Senior Research Software Engineer

Cunliang (Liang) Geng

Cunliang is a Senior Research Software Engineer. His work sits at the interface of scientific research, software engineering, and machine learning, with a focus on designing robust, reusable, and open-source software for life sciences research.

He holds a PhD in computational structural biology from Utrecht University, where he applied machine learning methods to study protein interactions — an area that has become increasingly central with the rapid progress of AlphaFold and related approaches for protein structure prediction and design. His background also includes statistical mechanics and bioinformatics during his master’s studies, giving him a broad foundation in molecular modelling and simulation.

Since joining the eScience Center, Cunliang has played important technical and collaborative roles in more than a dozen life sciences projects, working closely with research groups in the Netherlands and internationally. He has extensive experience designing and optimising deep learning systems, building scalable scientific data pipelines, and developing high-performance computing solutions. His work spans topics such as deep learning for bimolecular science, multi-omics data integration and analysis, federated learning, and scalable scientific data infrastructure. 

In these collaborations, Cunliang contributes not only as an engineer, but also as a technical lead and scientific partner: helping researchers translate complex biological questions into computational workflows, making architectural decisions, guiding software design, ensuring code quality and sustainability, and supporting research teams in adopting best practices for reusable and maintainable research software. All of his research software contributions are open source and can be found at Github and Research Software Directory.

In addition, he is a certified Carpentries instructor and have delivered training for researchers on deep learning, parallel programming, Docker containers, and other research computing skills. Through both project work and training, he actively supports the development of research software capacity within the life sciences community.