Postdoctoral Fellows and Visiting Scholars

Marina is a postdoctoral scientist in the Department of Cardiovascular Medicine at Stanford and conducts research in the Ashley Lab. She is also a NIH T32 fellow in Myocardial Biology.
Marina obtained her PhD in Biomedical Engineering from UC Davis in 2023 with a research focus on cardiovascular and cancer research (cardio-oncology). Her PhD research addressed the clinical need of cancer patients facing cardiovascular diseases after rigorous chemotherapy treatment. During her PhD, she discovered novel chemotherapy combinations for cancer cell growth inhibition. Additionally, she investigated the effects of the novel chemotherapy combinations on the cardiac EC-coupling system. For her postdoctoral work in the Ashley Lab, she conducts research on myocardial tissue slices, works with gene therapy, and has a collaboration with the BME Department on 3D bioprinting the heart.

Josh is a Canadian biomedical data scientist with experience in bioinformatics, data science, and immunology. After completing a BSc and a MSc in Experimental Medicine at McGill university (Montreal, Canada), he relocated to the Netherlands for his PhD at Radboud University. During his PhD, he analyzed complex immunological data (bulk and single-cell transcriptomics, high-dimensional cytometry, high-throughput proteomics) derived from human observational studies or interventional studies (vaccination and experimental human infection). This work uncovered molecular and cellular correlates of clinically important endpoints such as disease severity, symptom progression, and antibody responses. In 2022, Josh relocated to Stanford to join Brice Gaudilliere lab to develop and apply multi-omic data integration and machine learning techniques, establishing that early gestational immune dysregulation can predict preterm birth. Since 2024, in the Ashley lab, Josh is focused on the application of deep learning to analyze the genetics of cardiovascular disease.

Bruna is a postdoctoral scholar in Cardiovascular Medicine. She completed her Doctor of Medicine in 2018 from Ruprecht Karl Universitat Heidelberg. She is a cardiologist Department of Cardiology, Pneumology and Angiology, Heidelberg University Hospital, Germany.

Arash Keshavarzi, with a foundation in chemistry, molecular biology, and drug discovery from his bachelor’s and master’s studies in Biotechnology, further honed his expertise with a Ph.D. focused on the applications of Deep Learning for non-structural drug discovery, culminating in two significant patents. Now, as a postdoctoral scientist, Arash is at the forefront of integrating foundation models and large language models (LLMs) into genomics and proteomics. His research aims to demystify the variants of uncertain significance (VUS), striving to pioneer clearer insights in this intricate realm. Beyond his research, Arash is an avid traveler who cherishes moments with friends, hiking, biking, and exploring new horizons.

Dr. Hector Rodrigo Mendez is a Medical Geneticist from Argentina. Rodrigo completed a residency program in Medical Genetics at Centro Nacional de Genetica Medica – ANLIS (Buenos Aires, Argentina) and a Master’s program in Medical Molecular Biology at Buenos Aires University.
Rodrigo continued his scientific career at a German Genomic Start-up, working as a human geneticist and providing his experience in rare disorders, genomic data (WGS/WES/gene panels) analysis, variant interpretation, and its integration with a deep focus on genotype-phenotype correlation.
Rodrigo’s areas of expertise are rare disorders, NGS technology, Whole Genome Sequencing analysis, and ACMG interpretation guidelines, and his research aims are:
– Collection and analysis of clinical data through deep-learning phenotyping approaches.
– Multi-omic data integration to elucidate complex and rare genetic disorders.
– International collaborations to break down barriers to research participation amongst those who have been under-represented.

Samuel Montalvo is a Clinical Exercise Physiologist and Sports Biomechanist with a keen interest in human exercise and sports performance. Currently, he is serving as a Post-Doctoral Research Fellow under the Wu Tsai Human Performance Alliance at Stanford, supervised by Dr. Matthew Wheeler. His research interests revolve around understanding the biomechanical, molecular, and physiological mechanisms of human performance across diverse populations—ranging from clinical and sedentary individuals to athletes.

Jack is an Australian physician (MD, PhD) currently working as a Post-Doctoral Research Fellow at Stanford University. He is supervised by Professor Euan Ashley and is an active member of the Ashley Lab.

Jack’s fellowship concerns the diagnosis and risk prediction of cardiovascular disease. Jack employs a variety of statistical methods to assess new diagnostic technologies, such as smart phones and smart wearables, and my work also extends to computational cardiac genetics. The data sources he utilizes to conduct my research are numerous, but include large datasets such as the UK Biobank, as well as publicly available dataset (meta-analysis and meta-research). He also has previously used large electronic health records (>250 million EHRs).

