About me
Hi, I am a AI Research Scientist Intern at Absci in New York, focusing on generative models for protein design.
I hold a Master’s degree in Advanced Computer Science from the University of Cambridge. For my Master’s thesis, I worked on diffusion models for antibody design, advised by Professor Pietro Liò and Professor José Miguel Hernández-Lobato. Prior to my Master’s, I was a Software Engineer at Morgan Stanley.
My research interests include generative models and geometric deep learning for applications in molecular modeling and protein design.
An up-to-date list of my publications is available below and on my Google Scholar.
Publications
Improving Antibody Design with Force-Guided Sampling in Diffusion Models. Paulina Kulytė, Francisco Vargas, Simon Valentin Mathis, Yu Guang Wang, José Miguel Hernández-Lobato, Pietro Liò. arXiv (2024). [pdf]
Metric Learning for Clifford Group Equivariant Neural Networks. Riccardo Ali*, Paulina Kulytė*, Haitz Sáez de Ocáriz Borde, Pietro Liò. ICML 2024 Workshop on Geometry-grounded Representation Learning and Generative Modeling (2024). [pdf]