Summary
Mohammad Zadenoori is a postdoctoral researcher and computational biologist with eight years of experience applying machine learning and GPU-accelerated computing to biomedical and transport problems. Holding a PhD in Computer Engineering with a specialization in ML, he builds high-performance R and Python tools for single-cell genomics within Bioconductor and has optimized end-to-end workflows for normalization, clustering, and differential expression. His background spans applied AI in industry—improving transit scheduling with deep learning and delivering production Flask services—and healthcare, where he developed ML models for retinal pathology detection from OCT imaging. He has explored prompt engineering for requirements automation and practical LLM-based systems like a "Talk to PDF" support chatbot, reflecting a blend of research and product-minded engineering. Comfortable shipping open-source code and collaborating across academia and industry, he brings both theoretical rigor and pragmatic optimization skills to large-scale bioinformatics challenges. An often-overlooked strength is his track record of translating research prototypes into deployable pipelines that leverage GPU parallelism for real-world datasets.
8 years of coding experience
5 years of employment as a software developer
Master's Degree, Artificial Intelligence, Master's Degree, Artificial Intelligence at Qazvin Islamic Azad University
PhD in Computer engineering., Computer science with Specialization in Machine Learning, PhD in Computer engineering., Computer science with Specialization in Machine Learning at Università degli Studi di Firenze
Data Scientist Nanodegree, data scientist, Data Scientist Nanodegree, data scientist at Udacity
Bachelor's Degree, Information Technology, Bachelor's Degree, Information Technology at Hamedan university of Technology (HUT)
English, Italian, Persian