The Berkeley Artificial Intelligence Research (BAIR) Lab is celebrating its class of 2026 — a group of PhD graduates whose work spans the full breadth of modern AI. From robotics and embodied intelligence to large language models, computer vision, generative modeling, AI safety, and AI for science and healthcare, this cohort has pushed the frontiers of the field.
The graduates are headed everywhere ideas travel: to faculty and postdoctoral positions, to industry research labs, and to startups of their own founding. Several are still exploring what comes next and are actively seeking opportunities.
Notable Placements
Sergey Levine's students are heading to top research roles. One graduate is joining Physical Intelligence as a Member of Technical Staff, working on large-scale robot learning including imitation learning, reinforcement learning, and generative modeling. Another is heading to Google DeepMind as a Research Scientist, focusing on AI safety and reinforcement learning in multi-agent settings.
Trevor Darrell's advisees are pursuing diverse paths. One is becoming a Member of Technical Staff at Physical Intelligence, building generalist vision and robotic models. Another is joining the research scientist ranks in industry, focusing on interpreting and controlling generative models.
Dan Klein's graduates are tackling fundamental questions about LLM scaling. One is exploring how test-time scaling and pretraining can be bridged — turning inferences drawn at test-time into learned representations that models can hold onto across interactions. Another is joining Princeton CITP as a postdoctoral fellow, designing language models to work reliably and fairly for diverse user populations.
Stuart Russell and Jiantao Jiao are sending a graduate to OpenAI as a Member of Technical Staff, focused on understanding and improving LLM reasoning capabilities.
Jitendra Malik and Yi Ma have a graduate joining Amazon as a Research Scientist while also taking a faculty position at the University of Chicago, working on dexterous manipulation and robot learning.
Academic and Research Trajectories
Bjoern Hartmann's graduate is becoming an Assistant Professor of Computer Science at UCLA, studying effective human-AI co-design and language-oriented technologies.
Gopala Anumanchipalli's advisees are taking varied paths. One co-led the development of multimodal AI tools for translating brain activity into text and speech — work published in Nature (2023) and Nature Neuroscience (2025) — and is now tech lead for voice modeling at Roblox. Another is looking for AI talent to join their startup.
John Canny's graduate is joining Mistral AI as an AI Scientist, focusing on human user simulation and conversational collaborative AI agents.
Jennifer Listgarten and Yun Song's graduate is becoming a Research Scientist, working on machine learning for biology with an emphasis on generative modeling for proteins.
David Bamman's advisees are pursuing teaching faculty and research scientist roles, working on NLP and multimodal machine learning, LLM evaluation, and understanding whose voices get represented in AI systems.
Robotics and Embodied AI
Negar Mehr's graduate is joining Toyota Woven's end-to-end autonomous driving team, working on autonomous robots that safely coordinate with humans in shared environments.
Masayoshi Tomizuka's advisees are heading to roles including Research Scientist at Luma AI and Applied Scientist positions, working on multimodal foundation models, world models, and safe autonomous systems.
Alexandre Bayen's graduate is becoming Chief Scientist and Co-founder at Yumi Health, focusing on RL for autonomous driving. Another is becoming an Energy Fellow at Stanford, working on physics-informed learning and control for mixed-autonomy systems.
Industry Research
Kurt Keutzer's graduate is joining xAI as a Member of Technical Staff, working on scalable and self-improving LLM agents for complex, long-horizon coding tasks.
Ion Stoica's graduate is pursuing research scientist roles in LLM post-training, data curation, RLHF, and agentic workflows.
Aditi Krishnapriyan's graduate is becoming Lead Research Scientist at Baseten, working on reinforcement learning, world models, and AI for biology and chemistry.
Kannan Ramchandran and Thomas Courtade's graduate is joining Hudson River Trading's AI Labs, working on online learning, interpretability, and scalable attribution methods.
Claire Tomlin's graduate is pursuing research scientist roles in safety assurances for AI-enabled autonomous systems.
A Community Shaped
Beyond individual achievements, this cohort has published influential research, built systems with real-world impact, mentored their peers, and shaped the BAIR community. Their work reflects the breadth and depth of Berkeley's AI research ecosystem.
As the BAIR community celebrates these graduates, the message is clear: they've pushed the frontiers of AI, and the field is better for it. The class of 2026 is heading out to shape the future of artificial intelligence — and we can't wait to see what they do next.