I work on statistical learning and inference problems that arise in data-driven design: the design of novel objects with desired properties, such as proteins or small molecules, in a way that is learned from data. How can we quantify uncertainty or estimate risk when we deploy design algorithms? How can we understand the inductive biases of generative models used for design? I am particularly interested in these questions in the context of protein engineering.

I also maintain an interest in machine learning methods for exploring life in our last great frontier, the ocean.

Some highlighted work is below. See Google Scholar for a complete record.

* denotes equal contribution. (\(\alpha\)-\(\beta\)) denotes alphabetical ordering.

preprints

  • (\(\alpha\)-\(\beta\)) Anastasios N. Angelopoulos, Stephen Bates, Clara Fannjiang, Michael I. Jordan, and Tijana Zrnic. Prediction-powered inference. 2023. arXiv code

  • Danqing Zhu*, David H. Brookes*, Akosua Busia*, Ana Carneiro, Clara Fannjiang, Galina Popova, David Shin, Edward F. Chang, Tomasz J. Nowakowski, Jennifer Listgarten, and David V. Schaffer. Optimal trade-off control in machine learning-based library design, with application to adeno-associated virus (AAV) for gene therapy. 2021. bioRxiv bibtex

refereed conferences

  • Clara Fannjiang and Jennifer Listgarten. Autofocused oracles for model-based design. NeurIPS 2020. arXiv proceedings code bibtex

journals

  • Clara Fannjiang, Stephen Bates, Anastasios N. Angelopoulos, Jennifer Listgarten, and Michael I. Jordan. 2022. Conformal prediction under feedback covariate shift for biomolecular design. Proceedings of the National Academy of Sciences, 119(43), e2204569119. arXiv publication PDF code bibtex talk

  • Chloe Hsu, Hunter Nisonoff, Clara Fannjiang, and Jennifer Listgarten. 2022. Learning protein fitness models from evolutionary and assay-labelled data. Nature Biotechnology, 40, 1114–1122. PDF publication bibtex

  • Clara Fannjiang, T. Aran Mooney, Seth Cones, David Mann, K. Alex Shorter, and Kakani Katija. 2019. Augmenting biologging with supervised machine learning to study in situ behavior of the medusa Chrysaora fuscescens. Journal of Experimental Biology, 222, jeb207654. PDF publication jellyfish footage code bibtex

  • Clara Fannjiang. 2013. Optimal arrays for compressed sensing in snapshot-mode radio interferometry. Astronomy & Astrophysics, 559, A73. PDF publication bibtex


Benthocodon hyalinus, after photo by K. Raskoff in Matsumoto et al. (2020).