Leandro Martin Velez
Bioinformatics Ml Ai Scientist @Genentech
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WORK HISTORY
Bioinformatics Ml Ai Scientist @Genentech
Genentech (via Astrix Technologies)I am a Bioinformatics and ML Scientist within the Computational Biology & Medicine department at Genentech’s Research and Early Development (gRED) Center of Excellence. My work focuses on the intersection of high-dimensional biological data and predictive modeling to advance drug development and precision medicine.Key Contributions:Advanced ML Modeling: Developing and implementing state-of-the-art machine learning models to predict patient risk and clinical outcomes using multi-modal datasets.Data Harmonization: Leading the centralization and integration of heterogeneous data sources, including clinical trial results, genetics, and multi-omics (WGS, transcriptomics/proteomics).Feature Engineering: Deriving novel features from complex, high-dimensional datasets to identify predictive signatures and biomarkers.Cross-Functional Collaboration: Partnering with interdisciplinary teams of biologists, chemists, and clinical scientists to translate computational insights into actionable research strategies.Technical Toolkit:Programming: Expertise in R and Python for data manipulation, statistical analysis, and ML pipeline development.Modality Expertise: Proven ability to work with diverse data types, including omics, clinical safety labs, and unstructured text.Specialized Methods: Statistical modeling, survival analysis, and the application of NLP/LLMs for feature extraction.
EDUCATION
Faculty of Exact and Natural Sciences, University of Buenos Aires
Degree in Biological Sciences, Molecular Biology
Facultad de ciencias exactas y naturales (FCEyN), UBA
Profesorado en Cs. Biológicas, Docencia
Faculty of Exact and Natural Sciences, University of Buenos Aires, Argentina
PhD, Biomedical Sciences
University of Buenos Aires
Bachelor's Degree, Biology/Biological Sciences, General
University of Buenos Aires
Doctor of Philosophy, Molecular Biology
ABOUT LEANDRO MARTIN VELEZ
Highly accomplished and results-oriented Molecular Biology Scientist turned Bioinformatician with a proven track record of leading preclinical research projects from hypothesis generation to publication. Expertise in pre-clinical disease models, systems genetics, and multi-omics data integration and analysis, particularly in the areas of metabolic diseases (PCOS, Obesity) and cancer. Proficient in developing and optimizing molecular assays, including NGS, RNA-seq, qPCR, Western blot, and ELISA. Adept at bioinformatics analysis using R and Python, integrating multi-omics data with clinical and phenotypic information to uncover novel biological insights. PhD Molecular Biology Email: l••••••••@gmail.com Possess a strong foundation in both in vivo research, including extensive experience with rodent models, and in vitro studies, utilizing various cell culture techniques. Experience working under GLP-like conditions with meticulous documentation and quality control. Passionate about advancing scientific knowledge and translating research findings into impactful solutions. CORE COMPETENCIES- In Vivo Pharmacology; Disease Modeling- Metabolic Phenotyping & Analysis- NGS (RNA extraction, library prep, seq, and posterior in silico analysis); Multi-omics integration and analysis- In Vitro cultures of mammalian cells for tissue - tissue communication studies- Molecular Biology Techniques (qPCR, WB, ELISA)- Rodent Handling, Dosing (IP, PO, SQ, IV); Surgical Procedures- Bioinformatics; Statistical Analysis (R, Python)- Project Leadership; Collaboration- Mentoring; Training SOFTWARE PROFICIENCIES- Microsoft Office Suite (Excel, Word, PowerPoint)- Inkscape/Adobe Illustrator (Vector Graphics)- GraphPad Prism (Data Visualization; Statistical Analysis)- SPSS (Statistical Software) and JMP- ImageJ (Image Analysis)- R (Statistical Computing & Data Visualization)- FastQC (Sequence Quality Control)- RNA-Seq Data Analysis (STAR, Kallisto, Salmon, DESeq2, edgeR/limma)- Single-cell RNA-Seq and Spatial Analysis (Seurat)
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