BAIR 2024 Graduate Directory – PhD Profiles & Contact Info
Sources: http://bair.berkeley.edu/blog/2024/03/11/grads-2024, http://bair.berkeley.edu/blog/2024/03/11/grads-2024/, BAIR Blog
Overview
The BAIR Graduate Directory is a curated collection of BAIR Lab PhD graduates who have expanded AI research frontiers and are pursuing opportunities in academia, industry, and beyond. The directory emphasizes that these graduates bring deep expertise across AI subfields and are ready to engage in new collaborations. It highlights that their profiles include detailed research interests, advisor information, and contact details, making it easier for academic institutions, research organizations, and industry partners to discover and recruit the newest generation of AI pioneers. The page notes that BAIR’s initiative mirrors ideas from the Stanford AI Lab, and it invites collaborations and engagements across sectors. Examples of the kinds of profiles you’ll encounter span deep learning, robotics, natural language processing, computer vision, security, and related areas, reflecting the breadth of BAIR’s doctoral work. Examples of profiles in this directory include:
- Abdus Salam Azad — Email: [email protected]; Website: https://www.azadsalam.org/; Advisor(s): Ion Stoica; Research blurb: Environment Generation / Curriculum Learning for training Autonomous Agents with Reinforcement Learning; currently pursuing LLM-based autonomous agents. Jobs Interested In: Research Scientist, ML Engineer. See the directory page for full details.
- Alicia Tsai — Website: https://www.aliciatsai.com/; Advisor(s): Laurent El Ghaoui; Research blurb: Theoretical work on deep implicit models with a unified state-space view, training challenges in deep learning, and applications to NLP and natural science. Jobs Interested In: Research Scientist, Applied Scientist, Machine Learning Engineer.
- Catherine Weaver — Website: https://cwj22.github.io; Advisor(s): Masayoshi Tomizuka, Wei Zhan; Research blurb: ML and control for autonomous racing in Gran Turismo Sport, leveraging offline datasets to improve sample efficiency. Jobs Interested In: Research Scientist, Robotics/Controls Engineer.
- Eliza Kosoy — Website: https://www.elizakosoy.com/; Advisor(s): Alison Gopnik; Research blurb: Child development intersections with AI, benchmarks for LLMs rooted in child development, AI safety and UX considerations; currently interning at Google on AI/UX. Jobs Interested In: Research Scientist, UX Researcher, Education and AI, etc. The directory serves as a bridge to connect potential collaborators and recruiters with BAIR PhD graduates by providing direct contact channels and links to personal sites or professional profiles. The page can be a resource for institutions seeking expertise across AI research areas and for industry partners exploring candidates for research roles, engineering positions, or thought leadership.
Key features
- Profiles for each graduate include research interests, advisor(s), and contact information (email and website).
- Each profile often includes a research blurb summarizing the core focus of the PhD work.
- Contact information provides direct channels for outreach and collaboration.
- The directory spans a broad range of AI domains (e.g., deep learning, robotics, NLP, computer vision, security) reflecting BAIR’s research breadth.
- The page is a recruitment-friendly resource intended to ease connections with the newest generation of AI researchers.
- The directory is presented as an ongoing annual showcase, aligning with BAIR’s tradition of highlighting graduates.
- The inspiration from the Stanford AI Lab is acknowledged, emphasizing cross-institutional ideas for sharing graduate profiles.
Common use cases
- Academic collaboration: identify potential collaborators on grant proposals, papers, or student-supervised projects.
- Recruitment: industry and research labs seeking PhD-level talent for roles such as research scientist, ML engineer, or robotics engineer.
- Networking: connect with graduates for speaking engagements, collaboration discussions, or mentoring opportunities for current students.
- Talent intelligence: survey the career trajectories and research interests of BAIR graduates to inform hiring strategies and program development.
Setup & installation
Not applicable: No installation required for the BAIR Graduate Directory.Quick start
# Quick start: fetch and preview the directory page
curl -sL https://bair.berkeley.edu/blog/2024/03/11/grads-2024/ | head -n 20Pros and cons
- Pros:
- Centralized, public showcase of BAIR PhD graduates and their research areas.
- Direct access to emails and personal websites for outreach.
- Wide coverage across AI subfields and applications.
- Simple mechanism for institutions and industry to discover talent.
- Cons:
- Content is limited to BAIR graduates and may not represent all relevant AI PhD talents.
- Profiles may vary in depth and completeness depending on individual updates.
- Not a structured database; discovery relies on manual browsing of the page.
Alternatives (brief comparisons)
- Stanford AI Lab graduate directories or similar university lab directories exist as inspiration, highlighting that such public profiles facilitate cross-institution collaborations. The BAIR page explicitly thanks Stanford AI Lab for the idea.
- Other university or lab pages may provide similar profiles but with different depth, formatting, or data fields.
Pricing or License
Not specified.
References
- https://bair.berkeley.edu/blog/2024/03/11/grads-2024/
- https://www.azadsalam.org/
- https://www.aliciatsai.com/
- https://cwj22.github.io
- https://chawins.github.io/
- http://cs.berkeley.edu/~shah/
- https://www.elizakosoy.com/
- https://fangyuwu.com/
- https://www.francesding.com/
- https://people.eecs.berkeley.edu/~jianlanluo/
- https://kathyjang.com
- https://people.eecs.berkeley.edu/~kevinlin/
- https://nikhil-ghosh-berkeley.github.io/
- https://aliengirlliv.github.io/oliviawatkins
- https://rmcao.net
- https://ryanhoque.github.io/
- https://www.qxcv.net/
- https://shishirpatil.github.io/
- https://suziepetryk.com/
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