Generative Models
Grace Luo [advisor: Trevor Darrell]
Learning to Solve Long-Horizon Tasks with Formal Logic and Structured Feedback
Ameesh Shah [advisor: Sanjit A. Seshia]
Limits of Efficient Algorithms in the Worst and Average Cases
Ansh Nagda [advisor: Prasad Raghavendra]
Memory-Efficient LLM Inference Algorithms
Coleman Hooper [advisor: Kurt Keutzer and Sophia Shao]
Mitigating Post-Training Effects on Generative Diversity in Language Models
Justin Wong [advisor: Sanjit A. Seshia and Joseph Gonzalez]
Modeling and Interpreting Genome Evolution at Multiple Timescales
Milind Jagota [advisor: Yun S. Song]
Moving Computation From Pretraining to Test-time
Charlie Snell [advisor: Daniel Klein]
On Small Space Computation
Hongxun Wu [advisor: Jelani Nelson and Avishay Tal]
Perceptually Grounded Modeling and Modification of Speaker Identity
Robert Netzorg [advisor: Bin Yu]
Power Dense DC-DC Converters for Electric Transportation: Design Optimization and Practical Considerations
Sahana Krishnan [advisor: Robert Pilawa-Podgurski]
Privacy and Adaptivity Considerations in Modern Data Analysis
Xin Lyu [advisor: Jelani Nelson and Avishay Tal]
Reinforcement Learning with Action Chunking Policies
Qiyang Li [advisor: Sergey Levine]
Responsible Language Model Design for Complex Populations
Eve Fleisig [advisor: Daniel Klein and Rediet Abebe]
Robustness of Neural Network Controllers
Neelay Junnarkar [advisor: Murat Arcak]
Sampling in Statistical Inference and Machine Learning
David Wu [advisor: Anant Sahai and Prasad Raghavendra]
Scalable and Accurate Models of Molecular Evolution
Sebastian Prillo [advisor: Yun S. Song and Nir Yosef]
Scaling Environments and Verifiers for Software Engineering Agents
Manish Shetty [advisor: Koushik Sen]
Security, Privacy, and Provenance for Generative AI
Jaiden Fairoze [advisor: Sanjam Garg]
So What’s the Vibe? Data-Driven Diagnosis of Model Behavior
Lisa Dunlap [advisor: Trevor Darrell and Joseph Gonzalez]
Synthesis-Enabled Reasoning: Scalable Automated Formal Verification for Hardware-Software Security
Adwait Godbole [advisor: Sanjit A. Seshia]
Synthesizing Executable Specifications to Improve AI Programming Agents
Naman Jain [advisor: Koushik Sen]
Task Decomposition with Multi-Agent Systems
Long Lian [advisor: Trevor Darrell and Adam Yala]
Toward Scalable and Self-Improving Large Language Model Agents
Xiuyu Li [advisor: Kurt Keutzer]
Towards Efficient and Scalable Robot Learning: Trajectory Pre-training, Synthetic Data, and Coding Agents
Letian Fu [advisor: Ken Goldberg]
Towards Understanding and Improving Large Language Model Reasoning
Hanlin Zhu [advisor: Stuart J. Russell and Jiantao Jiao]
Understanding Misalignment in AI Agents
Alexander Pan [advisor: Jacob Steinhardt]
User Simulation via Language Models
Josh Kang [advisor: John Wawrzynek]
Verifiable Cyber-Physical Systems: Building Engineering Models for Deterministic and Predictable Concurrent Execution
Shaokai Lin [advisor: Edward A. Lee and Sanjit A. Seshia]
Vision Models That See 10 Billion Pixels at Once
Baifeng Shi [advisor: Trevor Darrell]
Wisdom of the Crowd: The Statistical Benefits of Aggregation
Ishaq Aden-Ali [advisor: Peter Bartlett and Jelani Nelson]