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Yearly, the Berkeley Synthetic Intelligence Analysis (BAIR) Lab graduates a few of the most proficient and modern minds in synthetic intelligence and machine studying. Our Ph.D. graduates have every expanded the frontiers of AI analysis and are actually able to embark on new adventures in academia, trade, and past.<\/p>\n

These implausible people convey 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.<\/p>\n

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 most recent era of AI pioneers. Right here, you\u2019ll 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.<\/p>\n

Be a part of us in celebrating the achievements of BAIR\u2019s newest PhD graduates. Their journey is simply starting, and the longer term they’ll assist construct is brilliant!<\/p>\n

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Thanks to our pals on the Stanford AI Lab<\/a> for this concept!<\/i><\/small><\/p>\n\n

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\n $\"Abdus$ <\/a><\/p>\n
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\n E-mail:<\/strong> salam_azad@berkeley.edu<\/a>
\n Web site:<\/strong> https:\/\/www.azadsalam.org\/<\/a><\/p>\n
Advisor(s):<\/strong> Ion Stoica<\/p>\n
Analysis Blurb:<\/strong> My analysis curiosity lies broadly within the discipline of Machine Studying and Synthetic Intelligence. Throughout my PhD I’ve centered on Atmosphere 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 situations) for autonomous brokers to enhance generalization and pattern effectivity. Presently, I’m engaged on Giant Language Mannequin (LLM) primarily based autonomous brokers.
\n Jobs In:<\/strong> Analysis Scientist, ML Engineer<\/p><\/div><\/div><\/div>\n\n
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\n $\"Alicia$ <\/a><\/p>\n
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\n E-mail:<\/strong> aliciatsai@berkeley.edu<\/a>
\n Web site:<\/strong> https:\/\/www.aliciatsai.com\/<\/a><\/p>\n
Advisor(s):<\/strong> Laurent El Ghaoui<\/p>\n
Analysis Blurb:<\/strong> 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 functions to varied downside domains, together with pure language processing, and pure science.
\n Jobs In:<\/strong> Analysis Scientist, Utilized Scientist, Machine Studying Engineer<\/p><\/div><\/div><\/div>\n\n
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\n $\"Catherine$ <\/a><\/p>\n
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\n E-mail:<\/strong> catherine22@berkeley.edu<\/a>
\n Web site:<\/strong> https:\/\/cwj22.github.io<\/a><\/p>\n
Advisor(s):<\/strong> Masayoshi Tomizuka, Wei Zhan<\/p>\n
Analysis Blurb:<\/strong> 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.
\n Jobs In:<\/strong> Analysis Scientist and Robotics\/Controls Engineer<\/p><\/div><\/div><\/div>\n\n
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\n $\"Chawin$ <\/a><\/p>\n
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\n E-mail:<\/strong> chawin.sitawarin@gmail.com<\/a>
\n Web site:<\/strong> https:\/\/chawins.github.io\/<\/a><\/p>\n
Advisor(s):<\/strong> David Wagner<\/p>\n
Analysis Blurb:<\/strong> I’m broadly excited about the safety and security points of machine studying programs. 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 massive language fashions.
\n Jobs In:<\/strong> Analysis scientist<\/p><\/div><\/div><\/div>\n\n\n
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\n $\"Eliza$ <\/a><\/p>\n
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\n E-mail:<\/strong> eko@berkeley.edu<\/a>
\n Web site:<\/strong> https:\/\/www.elizakosoy.com\/<\/a><\/p>\n
Advisor(s):<\/strong> Alison Gopnik<\/p>\n
Analysis Blurb:<\/strong> Eliza Kosoy works on the intersection of kid growth and AI with Prof. Alison Gopnik. Her work consists of creating evaluative benchmarks for LLMs rooted in baby growth and finding out how youngsters and adults use GenAI fashions similar to ChatGPT\/Dalle and type psychological fashions about them. She\u2019s an intern at Google engaged on the AI\/UX staff and beforehand with the Empathy Lab. She has printed in Neurips, ICML, ICLR, Cogsci and cognition. Her thesis work created a unified digital atmosphere 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.
\n Jobs In:<\/strong> Analysis Scientist (baby growth and AI), AI security (specializing in youngsters), Person Expertise (UX) Researcher (specializing in blended strategies, youth, AI, LLMs), Schooling and AI (STEM toys)<\/p><\/div><\/div><\/div>\n\n
