Publications

Jarrid Rector-Brooks*, Théophile Lambert*, Marta Skreta*, Daniel Roth*, Yueming Long, Zi-Qi Li, Xi Zhang, Miruna Cretu, Francesca-Zhoufan Li, Tanvi Ganapathy, Emily Jin, Joey Bose, Jason Yang, Kirill Neklyudov, Yoshua Bengio, Alexander Tong, Frances H. Arnold, Cheng-Hao Liu. *Equal contribution. (2026). General Multimodal Protein Design Enables DNA-Encoding of Chemistry. aRxiv.

PDF Code Project

Emily Jin*, Andrei Cristian Nica*, Mikhail Galkin, Jarrid Rector-Brooks, Kin Long Kelvin Lee, Santiago Miret, Frances H. Arnold, Michael Bronstein, Joey Bose, Alexander Tong, Cheng-Hao Liu. *Equal contribution. (2026). OXtal: An All-Atom Diffusion Model for Organic Crystal Structure Prediction. International Conference on Learning Representations (ICLR).

PDF Code Project

Linus Bao*, Emily Jin*, Michael Bronstein, İsmail İlkan Ceylan, Matthias Lanzinger. *Equal contribution. (2025). Homomorphism Counts as Structural Encodings for Graph Learning. International Conference on Learning Representations (ICLR).

Emily Jin, Michael Bronstein, İsmail İlkan Ceylan, Matthias Lanzinger (2024). Homomorphism Counts for Graph Neural Networks: All About That Basis. International Conference on Machine Learning (ICML).

Emily Jin, J Alison Noble, Mireille Gomes (2023). A Review of Computer-Aided Diagnostic Algorithms for Cervical Neoplasia and an Assessment of Their Applicability to Female Genital Schistosomiasis. Mayo Clinic Proceedings: Digital Health.

Alexander Kitaygorodsky, Emily Jin, Yufeng Shen (2021). Predicting Localized Affinity of RNA Binding Proteins to Transcripts with Convolutional Neural Networks. bioRxiv.