Carlos Oliver Homepage

I am leading the Molecular Pattern Mining Project Group at the Department of Machine Learning and Systems Biology at the Max Planck Institute of Biochemistry, based in Munich, Germany. Formerly postdoc at ETH Zurich and a member of the labs of Jérôme Waldispühl and William L. Hamilton during my PhD studies in Computer Science.

I build algorithms that help us understand network data (often biological). More on my research here.

Contact

• Academic: oliver@biochem.mpg.de
• Business & Personal: carlos@ozeki.io
• GitHub: @cgoliver

Updates

• Book chapter on using rnaglib for RNA function prediction on ArXiV [ArXiV].
• Preprint on injecting structural language to large protein language models posted [ArXiV].
• Paper on conditional structure-aware substitution matrices accepted at RECOMB 2024! Preprint coming soon..
• Preprint on RNA drug discovery bioRxiv
• Paper on Multimodal learning for antimicrobial bacteria resistance accepted at Bioinformatics! [paper]
• ProteinShake accepted at NeurIPS 2023 Datasets and Benchmarks! Preprint coming soon..
• Open position PhD in my research group at the Max Planck Institute. [More info]
• Joint multidimensional scaling accepted at ICLR 2023! [ArXiV]
• McGill University School of Computer Science Colloquium talk on algorithms for molecular structure-function mapping. [slides]
• Preprint on graph neural networks for motif mining. [ArXiV]
• RNAglib, python package for ML on RNA 2.5D graphs is published in Bioinformatics Journal.
• Fuzzy network motif mining paper has been published at Bioinformatics.

Fields of study

• RNA and protein computational structural biology
• Structural bioinformatics
• Network motif mining
• Graph representation learning
• Drug discovery

Activities

• Google Scholar
• Consulting at Ozeki Inc.
• Pear Review
• Former Lead Scientist in Residence at Next AI
• Member of The Heterodox Academy

Reviewing (by topic)

• Bio(informatics): OUP Bioinformatics, ISMB, RECOMB, Nucleic Acids Research, eLife
• Machine Learning: Journal of Machine Learning Research, AAAI, NeurIPS
• Data Mining: KDD, IEEE Transactions on Emerging Topics in Computing, SIAM International Conference on Data Mining
• Cheminformatics: Nature Communications Chemistry, Journal of Cheminformatics

Software

• rnaglib: analysis and deep learning on RNA 2.5D and 3D models (Homepage, Source Code)
• proteinshake: deep learning on protein 3D structures (Homepage, Source Code)

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