Summary
Luis Camara is an interdisciplinary scientist-engineer with 11 years' experience applying computational chemistry, machine learning and computer vision to real-world problems, now focused on AI-driven drug discovery at the University of Geneva. He holds a PhD in Computational Chemistry and MSc degrees in Digital Signal Processing and Computer Vision, and bridges physics-based molecular modelling (docking, MD) with modern ML—especially GNNs and diffusion models—for virtual screening and generative molecular design. His career ranges from DSP and music fingerprinting systems that powered commercial platforms to state-of-the-art visual place recognition and multi-person tracking for robotics, demonstrating a rare ability to move ideas from research to deployed tools. Notably, his chemometrics work used GC–MS profiles to predict Pinot Noir origin and vintage with high accuracy, revealing sensory patterns through data science. He combines hands-on engineering (pipelines, dashboards, automated benchmarks) with deep domain knowledge to accelerate early discovery cycles and improve ligand prioritisation.
11 years of coding experience
13 years of employment as a software developer
PhD Computational Chemistry, PhD Computational Chemistry at Imperial College London
BSc Chemistry (Chemical Physics), BSc Chemistry (Chemical Physics) at Universidad Complutense de Madrid
Master of Science (MSc) Digital Signal Processing (Music), Master of Science (MSc) Digital Signal Processing (Music) at Queen Mary University of London
Master of Science (MSc) Computer Vision, Master of Science (MSc) Computer Vision at Universidad Rey Juan Carlos
English, Spanish, French