Allen Goodman
Genentech
149 5th Ave
New York, NY
10010
goodmaa3@gene.com
Allen Goodman
Genentech
149 5th Ave
New York, NY
10010
goodmaa3@gene.com
I’m a Senior Principal Machine Learning Engineer in the Frontier Research group at Genentech Research and Early Development (gRED), where I work on machine learning for drug discovery. Before Genentech, I was a member of Meta’s Fundamental AI Research (FAIR) team and the Broad Institute of MIT and Harvard’s Imaging Platform. While I’m best known for my work in microscopy, my primary research interest is differentiable programming. I was an active member of the demoscene and, as far as I know, the only American programmer to have won multiple Scene.org and Meteoriks awards.
Serrano, E., Chandrasekaran, S., Bunten, D., Brewer, K., Tomkinson, J., Kern, R., …, Goodman, A., & others (2025). Reproducible image-based profiling with Pycytominer. Nature Methods, 22(4), 677–680.
Ismail, A., Oikarinen, T., Wang, A., Adebayo, J., Stanton, S., Joren, T., Kleinhenz, J., Goodman, A., Corrada Bravo, H., Cho, K., & others (2025). Concept bottleneck language models for protein design. In International Conference on Learning Representations.
Frey, N., Hötzel, I., Stanton, S., Kelly, R., Alberstein, R., Makowski, E., …, Goodman, A., & others (2025). Lab-in-the-loop therapeutic antibody design with deep learning. bioRxiv preprint.
Caicedo, J., Goodman, A., Karhohs, K., Cimini, B., Ackerman, J., Haghighi, M., Heng, C., Becker, T., Doan, M., McQuin, C., & others (2019). Nucleus segmentation across imaging experiments: the 2018 Data Science Bowl. Nature Methods, 16(12), 1247–1253.
McQuin, C., Goodman, A., Chernyshev, V., Kamentsky, L., Cimini, B., Karhohs, K., Doan, M., Ding, L., Rafelski, S., Thirstrup, D., & others (2018). CellProfiler 3.0: Next-generation image processing for biology. PLoS Biology, 16(7), e2005970.