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\n $\"Fangyu$ <\/a><\/p>\n
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\n E-mail:<\/strong> fangyuwu@berkeley.edu<\/a>
\n Web site:<\/strong> https:\/\/fangyuwu.com\/<\/a><\/p>\n
Advisor(s):<\/strong> Alexandre Bayen<\/p>\n
Analysis Blurb:<\/strong> Underneath the mentorship of Prof. Alexandre Bayen, Fangyu focuses on the applying of optimization strategies to multi-agent robotic programs, notably within the planning and management of automated automobiles.
\n Jobs In:<\/strong> School, or analysis scientist in management, optimization, and robotics<\/p><\/div><\/div><\/div>\n\n
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\n $\"Frances$ <\/a><\/p>\n
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\n E-mail:<\/strong> frances@berkeley.edu<\/a>
\n Web site:<\/strong> https:\/\/www.francesding.com\/<\/a><\/p>\n
Advisor(s):<\/strong> Jacob Steinhardt, Moritz Hardt<\/p>\n
Analysis Blurb:<\/strong> 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.
\n Jobs In:<\/strong> Analysis scientist<\/p><\/div><\/div><\/div>\n\n\n
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\n $\"Kathy$ <\/a><\/p>\n
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\n E-mail:<\/strong> kathyjang@gmail.com<\/a>
\n Web site:<\/strong> https:\/\/kathyjang.com<\/a><\/p>\n
Advisor(s):<\/strong> Alexandre Bayen<\/p>\n
Analysis Blurb:<\/strong> My thesis work has specialised in reinforcement studying for autonomous automobiles, 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 goal is to see the direct impression of my efforts by contributing to modern AI analysis and options.
\n Jobs In:<\/strong> ML analysis scientist\/engineer<\/p><\/div><\/div><\/div>\n\n\n
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\n $\"Nikhil$ <\/a><\/p>\n
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\n E-mail:<\/strong> nikhil_ghosh@berkeley.edu<\/a>
\n Web site:<\/strong> https:\/\/nikhil-ghosh-berkeley.github.io\/<\/a><\/p>\n
Advisor(s):<\/strong> Bin Yu, Music Mei<\/p>\n
Analysis Blurb:<\/strong> I’m excited about creating a greater foundational understanding of deep studying and enhancing sensible programs, utilizing each theoretical and empirical methodology. Presently, I’m particularly excited about enhancing the effectivity of huge fashions by finding out methods to correctly scale hyperparameters with mannequin measurement.
\n Jobs In:<\/strong> Analysis Scientist<\/p><\/div><\/div><\/div>\n\n
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\n $\"Olivia$ <\/a><\/p>\n
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\n E-mail:<\/strong> oliviawatkins@berkeley.edu<\/a>
\n Web site:<\/strong> https:\/\/aliengirlliv.github.io\/oliviawatkins<\/a><\/p>\n
Advisor(s):<\/strong> Pieter Abbeel and Trevor Darrell<\/p>\n
Analysis Blurb:<\/strong> My work includes RL, BC, studying from people, and utilizing commonsense basis mannequin reasoning for agent studying. I\u2019m enthusiastic about language agent studying, supervision, alignment & robustness.
\n Jobs In:<\/strong> Analysis scientist<\/p><\/div><\/div><\/div>\n\n
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\n $\"Ruiming$ <\/a><\/p>\n
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\n E-mail:<\/strong> rcao@berkeley.edu<\/a>
\n Web site:<\/strong> https:\/\/rmcao.internet<\/a><\/p>\n
Advisor(s):<\/strong> Laura Waller<\/p>\n
Analysis Blurb:<\/strong> My analysis is on computational imaging, notably the space-time modeling for dynamic scene restoration and movement estimation. I additionally work on optical microscopy methods, optimization-based optical design, occasion digicam processing, novel view rendering.
\n Jobs In:<\/strong> Analysis scientist, postdoc, school<\/p><\/div><\/div><\/div>\n\n
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\n $\"Ryan$ <\/a><\/p>\n
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\n E-mail:<\/strong> ryanhoque@berkeley.edu<\/a>
\n Web site:<\/strong> https:\/\/ryanhoque.github.io<\/a><\/p>\n
Advisor(s):<\/strong> Ken Goldberg<\/p>\n
Analysis Blurb:<\/strong> Imitation studying and reinforcement studying algorithms that scale to massive robotic fleets performing manipulation and different complicated duties.
\n Jobs In:<\/strong> Analysis Scientist<\/p><\/div><\/div><\/div>\n\n
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\n $\"Sam$ <\/a><\/p>\n
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\n E-mail:<\/strong> sdt@berkeley.edu<\/a>
