School of Medicine
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Samuel Montalvo Hernandez
Postdoctoral Scholar, Cardiovascular Medicine
BioAs a clinical exercise physiologist and sport biomechanist, I am dedicated to advancing human exercise and sports performance. I hold certifications as a Performance and Sport Scientist (CPSS) and as a Strength and Conditioning Specialist with Distinction (CSCS, *D) from the National Strength and Conditioning Association (NSCA). In 2022, I was honored with the Wu Tsai Human Performance Alliance Post-Doctoral Research Fellowship and a T32 Post-Doctoral Fellowship, Research Training in Myocardial Biology (TIMBS) at Stanford University.
My research focuses on understanding the mechanical, molecular, and physiological mechanisms that underpin human performance. I am also committed to developing innovative and practical training methods to enhance exercise and sports performance. Currently, I am a member of the Stanford Bioinformatics Core, contributing to the NIH-funded Molecular Transducers of Physical Activity Consortium (MoTrPAC) project. In this capacity, I analyze extensive clinical and exercise datasets, as well as multi-omic, multi-tissue, multi-exercise modality, and multi-species data, to uncover new insights into the biological mechanisms of physical activity and its impact on human health and performance.
In addition to my primary research focus, I collaborate with several teams at Stanford on projects involving Sports and Electrocardiography, Cardiopulmonary Exercise Testing, Exercise and Neuromuscular Disease, and the Stanford Baseball Team.
Beyond research, I am deeply committed to teaching, mentoring, and promoting diversity. As a first-generation college graduate and a Mexican-American with Indigenous heritage, I bring a unique perspective to my work, which informs my dedication to creating supportive and inclusive spaces for underrepresented groups in science and education. I serve as a Post-Doc Mentoring Coach in collaboration with the Stanford Office of Postdoctoral Affairs, where I facilitate bi-weekly workshops on mentoring for postdocs. I am also part of the Stanford PRISM program, which promotes inclusion and diversity among postdoctoral scholars. Furthermore, I mentor prospective and current medical students through the MAVERICs program (Metascience Analyses and Explorations of Reproducibility in Cardiovascular Science) as part of the Stanford Cardiovascular Institute, supporting their growth in cardiovascular research.
These experiences reflect my dedication to fostering an inclusive and supportive academic environment. My long-term goal is to become a professor, combining my passion for research, education, and mentoring the next generation of scientists to advance the fields of exercise physiology and sports science. -
Connor Galen O'Brien
Postdoctoral Medical Fellow, Cardiovascular Medicine
BioDr. O'Brien is a native of Menlo Park, CA. He attended medical school at Columbia University College of Physicians and Surgeons. At Columbia he was elected to both Alpha Omega Alpha and Gold Humanism Honors Societies. He completed an Internal Medicine residency as well as fellowship in Cardiovascular Medicine at Stanford University. In his third year of fellowship, he was selected Chief Cardiology Fellow.
He is currently a post-doctoral fellow performing regenerative medicine research, specifically studying the role of exosomes in treating cardiomyopathy. In addition to his basic science research, he is also involved in human clinical trials investigating the role of stem cells in treating various forms of cardiomyopathy. -
Disha Sharma
Postdoctoral Scholar, Cardiovascular Medicine
BioI am a computational biologist with more than 12 years of extensive experience aiming to pursue career in developing translational medicine- and healthcare-oriented solutions. I have Ph.D. in bioinformatics with technical expertise for next-generation sequencing assays, genome-wide association studies, bulk and single-cell multi-omics analysis, R, python, shell Scripting, cloud computing, Data structure and algorithms, as well as machine and deep learning algorithms. I have solid background in genomics, transcriptomics, epigenomics and metagenomics. I have worked with both complex and rare genetic disorders performing data analysis, data interpretation, data curation with clinical data and databases.
I am presently a postdoctoral fellow at Stanford University for 4 years now where my main focus is to understand the genetic risks of cardiometabolic diseases using GWAS, integrating modalities including single-cell multiomics, CRISPR perturbation datasets. I am working on building machine learning models and use statistical genetics tools using large biobanks including UKBiobank, AllofUS and MVP. -
Laurens van de Wiel
Postdoctoral Scholar, Cardiovascular Medicine
BioLaurens van de Wiel is Dutch scientist from Berghem, The Netherlands. Laurens spent his undergrad in Software Development (BSc, Avans Hogeschool ‘s-Hertogenbosch) and Computing Science (MSc, Radboud University Nijmegen). Laurens continued his career at a start-up, where he created large-scale, real-time analytical software. Laurens continued on his academic trajectory at the Radboudumc in Nijmegen, where he started his PhD in bioinformatics.
During his PhD, Laurens integrated genetic data with protein 3D structures and protein domains. He utilized the skills he obtained before setting out on his academic trajectory; building large-scale, robust, reliable software. Exemplified by the MetaDome Web server (https://stuart.radboudumc.nl/metadome/). During his PhD, he developed novel methodologies for the interpretation of genetic variants of unknown clinical significance and, by integrating structural and evolutionary biology with genomics, Laurens identified 36 novel disease-gene associations for developmental disorders. These discoveries enabled diagnosis for over 500 families worldwide.
Laurens’ areas of expertise are (bioinformatic) software development, data integration of genetic variation with other omics, and his research aims are:
1.) Lessons long-learned in computer science aid computational biology
2.) Multi-omic data integration allows the impact measurement of genetic variation
3.) Diagnosing undiagnosed disorders will uncover novel insights into biology.
4.) International and multidisciplinary collaborations are key in diagnosing rare disorders.
At Stanford University, under guidance of Dr. Matthew Wheeler, he is conducting his postdoctoral studies in line with his research aims.
