Bryan Naidenov, Ph.D. Email & Phone Number

Cambridge, Massachusetts, United States

Palo Alto, California, United States

Lead ML/AI Scientist for the drug discovery platform.- Led the development and implementation of advanced AI models for predicting drug effects on gene expression perturbations.-Oversaw cross-functional efforts to conduct comprehensive in silico screening of billions of small molecules, identifying bioactive compounds for therapeutic applications in rare neuronal diseases.-Developed and utilize generative chemistry models to discover novel drug candidates and enhance drug discovery processes through innovative quantitative and computational techniques.

Stillwater, Ok

PhD candidate focusing on modeling high-dimensional genomic data with AI for crop phenotype prediction.1. Prediction of breeding values for several agronomic traits from a double haploid population of red winter wheat by deriving novel genome graphic representations and convolutional neural networks.2. Derivation of learned quantitative latent embeddings (4000 genomes from populations of lodgepole pine and white spruce) using a novel self-supervised learning objective based on incorporating genomic similarities in different contexts.3. Employed a Bayesian Hierarchical model to identify functional antimicrobial resistance genes in the domestic Salmonella enterica population as part of an association analysis. 4. Analysis of transcriptome landscape in upland cotton using polynomial models to identify relationships between domesticated transposons and promotors relating to salt tolerance.

Stillwater, Ok

Technical staff in charge of manipulating high-throughput third-generation DNA sequencing for back-end development and quantitative modeling. 1. Developed large-scale SNP databases for maize, allowing fast variable subsetting to support various regression algorithms using Sequence Ontology (SO) queries. 2. In charge of creating a back-end for bulk data cleaning/processing/transformation using a High-Performance Computing environment. 3. Created a JavaScript-based interface for high-speed access to HDF5 formats containing SNPs, phylogenetic information, and phenotypic data with the backend written in C++.4. Worked extensively with third-generation long-read sequencing technology for constructing the genomes of drought-resistant wheat varieties. 5. Built bioinformatics pipeline for rapid multiple-sequence alignments and SNP-calling for plant genomes, using BAM/VCF formats and the optimal aligners for noisy read mapping.

Doctor Of Philosophy - Phd, Biochemistry And Molecular Biology

Bachelor Of Science - Bs, Biology, General, Cum Laude