Bo Zhao (@BoZhao__) profile picture

Postdoc at Harvard

Cambridge, MA
Joined October 2022
Photo by Bo Zhao (@BoZhao__)Photo by Bo Zhao (@BoZhao__)Photo by Bo Zhao (@BoZhao__)Photo by Bo Zhao (@BoZhao__)Photo by Bo Zhao (@BoZhao__)Photo by Bo Zhao (@BoZhao__)Photo by Bo Zhao (@BoZhao__)Photo by Bo Zhao (@BoZhao__)Photo by Bo Zhao (@BoZhao__)Photo by Bo Zhao (@BoZhao__)
There’s lots of symmetry in neural networks! 🔍 We survey where they appear, how they shape loss landscapes and learning dynamics, and applications in optimization, weight space learning, and much more. ➡️ Symmetry in Neural Network Parameter Spaces arxiv.org/abs/2506.13018
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⏳ Less than one week until our CFP closes! Working on model populations, weights, gradients, representations, or training trajectories? We'd love to see your work at our #NeurIPS2026 workshop on neural network artifacts. 🗓 Deadline: Sept 1 AoE artifactsasdata.org/
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📣 CFP: Neural Network Artifacts Are Data Too! We welcome extended abstracts & full papers on model populations, weights, gradients, representations & training dynamics for our #NeurIPS2026 workshop. Join us in Paris! 🗓 Sept 1 AoE 🔗 artifactsasdata.org/
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How do LLMs organize emotion concepts? Excited to share our #ICML2026 paper: we uncover emergent “emotion trees” in LLMs, inspired by emotion wheels from psychology. 📄Emergence of Hierarchical Emotion Organization in Large Language Models 🔗arxiv.org/abs/2507.10599
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Excited to contribute a small piece to the growing work on affective cognition and internal representations in LLMs! We also hope our label-free tree-construction algorithm will find more applications beyond emotion.
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I defended my PhD thesis "Symmetry in Neural Networks"! Grateful to my advisor @yuqirose and committee Mikhail Belkin, Sicun Gao, and Barna Saha, as well as mentors, colleagues, and friends. Next stop: postdoc with @mweber_PU at Harvard's Geometric Machine Learning Group!
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Bo Zhao retweeted
🎉 Our paper on interpretable model mergeability prediction has been accepted to ICML 2026! Excited to share this joint work on understanding when model merging succeeds, with amazing co-authors @bozhao, @yuqirose, and @EmanueleRodola 🙏 Happy to chat in Seoul! 🇰🇷
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📢Excited to announce the Workshop on Weight-Space Symmetries @icmlconf! We welcome 4-page submissions analysing symmetries, their effects on training and model structure, and practical methods to utilize them. Submission Deadline: April 24 (23:59 AoE) #ICML2026
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Bo Zhao retweeted
🔵🔴 Join us this Saturday at @NeurIPSConf 2025 for the @unireps Workshop: Unifying Representations in Neural Models! We’re excited to host an exceptional lineup of speakers and panelists: @yuqirose @elmelis @evadyer @randall_balestr @KriegeskorteLab @abeirami @sarahookr @meenakshik93
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In weight space learning, parameters themselves become data. Parameter-space symmetry informs meta-networks that learn over these parameters while preserving equivariance to symmetry transformations.
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