Summary
Enes Senel is a senior scientist and PhD-trained bioinformatician based in Berlin with 12 years of experience applying machine learning to biological problems, from spatial transcriptomics to proteome–transcriptome integration. He developed Optocoder, a machine learning pipeline for optical sequencing–based spatial transcriptomics, and has translated research into industry roles at Johnson & Johnson where he focuses on ML-driven cell therapy. His background spans academia and industry—projects include predicting anti-insecticidal proteins, flow microscopy image analysis, and real‑time medical robotics vision—showing a rare mix of computational rigor and practical engineering. Comfortable bridging algorithm development and experimental datasets, he combines deep learning, data integration, and domain adaptation to probe cellular dynamics and cell–cell interactions.
12 years of coding experience
9 years of employment as a software developer
Bachelor of Science (B.S.), Computer Science, Bachelor of Science (B.S.), Computer Science at Özyeğin University
Master of Science (M.S.), Computer Science, Master of Science (M.S.), Computer Science at Technical University Munich
Doctor of Philosophy - PhD, Bioinformatics, Doctor of Philosophy - PhD, Bioinformatics at Humboldt-Universität zu Berlin
Anatolian High School Diploma, Anatolian High School Diploma at Kadıköy Anadolu Lisesi ve Maarif Koleji
English, German, Turkish