PhD candidate at EPFL, Switzerland
I am a PhD candidate in Computational and Quantitative Biology at the Laboratory for Biomolecular Modeling, EPFL, advised by Prof. Matteo Dal Peraro. I work on machine learning for structural bioinformatics, computational biophysics and integrative modeling, and lately on designing RNA. Outside research I enjoy chess, close-up magic, traveling, reading, and building things.
A parameter-free geometric deep learning approach that generates RNA sequences conditioned on both their backbone scaffolds and the surrounding molecular context. Presented at the NeurIPS 2025 AI4D3 workshop.
A geometric transformer extending PeSTo to predict binding interfaces between proteins and carbohydrates, including cyclodextrins. Featured on the cover of JCTC.
Full list on the publications page.
EPFL, Switzerland
Advisor: Prof. Matteo Dal Peraro
IISER Kolkata, India
Thesis: Applications of Geometric Deep Learning for Biomolecular Structure Modeling
Advisor: Prof. Matteo Dal Peraro
Supervised the computational and mathematical modeling of a synthetic biology project.
Teaching assistant.
Teaching assistant for the molecular dynamics, molecular modeling, and cryo-EM modules.
Always open to collaborating on interesting problems in RNA and protein design, computational biology, and structural bioinformatics.
parth.bibekar@epfl.ch