2024 BAIR Graduate Listing

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Yearly, the Berkeley Synthetic Intelligence Analysis (BAIR) Lab graduates a number of the most proficient and progressive minds in synthetic intelligence and machine studying. Our Ph.D. graduates have every expanded the frontiers of AI analysis and at the moment are able to embark on new adventures in academia, trade, and past.

These improbable people deliver with them a wealth of data, recent concepts, and a drive to proceed contributing to the development of AI. Their work at BAIR, starting from deep studying, robotics, and pure language processing to laptop imaginative and prescient, safety, and way more, has contributed considerably to their fields and has had transformative impacts on society.

This web site is devoted to showcasing our colleagues, making it simpler for educational establishments, analysis organizations, and trade leaders to find and recruit from the latest technology of AI pioneers. Right here, you’ll discover detailed profiles, analysis pursuits, and make contact with info for every of our graduates. We invite you to discover the potential collaborations and alternatives these graduates current as they search to use their experience and insights in new environments.

Be a part of us in celebrating the achievements of BAIR’s newest PhD graduates. Their journey is simply starting, and the long run they may assist construct is vivid!

Thanks to our buddies on the Stanford AI Lab for this concept!


Abdus Salam Azad

Abdus Salam Azad

Electronic mail: salam_azad@berkeley.edu
Web site: https://www.azadsalam.org/

Advisor(s): Ion Stoica

Analysis Blurb: My analysis curiosity lies broadly within the subject of Machine Studying and Synthetic Intelligence. Throughout my PhD I’ve targeted on Surroundings Technology/ Curriculum Studying strategies for coaching Autonomous Brokers with Reinforcement Studying. Particularly, I work on strategies that algorithmically generates various coaching environments (i.e., studying eventualities) for autonomous brokers to enhance generalization and pattern effectivity. At present, I’m engaged on Giant Language Mannequin (LLM) based mostly autonomous brokers.
Jobs In: Analysis Scientist, ML Engineer


Alicia Tsai

Alicia Tsai

Electronic mail: aliciatsai@berkeley.edu
Web site: https://www.aliciatsai.com/

Advisor(s): Laurent El Ghaoui

Analysis Blurb: My analysis delves into the theoretical points of deep implicit fashions, starting with a unified “state-space” illustration that simplifies notation. Moreover, my work explores varied coaching challenges related to deep studying, together with issues amenable to convex and non-convex optimization. Along with theoretical exploration, my analysis extends the potential purposes to varied downside domains, together with pure language processing, and pure science.
Jobs In: Analysis Scientist, Utilized Scientist, Machine Studying Engineer


Catherine Weaver

Catherine Weaver

Electronic mail: catherine22@berkeley.edu
Web site: https://cwj22.github.io

Advisor(s): Masayoshi Tomizuka, Wei Zhan

Analysis Blurb: My analysis focuses on machine studying and management algorithms for the difficult process of autonomous racing in Gran Turismo Sport. I leverage my background in Mechanical Engineering to find how machine studying and model-based optimum management can create secure, high-performance management programs for robotics and autonomous programs. A selected emphasis of mine has been methods to leverage offline datasets (e.g. human participant’s racing trajectories) to tell higher, extra pattern environment friendly management algorithms.
Jobs In: Analysis Scientist and Robotics/Controls Engineer


Chawin Sitawarin

Chawin Sitawarin

Electronic mail: chawin.sitawarin@gmail.com
Web site: https://chawins.github.io/

Advisor(s): David Wagner

Analysis Blurb: I’m broadly involved in the safety and security points of machine studying programs. Most of my earlier works are within the area of adversarial machine studying, significantly adversarial examples and robustness of machine studying algorithms. Extra lately, I’m enthusiastic about rising safety and privateness dangers on massive language fashions.
Jobs In: Analysis scientist


Dhruv Shah

Dhruv Shah

Electronic mail: shah@cs.berkeley.edu
Web site: http://cs.berkeley.edu/~shah/

Advisor(s): Sergey Levine

Analysis Blurb: I practice massive(-ish) fashions and make robots smarter.
Jobs In: Analysis scientist, roboticist


