2026 BAIR Graduate Showcase
| Source: BAIR Blog (Berkeley AI Research)
Tags: BAIR, Berkeley, embodied AI, robotics, LLM reasoning, Physical Intelligence
Berkeley's BAIR Lab announces its 2026 PhD graduating class, with researchers heading to faculty positions, industry labs (including Physical Intelligence), and startups across robotics, LLM reasoning, computer vision, and AI safety.
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The Berkeley Artificial Intelligence Research Lab's class of 2026 marks another cohort departing for influential positions across academia and industry. The showcase lists graduates spanning virtually every major AI subdomain — embodied intelligence and robotics, large language models and test-time scaling, computer vision, generative modeling, AI safety, and human-AI interaction.\n\nNotable placements include Baifeng Shi joining Physical Intelligence as a Member of Technical Staff, focused on generalist vision and robotic models. Charlie Snell's research explored the tradeoffs between test-time scaling and pretraining compute — bridging these remains an open challenge the field is actively working on. Eve Fleisig focused on making LLMs work reliably across diverse user populations, including calibration and bias evaluation work.\n\nThe showcase doubles as a talent signal: Berkeley continues producing researchers who land at frontier labs and shape new startups. Several graduates list themselves as actively seeking collaborators or positions, making this a useful reference for teams hiring senior AI researchers in 2026.