Google Summer of Code Students 2025

We are proud to announce that MDAnalysis — in collaboration with Molecular Nodes, ProLIF, and WESTPA — is hosting four Google Summer of Code (GSoC) contributors: @jpkrowe, @nilay-v3rma, @PardhavMaradani, and @yuyuan871111. MDAnalysis has been accepted as its own organization with GSoC for the sixth year in a row. We are grateful to Google for granting us the opportunity to get started on these four very exciting projects!

James (Jamie) Rowe: Integrating MDAnalysis Streaming Analysis within WESTPA Propagators

James’ project is a collaboration between MDAnalysis and WESTPA, a toolkit for running Weighted Ensemble simulations. In Weighted Ensemble simulations, many short trajectories are run in parallel and evaluated after each iteration to identify those that have progressed along a predefined coordinate. This analysis step can become a bottleneck, as all trajectories must be loaded and processed before the next iteration can begin. The goal of this project is to use MDAnalysis’ trajectory streaming capabilities to analyze trajectories on-the-fly, reducing analysis overhead and decreasing the time between iterations.

James is a 3rd year PhD student at Imperial College London. His PhD project aims to use molecular dynamics to understand how mutations and modifications to the fundamental building blocks of bone, such as collagen, lead to increased fracture risk and compromised mobility. He has recently released an article on selective rupture in collagen and a review article that integrates experimental and computational advances in bone research.

You can find James on GitHub, LinkedIn and Bluesky.

To find updates on this project, check out his blog here!

Nilay Verma: Enhancing ProLIF Visualizations: A Hybrid Approach for Automated, Customizable 2D Interaction Layout

Nilay’s project focuses on improving the 2D interaction visualizations in ProLIF, a tool for analyzing molecular interactions such as protein–ligand and protein–protein binding. He is enhancing LigNetwork plots by implementing graph-based algorithms to automate residue placement, reduce edge overlaps, and improve overall readability. Additionally, he is exploring the integration of visualization approaches from tools like InteractionDrawer and Flareplot to improve the visual representation of interactions. The goal is to create a more user-friendly and informative visualization tool for researchers.

Nilay is a sophomore at Indian Institute of Technology Gandhinagar (IITGN), pursuing a dual major in B.Tech Computer Science and Materials Science. He is passionate about computational materials science, machine learning, and generative AI and its applications.

You can find Nilay on GitHub, LinkedIn and his Portfolio.

To keep up with his work, you can check out his gsoc-blog.

Pardhav Maradani: Better Interfacing of Blender and MDAnalysis

MDAnalysis has a basic interface with Blender through a popular extension called Molecular Nodes, which allows importing MDAnalysis universes and provides advanced rendering capabilities through a GUI. The ability to script and support advanced visualizations of MDAnalysis results is currently limited. This project attempts to define, prototype and implement various APIs along with an integrated GUI within Blender as part of GGMolVis and Molecular Nodes that will together provide advanced visualization capabilities for MDAnalysis.

Pardhav is an undergraduate student from India pursuing a Bachelors in Computer Science and Engineering from Vellore Institute of Technology (Vellore) and a BS in Data Science and Applications from Indian Institute of Technology (IIT) Madras.

You can find Pardhav on GitHub @PardhavMaradani.

To see updates on this project, you can check out his blog.

Yu-Yuan (Stuart) Yang: MDAnalysis x ProLIF Project 5: H-Bond Interactions from Implicit Hydrogens

ProLIF, a MDAnalysis/RDKit-based tool for identifying protein-molecule interactions in molecular dynamics trajectories, lacks a straightforward method for evaluating hydrogen bonds when only heavy atoms are present. This project introduces an “implicit hydrogen bond (H-bond) interaction method” directly using heavy atom positions to detect H-bonds. This new feature for ProLIF will help many users (especially, beginner-level programming users) compare their experimental and computational structures without explicit hydrogens.

Yu-Yuan (Stuart) graduated from National Taiwan University (Taipei, Taiwan), holding a Bachelor of Science in Agricultural Chemistry, a Bachelor of Engineer in Chemical Engineering, and a Master of Science in Biomedical Electronics and Bioinformatics. He worked on both wet-lab (WPI fibril microcapsules, SEA-PHAGE) and dry-lab (FastEval Parkinsonism, Quantum computing for drug discovery, MD simulations of SARS-CoV-2 omicron variants, Automated WGS(WES) reporting system) projects. Stuart currently studies for a PhD in UKRI-AIDD doctoral training programme in Richard W. Pickersgill’s and Arianna Fornili’s group at Queen Mary University of London (London, UK) to explore protein conformations with a computer-vision-based deep learning model. He is pursuing a career as a computational research scientist in drug discovery. During the free time, Stuart enjoys playing volleyball and badminton and sometimes visiting new places and cities with his family and friends.

You can find Stuart on GitHub as @yuyuan871111 and on LinkedIn. To keep up to date with his latest projects, check out his blog.

— @BradyAJohnston @cbouy @fiona-naughton @jeremyleung521 @ljwoods2 @ltchong @orbeckst @talagayev @yuxuanzhuang @IAlibay @jennaswa (@MDAnalysis/gsoc-mentors and org admins)