Yearly, the Berkeley Synthetic Intelligence Analysis (BAIR) Lab graduates a few of the most gifted 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 carry with them a wealth of information, 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 pc imaginative and prescient, safety, and rather 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 tutorial 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 speak to 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 part of us in celebrating the achievements of BAIR’s newest PhD graduates. Their journey is simply starting, and the longer term they may assist construct is vibrant!
Thanks to our mates on the Stanford AI Lab for this concept!
E mail: salam_azad@berkeley.edu
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Advisor(s): Ion Stoica
Analysis Blurb: My analysis curiosity lies broadly within the area of Machine Studying and Synthetic Intelligence. Throughout my PhD I’ve targeted on Setting Era/ Curriculum Studying strategies for coaching Autonomous Brokers with Reinforcement Studying. Particularly, I work on strategies that algorithmically generates numerous coaching environments (i.e., studying situations) for autonomous brokers to enhance generalization and pattern effectivity. Presently, I’m engaged on Giant Language Mannequin (LLM) primarily based autonomous brokers.
Jobs In: Analysis Scientist, ML Engineer
E mail: aliciatsai@berkeley.edu
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Advisor(s): Laurent El Ghaoui
Analysis Blurb: My analysis delves into the theoretical facets of deep implicit fashions, starting with a unified “state-space” illustration that simplifies notation. Moreover, my work explores numerous 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 numerous drawback domains, together with pure language processing, and pure science.
Jobs In: Analysis Scientist, Utilized Scientist, Machine Studying Engineer
E mail: catherine22@berkeley.edu
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Advisor(s): Masayoshi Tomizuka, Wei Zhan
Analysis Blurb: My analysis focuses on machine studying and management algorithms for the difficult job 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 techniques for robotics and autonomous techniques. 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
E mail: chawin.sitawarin@gmail.com
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Advisor(s): David Wagner
Analysis Blurb: I’m broadly thinking about the safety and security facets of machine studying techniques. Most of my earlier works are within the area of adversarial machine studying, notably adversarial examples and robustness of machine studying algorithms. Extra just lately, I’m enthusiastic about rising safety and privateness dangers on giant language fashions.
Jobs In: Analysis scientist
E mail: eko@berkeley.edu
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Advisor(s): Alison Gopnik
Analysis Blurb: Eliza Kosoy works on the intersection of kid improvement and AI with Prof. Alison Gopnik. Her work consists of creating evaluative benchmarks for LLMs rooted in youngster improvement and finding out how kids and adults use GenAI fashions similar to ChatGPT/Dalle and type psychological fashions about them. She’s an intern at Google engaged on the AI/UX crew and beforehand with the Empathy Lab. She has printed in Neurips, ICML, ICLR, Cogsci and cognition. Her thesis work created a unified digital surroundings for testing kids 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 (youngster improvement and AI), AI security (specializing in kids), Person Expertise (UX) Researcher (specializing in blended strategies, youth, AI, LLMs), Training and AI (STEM toys)
E mail: fangyuwu@berkeley.edu
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Advisor(s): Alexandre Bayen
Analysis Blurb: Beneath the mentorship of Prof. Alexandre Bayen, Fangyu focuses on the applying of optimization strategies to multi-agent robotic techniques, notably within the planning and management of automated autos.
Jobs In: College, or analysis scientist in management, optimization, and robotics
E mail: frances@berkeley.edu
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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 totally different protein fashions be taught. 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
E mail: kathyjang@gmail.com
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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 ideas to broader challenges throughout domains like pure language processing. With my background, my goal is to see the direct impression of my efforts by contributing to progressive AI analysis and options.
Jobs In: ML analysis scientist/engineer
E mail: nikhil_ghosh@berkeley.edu
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Advisor(s): Bin Yu, Track Mei
Analysis Blurb: I’m thinking about growing a greater foundational understanding of deep studying and enhancing sensible techniques, utilizing each theoretical and empirical methodology. Presently, I’m particularly thinking about enhancing the effectivity of huge fashions by finding out methods to correctly scale hyperparameters with mannequin measurement.
Jobs In: Analysis Scientist
E mail: oliviawatkins@berkeley.edu
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Advisor(s): Pieter Abbeel and Trevor Darrell
Analysis Blurb: My work includes RL, BC, studying from people, and utilizing common sense basis mannequin reasoning for agent studying. I’m enthusiastic about language agent studying, supervision, alignment & robustness.
Jobs In: Analysis scientist
E mail: rcao@berkeley.edu
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Advisor(s): Laura Waller
Analysis Blurb: My analysis is on computational imaging, notably the space-time modeling for dynamic scene restoration and movement estimation. I additionally work on optical microscopy strategies, optimization-based optical design, occasion digital camera processing, novel view rendering.
Jobs In: Analysis scientist, postdoc, college
E mail: sdt@berkeley.edu
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Advisor(s): Stuart Russell
Analysis Blurb: My analysis focuses on making language fashions safe, strong and secure. I even have expertise in imaginative and prescient, planning, imitation studying, reinforcement studying, and reward studying.
Jobs In: Analysis scientist
E mail: shishirpatil2007@gmail.com
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Advisor(s): Joseph Gonzalez
Analysis Blurb: Gorilla LLM – Educating LLMs to make use of instruments ( LLM Execution Engine: Guaranteeing reversibility, robustness, and minimizing blast-radius for LLM-Brokers integrated into consumer and enterprise workflows; POET: Reminiscence sure, and vitality environment friendly fine-tuning of LLMs on edge gadgets similar to smartphones and laptops (
Jobs In: Analysis Scientist
E mail: spetryk@berkeley.edu
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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 situations, somewhat than solely in educational environments.
Jobs In: Utilized analysis scientist in generative AI, security, and/or accessibility
E mail: xingyu@berkeley.edu
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Advisor(s): Pieter Abbeel
Analysis Blurb: My analysis lies in robotics, machine studying, and pc imaginative and prescient, with the first purpose of studying generalizable robotic expertise from two angles: (1) Studying structured world fashions with spatial and temporal abstractions. (2) Pre-training visible illustration and expertise to allow information switch from Web-scale imaginative and prescient datasets and simulators.
Jobs In: College, or analysis scientist
