Yves Gaetan Nana Teukam

I am Yves Gaetan Nana Teukam, a Pre-Doctoral Researcher at IBM Research Zürich, focused on developing AI/ML methods to enhance scientific discovery and contribute to open-source projects. Currently, I am pursuing my Ph.D. in Biomedical Engineering at IBM Research and Eindhoven University of Technology, expected to be completed in March 2025.

My research integrates large language model fine tuning for protein engineering and the development of efficient ML pipelines for biocatalysis. Notable projects include Enzeptional, an end-to-end ML pipeline for enzyme optimization that integrates large language models with evolutionary optimization techniques. I also created LM-ABC, a chatbot framework that automates bioinformatics workflows, and RXNAAMapper, a transformer-based tool that achieved state-of-the-art accuracy in enzymatic binding site prediction. In addition to these projects, I have actively contributed to several open-source initiatives. My involvement with the GT4SD library focuses on training generative models to accelerate scientific discovery. I have also developed molecular dynamics simulation frameworks for validating AI-generated protein designs and implemented techniques for transfer learning in reaction prediction.

Previously, I led a bioinformatics project at StemAway, guiding an international team through gene expression analysis while implementing an automated quality control pipeline that halved analysis time. My internship at Sequentia Biotech provided me with hands-on experience in microbiome analysis and enterotype classification.

My research has been published in leading journals such as Nature Communications and the Computational and Structural Biotechnology Journal. In 2022, our IBM Research team was awarded the IEEE Open Software Services Award for GT4SD (Generative Toolkit for Scientific Discovery).

I hold a Master's degree in Data Science and a Bachelor's degree in Bioinformatics from the University of Rome La Sapienza. This interdisciplinary background empowers me to tackle complex biological challenges through innovative AI solutions.

My expertise spans various domains such as protein design, biocatalysis, drug discovery, and green chemistry, all aimed at making scientific discovery more efficient and accessible through AI technologies.

On this website, you can explore my research projects and publications. If you are interested in discussing applications of AI in scientific discovery or potential collaborations, please feel free to reach out.