Amy Wang

I’m a computational researcher specializing in sequence-based protein modeling and representation learning, with a decade of hands-on wet-lab experience. My work focuses on dataset design and predictive modeling for affinity and developability, integrating domain knowledge from physics-based approaches.

As a Senior ML Scientist at Prescient Design (Genentech), I lead research directions that deliver frameworks deployed across 10+ drug discovery programs, working in close partnership with experimental teams.

I earned my PhD in 2023 at Stanford, studying force-sensitive cell adhesion proteins with Alex Dunn and Bill Weis. I collaborated on GNN models for protein prediction with Microsoft Research's BioML Team (Kevin Yang, Ava Amini, Alex Lu) and on MD simulation analysis with Ron Dror's group. As an undergraduate at MIT, I studied protein-polymer systems for drug delivery in the Olsen, Langer, and Anderson labs.

CV | Google Scholar | Twitter
amywangsci [at] gmail.com

Publications

Lab-in-the-loop therapeutic antibody design with deep learning
N.C. Frey, I. Hötzel, S.D. Stanton, R. Kelly, R.G. Alberstein, ..., A. Wang, ..., A.Regev, Y. Wu, K. Cho, R. Bonneau, V. Gligorijević

bioRxiv 2025

Concept Bottleneck Language Models For Protein Design
A.A. Ismail, T. Oikarinen, A. Wang, J. Adebayo, S.D. Stanton, H.C. Bravo, K. Cho, N.C. Frey

International Conference on Learning Representations (ICLR) 2025

Fine-tuning discrete diffusion models via reward optimization with applications to dna and protein design
C. Wang, M. Uehara, Y. He, A. Wang, A. Lal, T. Jaakola, S. Levine, A. Regev, H. Wang, T. Biancalani

International Conference on Learning Representations (ICLR) 2025

Multi-level force-dependent allosteric enhancement of αE-catenin binding to F-actin by vinculin
N.A. Bax*, A. Wang*, D.L. Huang, S. Pokutta, A.R. Dunn, W.I. Weis

Journal of Molecular Biology 2023 | PDF

	Mechanism of the cadherin-catenin F-actin catch bond interaction A. Wang, A.R. Dunn, W.I. Weis eLife 2022 \| PDF
	A retrievable implant for the long-term encapsulation and survival of therapeutic xenogeneic cells S. Bose, L.R. Volpatti, D. Thiono, V. Yesilyurt, C. McGladrigan, Y. Tang, A. Facklam, A. Wang, S. Jhunjhunwala, O. Veiseh, J. Hollister-Lock, C. Bhattacharya, G.C. Weir, D.L. Greiner, R. Langer, D.G. Anderson Nature Biomedical Engineering 2020 \| PDF
	Structure and mechanism of the cation–chloride cotransporter NKCC1 T.A. Chew, B.J. Orlando, J. Zhang, N.R. Latorraca, A. Wang, S.A. Hollingsworth, D.H. Chen, R.O. Dror, M. Liao, L. Feng Nature* 2019 \| PDF
	Predicting protein–polymer block copolymer self-assembly from protein properties A. Huang, J.M. Paloni, A. Wang, A.C. Obermeyer, H.V. Sureka, H. Yao, B.D. Olsen Biomacromolecules 2019 \| PDF
	Design of insulin-loaded nanoparticles enabled by multistep control of nanoprecipitation and zinc chelation S. Chopra, N. Bertrand, J. Lim, A. Wang, O. Farokhzad, R. Karnik ACS Applied Materials & Interfaces 2017 \| PDF Patent Filed October 7, 2015.

Workshops

A guided design framework for the optimization of therapeutic-like antibodies
A. Wang, Z. Sang, S.D. Stanton, J.L. Hofmann, [...], N.C. Frey, A.M. Watkins, Franziska SeegerF. Seeger

Generative and Experimental Perspectives for Biomolecular Design, ICLR 2025 | PDF

SurfProp: A surface-based property prediction framework for antibody developability and screening
P. Rao, H. Isaacson, J.L. Hofmann, D. Davidson, A. Wang, A.M. Watkins, R. Bonneau, S. Izadi, J.H. Lee, N.C. Frey, F. Seeger

GenBio Workshop, ICLR 2025 | PDF

The Effects of Structural Conditioning on Antibody Inverse Folding
Z. Ma, D. Davidson, A. Wang, N. Frey, F. Seeger

Women in ML Workshop, NeurIPS 2023

Learning from physics-based features improves protein property prediction
A. Wang, A.X. Lu, A.P. Amini, K.K. Yang

Machine Learning in Structural Biology Workshop, NeurIPS 2022 | PDF | Poster

Awards and Affiliations

University Nominee for the 2023 Schmidt Science Fellows Program
Valuation of Public Companies in the Life Sciences Pitch Competition (INDE209) - First Place (2020)
NSF Graduate Research Fellowship (2018-2023)
Stanford ChEM-H Chemistry/Biology Interface Predoctoral Training Program (2018-2023)
Stanford Graduate Fellowship (2018-2023)
MIT Tau Beta Pi (2017)
MIT Chemical Engineering Departmental BP Academic Achievement Award (2016)

Webpage design courtesy of Jon Barron.

	Mechanism of the cadherin-catenin F-actin catch bond interaction A. Wang, A.R. Dunn, W.I. Weis eLife 2022 \| PDF
	A retrievable implant for the long-term encapsulation and survival of therapeutic xenogeneic cells S. Bose, L.R. Volpatti, D. Thiono, V. Yesilyurt, C. McGladrigan, Y. Tang, A. Facklam, A. Wang, S. Jhunjhunwala, O. Veiseh, J. Hollister-Lock, C. Bhattacharya, G.C. Weir, D.L. Greiner, R. Langer, D.G. Anderson Nature Biomedical Engineering 2020 \| PDF
	Structure and mechanism of the cation–chloride cotransporter NKCC1 T.A. Chew, B.J. Orlando, J. Zhang, N.R. Latorraca, A. Wang, S.A. Hollingsworth, D.H. Chen, R.O. Dror, M. Liao, L. Feng Nature* 2019 \| PDF
	Predicting protein–polymer block copolymer self-assembly from protein properties A. Huang, J.M. Paloni, A. Wang, A.C. Obermeyer, H.V. Sureka, H. Yao, B.D. Olsen Biomacromolecules 2019 \| PDF
	Design of insulin-loaded nanoparticles enabled by multistep control of nanoprecipitation and zinc chelation S. Chopra, N. Bertrand, J. Lim, A. Wang, O. Farokhzad, R. Karnik ACS Applied Materials & Interfaces 2017 \| PDF Patent Filed October 7, 2015.