Zeming Lin
Also known as Ze-ming LIN
As of October 2026, Zeming Lin is a principal research scientist on the AI research team at Biohub, where his work spans PyTorch and the ESM series of protein language models. He co-authored the PyTorch paper in the NeurIPS 2019 proceedings, and an inverse-folding paper he co-wrote was named an Outstanding Paper Runner Up at ICML 2022. ESMFold, credited to Lin et al., was released in November 2022, and a Science paper by Zeming Lin et al. on atomic-level protein structure was published in March 2023. He has previously worked at EvolutionaryScale and Meta, and holds a PhD from NYU.
Timeline
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2019
Co-authoring PyTorch
He co-authors the PyTorch paper in the NeurIPS 2019 proceedings.
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2022
An ICML outstanding paper runner-up
He co-authors 'Learning inverse folding from millions of predicted structures', an Outstanding Paper Runner Up at ICML 2022.
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November 2022
The ESMFold structure predictor
ESMFold, credited to Lin et al., is released in November 2022.
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March 2023
A Science paper on protein structure
He leads the author list of a Science paper on atomic-level protein structure with a language model, published in March 2023.
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As of October 2026
Principal research scientist at Biohub
He works as a principal research scientist on Biohub's AI research team, with a PhD from NYU and work that spans PyTorch and the ESM series of protein language models. He has previously worked at EvolutionaryScale and Meta.
Sources and credits
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- PyTorch: An Imperative Style, High-Performance Deep Learning Library
- ICML 2022 Awards
- GitHub - facebookresearch/esm: Evolutionary Scale Modeling (esm): Pretrained language models for proteins · GitHub
- expert reaction to Meta’s language model for predicting protein structure | Science Media Centre
- Biomolecular Structure Prediction With ESMFold2 Webinar