Eliza Kosoy

Eliza Kosoy

Electronic mail: eko@berkeley.edu
Web site: https://www.elizakosoy.com/

Advisor(s): Alison Gopnik

Analysis Blurb: Eliza Kosoy works on the intersection of kid improvement and AI with Prof. Alison Gopnik. Her work contains creating evaluative benchmarks for LLMs rooted in baby improvement and learning how youngsters and adults use GenAI fashions resembling ChatGPT/Dalle and type psychological fashions about them. She’s an intern at Google engaged on the AI/UX group and beforehand with the Empathy Lab. She has printed in Neurips, ICML, ICLR, Cogsci and cognition. Her thesis work created a unified digital setting for testing youngsters and AI fashions in a single place for the needs of coaching RL fashions. She additionally has expertise constructing startups and STEM {hardware} coding toys.
Jobs In: Analysis Scientist (baby improvement and AI), AI security (specializing in youngsters), Person Expertise (UX) Researcher (specializing in blended strategies, youth, AI, LLMs), Schooling and AI (STEM toys)


Fangyu Wu

Fangyu Wu

Electronic mail: fangyuwu@berkeley.edu
Web site: https://fangyuwu.com/

Advisor(s): Alexandre Bayen

Analysis Blurb: Beneath the mentorship of Prof. Alexandre Bayen, Fangyu focuses on the appliance of optimization strategies to multi-agent robotic programs, significantly within the planning and management of automated autos.
Jobs In: College, or analysis scientist in management, optimization, and robotics


Frances Ding

Frances Ding

Electronic mail: frances@berkeley.edu
Web site: https://www.francesding.com/

Advisor(s): Jacob Steinhardt, Moritz Hardt

Analysis Blurb: My analysis focus is in machine studying for protein modeling. I work on enhancing protein property classification and protein design, in addition to understanding what completely different protein fashions study. I’ve beforehand labored on sequence fashions for DNA and RNA, and benchmarks for evaluating the interpretability and equity of ML fashions throughout domains.
Jobs In: Analysis scientist


Jianlan Luo

Jianlan Luo

Electronic mail: jianlanluo@eecs.berkeley.edu
Web site: https://folks.eecs.berkeley.edu/~jianlanluo/

Advisor(s): Sergey Levine

Analysis Blurb: My analysis pursuits are broadly in scalable algorithms and follow of machine studying, robotics, and controls; significantly their intersections.
Jobs In: College, Analysis Scientist


Kathy Jang

Kathy Jang

Electronic mail: kathyjang@gmail.com
Web site: https://kathyjang.com

Advisor(s): Alexandre Bayen

Analysis Blurb: My thesis work has specialised in reinforcement studying for autonomous autos, specializing in enhancing decision-making and effectivity in utilized settings. In future work, I am keen to use these rules to broader challenges throughout domains like pure language processing. With my background, my purpose is to see the direct influence of my efforts by contributing to progressive AI analysis and options.
Jobs In: ML analysis scientist/engineer


Kevin Lin

Kevin Lin

Electronic mail: k-lin@berkeley.edu
Web site: https://folks.eecs.berkeley.edu/~kevinlin/

Advisor(s): Dan Klein, Joseph E. Gonzalez

Analysis Blurb: My analysis focuses on understanding and enhancing how language fashions use and supply info.
Jobs In: Analysis Scientist


Nikhil Ghosh

Nikhil Ghosh

Electronic mail: nikhil_ghosh@berkeley.edu
Web site: https://nikhil-ghosh-berkeley.github.io/

Advisor(s): Bin Yu, Music Mei

Analysis Blurb: I’m involved in growing a greater foundational understanding of deep studying and enhancing sensible programs, utilizing each theoretical and empirical methodology. At present, I’m particularly involved in enhancing the effectivity of huge fashions by learning methods to correctly scale hyperparameters with mannequin dimension.
Jobs In: Analysis Scientist


