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    Home»Thought Leadership in AI»2024 BAIR Graduate Listing – The Berkeley Synthetic Intelligence Analysis Weblog
    Thought Leadership in AI

    2024 BAIR Graduate Listing – The Berkeley Synthetic Intelligence Analysis Weblog

    Yasmin BhattiBy Yasmin BhattiApril 21, 2025No Comments7 Mins Read
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    2024 BAIR Graduate Listing – The Berkeley Synthetic Intelligence Analysis Weblog
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    Yearly, the Berkeley Synthetic Intelligence Analysis (BAIR) Lab graduates a few of 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 are actually able to embark on new adventures in academia, business, and past.

    These unbelievable 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 tutorial establishments, analysis organizations, and business leaders to find and recruit from the most recent era of AI pioneers. Right here, you’ll discover detailed profiles, analysis pursuits, and get in touch with 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’ll 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 subject of Machine Studying and Synthetic Intelligence. Throughout my PhD I’ve centered 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 the moment, I’m engaged on Giant Language Mannequin (LLM) based mostly autonomous brokers.
    Jobs In: Analysis Scientist, ML Engineer


    Alicia Tsai


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

    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 varied drawback domains, together with pure language processing, and pure science.
    Jobs In: Analysis Scientist, Utilized Scientist, Machine Studying Engineer


    Catherine Weaver


    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 specific emphasis of mine has been tips on how 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


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

    Advisor(s): David Wagner

    Analysis Blurb: I’m broadly fascinated with the safety and security facets 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 lately, I’m enthusiastic about rising safety and privateness dangers on massive language fashions.
    Jobs In: Analysis scientist



    Eliza Kosoy


    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 growth and AI with Prof. Alison Gopnik. Her work consists of creating evaluative benchmarks for LLMs rooted in baby growth and learning how youngsters and adults use GenAI fashions reminiscent of ChatGPT/Dalle and type psychological fashions about them. She’s an intern at Google engaged on the AI/UX workforce 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 growth and AI), AI security (specializing in youngsters), Person Expertise (UX) Researcher (specializing in combined strategies, youth, AI, LLMs), Training and AI (STEM toys)


    Fangyu Wu


    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 autos.
    Jobs In: School, or analysis scientist in management, optimization, and robotics


    Frances Ding


    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 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



    Kathy Jang


    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 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 affect of my efforts by contributing to revolutionary AI analysis and options.
    Jobs In: ML analysis scientist/engineer



    Nikhil Ghosh


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

    Advisor(s): Bin Yu, Music Mei

    Analysis Blurb: I’m fascinated with growing a greater foundational understanding of deep studying and bettering sensible methods, utilizing each theoretical and empirical methodology. At the moment, I’m particularly fascinated with bettering the effectivity of enormous fashions by learning tips on how to correctly scale hyperparameters with mannequin dimension.
    Jobs In: Analysis Scientist


    Olivia Watkins


    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


    Ruiming Cao


    E mail: rcao@berkeley.edu
    Web site: https://rmcao.web

    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, college


    Ryan Hoque


    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 complicated duties.
    Jobs In: Analysis Scientist


    Sam Toyer


    E mail: sdt@berkeley.edu
    Web site: https://www.qxcv.web/

    Advisor(s): Stuart Russell

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


    Shishir G. Patil


    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 consumer and enterprise workflows; POET: Reminiscence certain, and vitality environment friendly fine-tuning of LLMs on edge units reminiscent of smartphones and laptops (https://poet.cs.berkeley.edu/).
    Jobs In: Analysis Scientist


    Suzie Petryk


    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 eventualities, fairly than solely in educational environments.
    Jobs In: Utilized analysis scientist in generative AI, security, and/or accessibility


    Xingyu Lin


    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 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: School, or analysis scientist


    Yaodong Yu


    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 concept and follow of reliable machine studying, together with interpretability, privateness, and robustness.
    Jobs In: School


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    Yasmin Bhatti
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