Matteo D'Antonio

Experienced geneticist and bioinformatics scientist with 15+ years of research expertise in leveraging machine learning and computational methods to enhance disease prediction, therapeutic discovery, and precision medicine. Recognized for leading cross-functional projects, securing significant funding, and publishing extensively, with 48+ peer-reviewed articles (19 first author) and an h-index of 26 in prominent journals such as Nature, Nature Genetics, Nature Communications, Cell Reports, PLoS Computational Biology and Cell Genomics. Experienced lecturer and conference speaker, presenting research at 23+ academic and industry conferences and teaching multiple graduate-level courses in bioinformatics and medical informatics.

Demonstrated ability to drive impactful collaborations in large, multidisciplinary, and international projects, excelling in multitasking and managing complex priorities effectively. Proficient in real-world data analysis, human genetics with a particular focus on diversity and social determinants of health, evolutionary bioinformatics, and interdisciplinary team collaboration.

Assistant Professor

Division of Biomedical Informatics, Department of Medicine, University of California, San Diego

March 2022 – present

• Developed high-accuracy machine learning prediction tools for skin cancer and cardiovascular disease risk using genetic, health record, environmental variables and social determinants of health using real-world data (All Of Us).
• Co-Investigator on the NIH Centers for Excellence in Genomics Center for Admixture Science and Technology (CAST), a multi-institute collaboration across the US, including UC San Diego, Yale, University of Indiana and VA Palo Alto.
• Member of the SMART Cancer Care Teams: Enhancing EHR Communication to Improve Interprofessional Teamwork, a multicenter working group that combines members from UC San Diego, UC Davis, UCLA and University of Iowa.
• Spearheaded projects enhancing predictive power in precision medicine by integrating genome-wide association studies (GWAS) and Polygenic Risk Scores (PRS) with environmental data for diverse populations.
• Principal Investigator on an American Cancer Society grant for developing polygenic risk scores in breast cancer.
• Mentored 19 students in genome analysis and computational biology, building expertise in bioinformatics and applied biomedical informatics.

Assistant Project Scientist

Department of Pediatrics and Institute for Genomic Medicine, University of California, San Diego

May 2018 – February 2022

• As a member of the of the international iPSCORE and i2QTL consortia (UC San Diego, Stanford, EMBL-EBI), published 30 manuscripts on the genomics, transcriptomics and epigenomics of induced pluripotent stem cells (2015-2024, >1,200 citations), including nine as first author.
• As member of the international consortium COVID 19 Host Genetics Initiative, conducted pan-tissue SARS-CoV-2 susceptibility studies, revealing significant genetic drivers of COVID-19 severity across cell types.
• Identified a novel gene that affects cystic fibrosis severity, which supported a successful NIH RM1 grant application ($13.6M).
• Identified potential therapeutic targets in heart failure by analyzing RNA Binding Proteins
• Characterized novel mechanisms underlying cardiovascular disease by studying iPSC-derived cardiac cell types.

Postdoctoral Scholar

Moores Cancer Center and Institute for Genomic Medicine, University of California, San Diego

April 2013 – April 2018 

• Conducted the first somatic mutation landscape analysis in iPSCs, combining whole genome sequencing and epigenomic data for mutation profiling.
• Identified the kataegis mutational signature as a novel prognostic marker in breast cancer, described by 20+ news outlets.
• Developed pioneering methods for non-coding driver mutation detection in breast cancer, including in vivo validation in Ciona intestinalis.

PhD Student and Postdoctoral Scholar

European School of Molecular Medicine and European Institute of Oncology, Milan, Italy

January 2008 – March 2012 (PhD); March 2012 – March 2013 (Postdoctoral Scholar)

• Analyzed protein interaction network evolution across species, mapping gene duplicability impacts on cancer genomics.
• Developed a new method to identify novel cancer drivers in ovarian cancer by integrating expression profiles, mutation effects, and systemic properties of mutated genes.
• Established the Network of Cancer Genes (NCG) database, integrating mutation, interaction, and evolutionary data for cancer genomics (7 versions, >1,000 citations).

• European School of Molecular Medicine and European Institute of Oncology (2008-2012): PhD in Molecular Medicine
• Politecnico di Milano (2006-2008): MSc in Biomedical Engineering
• Technical University of Denmark (2004-2006): MSc in Bioinformatics
• Politecnico di Milano (2001-2004): BSc in Biomedical Engineering