Kangway Chuang
Senior Director of Machine Learning, Computational Sciences
I received my B.S. and Ph. D. from Caltech in Chemistry, and was subsequently an Arnold O. Beckman Fellow at UCSF where I worked on new deep learning approaches for molecular design. In 2021, I joined Genentech as part of the Department of Artificial Intelligence and Machine Learning in Research Biology to develop machine learning algorithms for virtual screening and molecular optimization in close collaboration with Discovery Chemistry and Peptide Therapeutics. With the creation of Genentech Computational Sciences (gCS), my group transitioned to Prescient Design/Machine Learning for Drug Discovery, where I led a team advancing next-generation machine learning algorithms to transform molecular design. In 2025, I took over the Foundation Modeling team within AI for Drug Discovery. I lead a team of scientists and engineers that develop scientific reasoning models and agents for drug discovery, with a focus on autonomous design.
Postdoctoral Mentor
I find great joy in guiding the professional and scientific development of the next generation of researchers. Genentech provides an exceptional environment that empowers postdocs to think creatively, take risks and make discoveries that push the frontiers of knowledge. My goal is to foster an inclusive culture where postdocs feel supported to make important scientific contributions as we advance impactful science together. It is a privilege to mentor these scientists in their journey to become future leaders in their fields.
Featured Publication
Accurate and Efficient Structural Ensemble Generation of Macrocyclic Peptides using Internal Coordinate Diffusion.
2024, arXiv: 2305.19800 [q-bio.BM]
RINGER: Rapid Conformer Generation for Macrocycles with Sequence-Conditioned Internal Coordinate Diffusion.
2023, arXiv: 2305.19800 [q-bio.BM]
Attention-Based Learning on Molecular Ensembles.
2020, arXiv: arXiv:2011.12820 [cs.LG]
A 15-Step Synthesis of (+)-Ryanodol.
Science. 2016, 353, 912