Friday, May 24, 2024

2024 BAIR Graduate Listing – The Berkeley Synthetic Intelligence Analysis Weblog

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Yearly, the Berkeley Synthetic Intelligence Analysis (BAIR) Lab graduates a number 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 are actually able to embark on new adventures in academia, trade, and past.

These unbelievable people convey 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 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 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 long run they’ll assist construct is vivid!

Thanks to our buddies on the Stanford AI Lab for this concept!


Abdus Salam Azad


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 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. 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 features 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 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 learn 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 inquisitive about the safety and security features of machine studying methods. Most of my earlier works are within the area of adversarial machine studying, significantly adversarial examples and robustness of machine studying algorithms. Extra not too long ago, 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 improvement and AI with Prof. Alison Gopnik. Her work contains creating evaluative benchmarks for LLMs rooted in youngster improvement and finding out how kids and adults use GenAI fashions corresponding to ChatGPT/Dalle and kind psychological fashions about them. She’s an intern at Google engaged on the AI/UX crew 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 (youngster improvement and AI), AI security (specializing in kids), Consumer Expertise (UX) Researcher (specializing in blended strategies, youth, AI, LLMs), Schooling and AI (STEM toys)


Fangyu Wu


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

Advisor(s): Alexandre Bayen

Analysis Blurb: Underneath the mentorship of Prof. Alexandre Bayen, Fangyu focuses on the appliance of optimization strategies to multi-agent robotic methods, significantly 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 completely 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 intention is to see the direct impression of my efforts by contributing to progressive 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 inquisitive about growing a greater foundational understanding of deep studying and bettering sensible methods, utilizing each theoretical and empirical methodology. At the moment, I’m particularly inquisitive about bettering the effectivity of huge fashions by finding out learn how to correctly scale hyperparameters with mannequin measurement.
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 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


Ruiming Cao


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

Advisor(s): Laura Waller

Analysis Blurb: My analysis is on computational imaging, significantly 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, school


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 advanced duties.
Jobs In: Analysis Scientist


Sam Toyer


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

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


Shishir G. Patil


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 person and enterprise workflows; POET: Reminiscence sure, and power environment friendly fine-tuning of LLMs on edge gadgets corresponding to 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 decreasing 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


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




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