Aside from his own research prioritizes (above), Jack also work on studies conducted collaboratively within the Ashley Lab, the Division of Cardiovascular Medicine. These studies broadly include digital health randomized controlled trials (RCTs) and meta-research (including statistical methods such as meta-analysis, meta-regression etc).

Jack previously completed a DPhil (PhD) in clinical epidemiology at the University of Oxford as a Clarendon Scholar. The title of his DPhil thesis was: “Biostatistical and meta-research approaches to assess diagnostic tests”. Jack’s published research is available at the google scholar page (https://scholar.google.co.uk/citations?user=n5l7tL8AAAAJ&hl=en) and some of his code is publicly available at his GitHub (https://github.com/jackosullivanoxford).

Beyond academic institutions, Jack consults to the World Health Organization (WHO); including on WHO guidelines, where he is currently the methodological chair for a WHO guideline concerning the early(ier) detection of disease in adults. Jack also work as an associate editor at one of the BMJ sub-journals: BMJ EBM. During my DPhil Jack worked clinically at Oxford University Hospitals (John Radcliffe Hospital) and intend to return to clinical practice as a Physician-Scientist at Stanford upon the completion of my research Fellowship.

You can follow Jack on twitter (https://twitter.com/DrJackOSullivan): where you will find him tweeting about statistics, surfing, cardiology, medicine, epidemiology, health policy, and, occasionally, politics.

Theresia is a Visiting Scholar in the Division of Cardiovascular Medicine. She obtained her MSc in Biochemistry/Molecular Biology at the University of Alaska Fairbanks, USA (2013), and her PhD in Basic Metabolic Research at the University of Copenhagen, Denmark (2018). Her overall research interest is to investigate how common genetic variation contributes to cardiometabolic disease and how lifestyle factors interact with a genetic predisposition to common disease traits. In the Hansen lab at the University of Copenhagen, she applied diverse statistical genetic analysis methods in European cohort studies to uncover genetic underpinnings of adiposity and metabolic disease-related traits, and to understand their complex relationship with lifestyle at the molecular level. She received funding from the Novo Nordisk Foundation and the Stanford Bio-X program to carry out a three year project at Stanford as part of the Knowles lab and the Ashley lab. During her three years, she focuses on combining a computational and experimental framework to identify novel genetic variants that are causally related to cardiometabolic disease, and to investigate their relationship to lifestyle factors. At the Ashley lab she is involved in the ELITE project that is seeking to discover genetic determinants of physical fitness in the world’s most elite endurance athletes. Her vision is to provide insights that will pave the way for personalized prevention and treatment, and for new drug targets.

Samiya is a postdoctoral scholar in the Ashley Lab, Stanford University School of Medicine. She obtained her Ph.D. (in 2019) at The Australian National University, Australia. She studied Electrical and Computer Science Engineering and is specialized in wearable technology and wireless body-centric networks. During her Ph.D., she performed extensive experimental analysis to optimize wireless communication performance between wearable sensors, with cross-layer techniques and predictive analytics, to build autonomous human-centered networks. In the Ashley Lab, she is working towards developing artificial intelligence based wearable system for monitoring cardiac arrhythmia. She is also researching on various machine learning and deep learning based prediction with wearable data analysis for healthcare applications that include physical activity recognition, sleep prediction, monitoring sleep disorders associated with cardiovascular health. Outside of work, she likes traveling, hiking, watching movies, and trying new recipes.

Qianru joined the Ashley lab as a postdoctoral scholar in the summer of 2019. Qianru obtained her Master’s degree (2014) and Ph.D. (2018) in Mechanical Engineering from MIT, where she innovates microfluidic technologies to measure biophysical properties of bacteria for applications in sustainable energy and synthetic biology. In her Ph.D. thesis project, she developed a novel microfluidic process to rapidly identify and sort electricity-producing bacteria for use in microbial fuel cells and bioremediation. Her microfluidic system noninvasively classified bacteria according to their cell surface polarizability, an inherent electrical property of microorganisms, which was found to be an indicator of cell extracellular electron transfer. Currently, she is interested in applying microfluidics-enabled phenotyping of single cardiomyocytes to efforts in understanding the pathogenesis of hypertrophic cardiomyopathy. Outside the lab, Qianru is a badminton player, and a big fan of comedy shows and detective films.

Laurens 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.

Yuta is a postdoctoral research fellow in Ashley lab. He graduated and received DVM from Tokyo University of Agriculture and Technology in 2013. At veterinary school, he investigated the valvular disease of dogs. After graduation, he focused on the inherited cardiac diseases, and conducted research on CALM gene mutation-related arrhythmias (Calmodulinopathy) using iPS cell model in Kyoto University where he obtained a PhD in 2017. His current research interests are pathophysiological mechanism and gene therapy approach for inherited cardiac diseases. Outside the lab, he enjoys watching baseball games, reading books, playing video games, and California life.