Bryan Naidenov, Ph.D. Email and Phone Number

Machine learning industry scientist with expertise in mathematical modeling, machine learning, Bayesian inference, and artificial intelligence in the pharmacological space.• 8 years of R&D experience in quantitative modeling & algorithm design for trait prediction, biomarker identification, and drug discovery.• Modeling expertise: Deep learning, Bayesian modeling, variational inference, causal inference, uncertainty estimation, transformers, self-supervised LLMs, (mixed) linear programming, model validation, hypothesis testing, BLUPs, RKHS regression, and general Monte Carlo methods.• Assays: High-throughput sequencing (scRNA-seq, DRUG-seq, DNase-seq, Perturb-seq, ATAC-seq, ChIP-seq), phenotypic screening (high-content cellular imaging), and viability screening (LDH).• Therapeutic areas: Rare disease, neurological disorders, and oncology for drug repurposing in preclinical disease models.My academic research was focused on developing deep learning models for complex polygenetic traits (grain yield, protein content, and flowering time) in staple crops, like Triticum aestivum, by learning informative Euclidean spaces for high-dimensional genomic data. Proficient in Python, R, and C++ in UNIX HPC systems.