Yearly, the Berkeley Synthetic Intelligence Analysis (BAIR) Lab graduates among the most proficient and revolutionary 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, business, and past.
These incredible people carry with them a wealth of information, contemporary 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 far 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 business leaders to find and recruit from the latest technology of AI pioneers. Right here, you’ll discover detailed profiles, analysis pursuits, and phone data 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 are going to 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 Atmosphere Technology/ Curriculum Studying strategies for coaching Autonomous Brokers with Reinforcement Studying. Particularly, I work on strategies that algorithmically generates numerous coaching environments (i.e., studying eventualities) for autonomous brokers to enhance generalization and pattern effectivity. At the moment, I’m engaged on Giant Language Mannequin (LLM) based mostly 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 features 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 downside 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: https://cwj22.github.io
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 protected, high-performance management methods for robotics and autonomous methods. A selected emphasis of mine has been the way 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
Web site: https://chawins.github.io/
Advisor(s): David Wagner
Analysis Blurb: I’m broadly excited by the safety and security features of machine studying methods. 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.
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 consists of creating evaluative benchmarks for LLMs rooted in baby improvement and learning how kids and adults use GenAI fashions akin to ChatGPT/Dalle and type psychological fashions about them. She’s an intern at Google engaged on the AI/UX staff and beforehand with the Empathy Lab. She has revealed 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 (baby 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
Web site: https://fangyuwu.com/
Advisor(s): Alexandre Bayen
Analysis Blurb: Below the mentorship of Prof. Alexandre Bayen, Fangyu focuses on the applying of optimization strategies to multi-agent robotic methods, notably within the planning and management of automated automobiles.
Jobs In: College, 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 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
Web site: https://kathyjang.com
Advisor(s): Alexandre Bayen
Analysis Blurb: 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 intention is to see the direct influence of my efforts by contributing to revolutionary 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, Tune Mei
Analysis Blurb: I’m excited by growing a greater foundational understanding of deep studying and enhancing sensible methods, utilizing each theoretical and empirical methodology. At the moment, I’m particularly excited by enhancing the effectivity of huge fashions by learning the way to 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 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
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 methods, optimization-based optical design, occasion digicam processing, novel view rendering.
Jobs In: Analysis scientist, postdoc, college
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 massive robotic fleets performing manipulation and different advanced 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 protected. 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 – 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 included into consumer and enterprise workflows; POET: Reminiscence sure, and power environment friendly fine-tuning of LLMs on edge units akin 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 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 educational 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 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.
Jobs In: College, 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 principle and apply of reliable machine studying, together with interpretability, privateness, and robustness.
Jobs In: College
