Yearly, the Berkeley Synthetic Intelligence Analysis (BAIR) Lab graduates among 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 unbelievable people carry 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 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 educational establishments, analysis organizations, and trade leaders to find and recruit from the most recent 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 shiny!
Thanks to our mates on the Stanford AI Lab for this concept!
E-mail: salam_azad@berkeley.edu
Web site: https://www.azadsalam.org/
Advisor(s): Ion Stoica
Analysis Blurb: My analysis curiosity lies broadly within the discipline of Machine Studying and Synthetic Intelligence. Throughout my PhD I’ve centered on Setting Era/ 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. At the moment, I’m engaged on Giant Language Mannequin (LLM) primarily based autonomous brokers.
Jobs In: Analysis Scientist, ML Engineer
E-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 functions to varied drawback domains, together with pure language processing, and pure science.
Jobs In: Analysis Scientist, Utilized Scientist, Machine Studying Engineer
E-mail: catherine22@berkeley.edu
Web site: 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 specific emphasis of mine has been how you can 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
Web site: https://chawins.github.io/
Advisor(s): David Wagner
Analysis Blurb: I’m broadly inquisitive 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 lately, I’m enthusiastic about rising safety and privateness dangers on giant language fashions.
Jobs In: Analysis scientist
E-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 finding out how kids and adults use GenAI fashions equivalent to ChatGPT/Dalle and kind psychological fashions about them. She’s an intern at Google engaged on the AI/UX group and beforehand with the Empathy Lab. She has revealed in Neurips, ICML, ICLR, Cogsci and cognition. Her thesis work created a unified digital atmosphere 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 (baby improvement and AI), AI security (specializing in kids), Person Expertise (UX) Researcher (specializing in combined strategies, youth, AI, LLMs), Schooling and AI (STEM toys)
E-mail: fangyuwu@berkeley.edu
Web site: https://fangyuwu.com/
Advisor(s): Alexandre Bayen
Analysis Blurb: Below the mentorship of Prof. Alexandre Bayen, Fangyu focuses on the appliance of optimization strategies to multi-agent robotic programs, notably within the planning and management of automated autos.
Jobs In: School, or analysis scientist in management, optimization, and robotics
E-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 bettering 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
Web site: kathyjang.com
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 purpose is to see the direct affect of my efforts by contributing to modern AI analysis and options.
Jobs In: ML analysis scientist/engineer
E-mail: nikhil_ghosh@berkeley.edu
Web site: https://nikhil-ghosh-berkeley.github.io/
Advisor(s): Bin Yu, Music Mei
Analysis Blurb: I’m inquisitive about growing a greater foundational understanding of deep studying and bettering sensible programs, utilizing each theoretical and empirical methodology. At the moment, I’m particularly inquisitive about bettering the effectivity of enormous fashions by finding out how you can correctly scale hyperparameters with mannequin dimension.
Jobs In: Analysis Scientist
E-mail: oliviawatkins@berkeley.edu
Web site: https://aliengirlliv.github.io/oliviawatkins
Advisor(s): Pieter Abbeel and Trevor Darrell
Analysis Blurb: My work entails 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
Web site: https://rmcao.internet
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 digicam processing, novel view rendering.
Jobs In: Analysis scientist, postdoc, school
E-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 giant robotic fleets performing manipulation and different complicated duties.
Jobs In: Analysis Scientist
E-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
E-mail: shishirpatil2007@gmail.com
Web site: https://shishirpatil.github.io/
Advisor(s): Joseph Gonzalez
Analysis Blurb: Gorilla LLM – Instructing LLMs to make use of instruments (https://gorilla.cs.berkeley.edu/); LLM Execution Engine: Guaranteeing reversibility, robustness, and minimizing blast-radius for LLM-Brokers included into person and enterprise workflows; POET: Reminiscence certain, and vitality environment friendly fine-tuning of LLMs on edge units equivalent to smartphones and laptops (https://poet.cs.berkeley.edu/).
Jobs In: Analysis Scientist
E-mail: spetryk@berkeley.edu
Web site: https://suziepetryk.com/
Advisor(s): Trevor Darrell, Joseph Gonzalez
Analysis Blurb: I work on bettering 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, relatively than solely in tutorial environments.
Jobs In: Utilized analysis scientist in generative AI, security, and/or accessibility
E-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 aim 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: School, or analysis scientist
E-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 observe of reliable machine studying, together with interpretability, privateness, and robustness.
Jobs In: School