\n Web site:<\/strong> https:\/\/www.qxcv.internet\/<\/a><\/p>\n
Advisor(s):<\/strong> Stuart Russell<\/p>\n
Analysis Blurb:<\/strong> 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.
\n Jobs In:<\/strong> Analysis scientist<\/p><\/div><\/div><\/div>\n\n
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\n $\"Shishir$ <\/a><\/p>\n
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\n E-mail:<\/strong> shishirpatil2007@gmail.com<\/a>
\n Web site:<\/strong> https:\/\/shishirpatil.github.io\/<\/a><\/p>\n
Advisor(s):<\/strong> Joseph Gonzalez<\/p>\n
Analysis Blurb:<\/strong> 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 similar to smartphones and laptops (https:\/\/poet.cs.berkeley.edu\/).
\n Jobs In:<\/strong> Analysis Scientist<\/p><\/div><\/div><\/div>\n\n
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\n $\"Suzie$ <\/a><\/p>\n
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\n E-mail:<\/strong> spetryk@berkeley.edu<\/a>
\n Web site:<\/strong> https:\/\/suziepetryk.com\/<\/a><\/p>\n
Advisor(s):<\/strong> Trevor Darrell, Joseph Gonzalez<\/p>\n
Analysis Blurb:<\/strong> 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, moderately than solely in educational environments.
\n Jobs In:<\/strong> Utilized analysis scientist in generative AI, security, and\/or accessibility<\/p><\/div><\/div><\/div>\n\n
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\n $\"Xingyu$ <\/a><\/p>\n
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\n E-mail:<\/strong> xingyu@berkeley.edu<\/a>
\n Web site:<\/strong> https:\/\/xingyu-lin.github.io\/<\/a><\/p>\n
Advisor(s):<\/strong> Pieter Abbeel<\/p>\n
Analysis Blurb:<\/strong> My analysis lies in robotics, machine studying, and pc imaginative and prescient, with the first aim 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.
\n Jobs In:<\/strong> School, or analysis scientist<\/p><\/div><\/div><\/div>\n\n
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\n $\"Yaodong$ <\/a><\/p>\n
\n
\n E-mail:<\/strong> yyu@eecs.berkeley.edu<\/a>
\n Web site:<\/strong> https:\/\/yaodongyu.github.io\/<\/a><\/p>\n
Advisor(s):<\/strong> Michael I. Jordan, Yi Ma<\/p>\n
Analysis Blurb:<\/strong> My analysis pursuits are broadly in idea and apply of reliable machine studying, together with interpretability, privateness, and robustness.
\n Jobs In:<\/strong> School<\/p><\/div><\/div><\/div>\n<\/div>\n<\/div>\n<\/div>\n\n","protected":false},"excerpt":{"rendered":"
Yearly, the Berkeley Synthetic Intelligence Analysis (BAIR) Lab graduates a few of the most proficient and modern minds in synthetic intelligence and machine studying. Our Ph.D. graduates have every expanded the frontiers of AI analysis and are actually able to embark on new adventures in academia, trade, and past. These implausible people convey with them […]<\/p>\n","protected":false},"author":2,"featured_media":2645,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[55],"tags":[311,2567,310,110,1155,2568,312,193],"class_list":["post-2643","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-machine-learning","tag-artificial","tag-bair","tag-berkeley","tag-blog","tag-directory","tag-graduate","tag-intelligence","tag-research"],"_links":{"self":[{"href":"https:\/\/techtrendfeed.com\/index.php?rest_route=\/wp\/v2\/posts\/2643","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/techtrendfeed.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/techtrendfeed.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/techtrendfeed.com\/index.php?rest_route=\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/techtrendfeed.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=2643"}],"version-history":[{"count":1,"href":"https:\/\/techtrendfeed.com\/index.php?rest_route=\/wp\/v2\/posts\/2643\/revisions"}],"predecessor-version":[{"id":2644,"href":"https:\/\/techtrendfeed.com\/index.php?rest_route=\/wp\/v2\/posts\/2643\/revisions\/2644"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/techtrendfeed.com\/index.php?rest_route=\/wp\/v2\/media\/2645"}],"wp:attachment":[{"href":"https:\/\/techtrendfeed.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=2643"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/techtrendfeed.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=2643"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/techtrendfeed.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=2643"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}