I am a PhD Candidate at the Institute for Protein Design at the University of Washington, working in the DiMaio Lab on improving biomolecular structure-prediction models for modeling and engineering protein-ligand and antibody-antigen interactions.

Education

• Ph.D. Candidate (passed General Exam, December 2025)
  Institute for Protein Design
  University of Washington
• M.S. in Molecular Engineering and Sciences
  University of Washington, 2024
• B.S. in Computer Science, Minor in Chemistry & Biochemistry @ Georgia Institute of Technology, 2022

Publications

Linker-Length Landscape Mapping Enables Coupling of Diverse Synthetic Chemically Induced Dimerization Systems to Molecular Readouts

Pan Y, Kang S, **Nakajima An D**, Yu Y, DiMaio F, Gu L. Linker-Length Landscape Mapping Enables Coupling of Diverse Synthetic Chemically Induced Dimerization Systems to Molecular Readouts. bioRxiv; 2026. doi: https://doi.org/10.64898/2026.07.01.735888

AF2Complex predicts direct physical interactions in multimeric proteins with deep learning

Gao, M., **Nakajima An, D.**, Parks, J.M. et al. AF2Complex predicts direct physical interactions in multimeric proteins with deep learning. Nat Commun 13, 1744 (2022). https://doi.org/10.1038/s41467-022-29394-2

Deep Learning System for Labeling Neurology Text

**An, Davi Nakajima**, Kartchner, D., Zhang, C., & Mitchell, C. S. (2021, October). Deep Learning System for Labeling Neurology Text for Predictive Medicine. In ANNALS OF NEUROLOGY (Vol. 90, pp. S159-S160). 111 RIVER ST, HOBOKEN 07030-5774, NJ USA: WILEY.

ReGAL: Rule-Generative Active Learning for Model-in-the-Loop Weak Supervision

David Kartchner, Wendi Ren, **Davi Nakajima An**, Chao Zhang, and Cassie S. Mitchell. ReGAL: Rule-Generative Active Learning for Model-in-the-Loop Weak Supervision. Retrieved from https://par.nsf.gov/biblio/10286627. Advances in neural information processing systems .