Olivia Watkins

Olivia Watkins

Electronic mail: oliviawatkins@berkeley.edu
Web site: https://aliengirlliv.github.io/oliviawatkins

Advisor(s): Pieter Abbeel and Trevor Darrell

Analysis Blurb: My work includes RL, BC, studying from people, and utilizing commonsense basis mannequin reasoning for agent studying. I’m enthusiastic about language agent studying, supervision, alignment & robustness.
Jobs In: Analysis scientist


Ruiming Cao

Ruiming Cao

Electronic mail: rcao@berkeley.edu
Web site: https://rmcao.internet

Advisor(s): Laura Waller

Analysis Blurb: My analysis is on computational imaging, significantly the space-time modeling for dynamic scene restoration and movement estimation. I additionally work on optical microscopy methods, optimization-based optical design, occasion digital camera processing, novel view rendering.
Jobs In: Analysis scientist, postdoc, college


Ryan Hoque

Ryan Hoque

Electronic mail: ryanhoque@berkeley.edu
Web site: https://ryanhoque.github.io

Advisor(s): Ken Goldberg

Analysis Blurb: Imitation studying and reinforcement studying algorithms that scale to massive robotic fleets performing manipulation and different advanced duties.
Jobs In: Analysis Scientist


Sam Toyer

Sam Toyer

Electronic mail: sdt@berkeley.edu
Web site: https://www.qxcv.internet/

Advisor(s): Stuart Russell

Analysis Blurb: My analysis focuses on making language fashions safe, sturdy and secure. I even have expertise in imaginative and prescient, planning, imitation studying, reinforcement studying, and reward studying.
Jobs In: Analysis scientist


Shishir G. Patil

Shishir G. Patil

Electronic mail: shishirpatil2007@gmail.com
Web site: https://shishirpatil.github.io/

Advisor(s): Joseph Gonzalez

Analysis Blurb: Gorilla LLM – Educating LLMs to make use of instruments (https://gorilla.cs.berkeley.edu/); LLM Execution Engine: Guaranteeing reversibility, robustness, and minimizing blast-radius for LLM-Brokers integrated into consumer and enterprise workflows; POET: Reminiscence sure, and power environment friendly fine-tuning of LLMs on edge units resembling smartphones and laptops (https://poet.cs.berkeley.edu/).
Jobs In: Analysis Scientist


Suzie Petryk

Suzie Petryk

Electronic mail: spetryk@berkeley.edu
Web site: https://suziepetryk.com/

Advisor(s): Trevor Darrell, Joseph Gonzalez

Analysis Blurb: I work on enhancing the reliability and security of multimodal fashions. My focus has been on localizing and lowering hallucinations for imaginative and prescient + language fashions, together with measuring and utilizing uncertainty and mitigating bias. My pursuits lay in making use of options to those challenges in precise manufacturing eventualities, fairly than solely in tutorial environments.
Jobs In: Utilized analysis scientist in generative AI, security, and/or accessibility


Xingyu Lin

Xingyu Lin

Electronic mail: xingyu@berkeley.edu
Web site: https://xingyu-lin.github.io/

Advisor(s): Pieter Abbeel

Analysis Blurb: My analysis lies in robotics, machine studying, and laptop imaginative and prescient, with the first objective of studying generalizable robotic abilities from two angles: (1) Studying structured world fashions with spatial and temporal abstractions. (2) Pre-training visible illustration and abilities to allow information switch from Web-scale imaginative and prescient datasets and simulators.
Jobs In: College, or analysis scientist


Yaodong Yu

Yaodong Yu

Electronic mail: yyu@eecs.berkeley.edu
Web site: https://yaodongyu.github.io/

Advisor(s): Michael I. Jordan, Yi Ma

Analysis Blurb: My analysis pursuits are broadly in idea and follow of reliable machine studying, together with interpretability, privateness, and robustness.
Jobs In: College


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