School of Medicine
Showing 1-50 of 56 Results
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Jonas Cerneckis
Postdoctoral Scholar, Cardiovascular Institute
BioI am a postdoctoral scholar at the Stanford Cardiovascular Institute working at the intersection of cardiovascular biology, neuroscience, and regenerative medicine. My research focuses on developing and applying new approach methodologies (NAMs), including human induced pluripotent stem cell-derived models, organoids, and computational approaches, to investigate disease mechanisms and identify opportunities for therapeutic development. I completed my PhD at the Irell & Manella Graduate School of Biological Sciences at City of Hope, where I studied Alzheimer’s disease using human stem cell-based models and machine learning.
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Souradeep Dey
Postdoctoral Scholar, Cardiovascular Institute
BioDr. Souradeep Dey is a postdoctoral scholar at the Stanford Cardiovascular Institute, specializing in tissue engineering, regenerative medicine, organ-on-chip technologies, 3D bioprinting and stem cells. Dr. Dey earned his Ph.D. in Nanotechnology from the Indian Institute of Technology Guwahati, India, where his doctoral research focused on developing clinically relevant 3D printed in vitro microphysiological models for disease modeling and drug screening applications.
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Ramzi Emanuel Dudum
Member (Postdoc), Cardiovascular Institute
BioDr. Dudum is a cardiologist and population health expert working to develop novel risk prediction methods and implementation strategies to create practices and systems that allow for reductions in cardiovascular disease. He completed a Masters in Public Health at Johns Hopkins concentrating in epidemiology and biostatistics and a Doctorate of Medicine at George Washington University.
He completed internal medicine residency training as part of the Osler Medical Service, where he worked under the mentorship of Drs. Roger Blumenthal and Michael Blaha to study improving cardiovascular risk prediction and coronary artery calcium. Given his focus on population health and implementation science, he also helped launch and refine risk adjustment tools and implemented guideline-directed medical care pathways. During his time there, he was recognized for his clinical acumen and dedication to patient care.
He came to Stanford for his cardiovascular medicine fellowship and continued research in coronary artery calcium under the mentorship of Drs. David Maron and Fatima Rodriguez while also conducting cardiovascular health implementation science work under the mentorship of Dr. Steve Asch. He serves as the co-investigator of a prospective randomized trial testing the effects of notification of incidental coronary artery calcium on statin initiation rates among those with and without cardiovascular disease (NCT 05588895). He has worked with hospital leaders to implement digital health and artificial intelligence tools, creating the infrastructure for the prospective use of AI-algorithms on radiology studies. As a preventive cardiologist and population health expert, he leads efforts in the preventive cardiology section related to improving cardiovascular health. -
Hiroyuki Inoue
Postdoctoral Scholar, Cardiovascular Institute
BioPhysician-scientist and board-certified cardiologist with expertise in cardiovascular disease, gene therapy, iPSC disease modeling, genome editing, high-throughput screening, and computational approaches for functional genomics and phenotypic data analysis.
Performed 400+ percutaneous coronary interventions (PCI), catheter ablations, and cardiac device implantations as primary operator, and currently conduct translational cardiovascular research at Stanford. -
Nerea Jimenez Tellez
Postdoctoral Scholar, Cardiovascular Institute
BioNerea is a Postdoctoral Scholar at Dr. Joseph Wu's lab. She earned her Bachelor's degree in Biochemistry at Universidad Complutense de Madrid (Spain). She was in an exchange program at the University of Saskatchewan (Canada) where she completed her Honours Thesis project on the Regulation of the Metastasis Suppressor Protein CREB3L1 in Dr. Deborah H Anderson's lab. She received her Masters' degree at Universidad de Alcalá (Spain) working at Dr. Isabel Liste Noya's lab on The role of p27Kip1 in the pluripotency and differentiation of dopaminergic neurons. She obtained her Ph.D. in Dr. Naweed Syed's lab studying the Cellular and molecular mechanisms underlying anesthetic-induced cytotoxicity, and their impact on learning and memory. She has received an ATRAC postdoctoral fellowship (Aug 2022 - Aug 2023), an AHA postdoctoral fellowship (Apr 2023 - Sept 2024) and currently holds a TRDRP Postdoctoral Fellowship (Jul 2024 - Jun 2027) titled "Using a human in vitro platform to study the effects of cannabinoids on the cardiovascular system" .
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Jiawei Li
Postdoctoral Scholar, Cardiovascular Institute
BioMy research interests include organoids, engineering, and AI.
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Thulaj Dattatraya Meharwade
Postdoctoral Scholar, Cardiovascular Institute
BioDr. Thulaj Meharwade is a postdoctoral fellow at the Stanford Cardiovascular Institute with research interests in Inflammaging, disease modeling, cellular heterogeneity and drug discovery. Dr. Meharwade received his PhD in Biochemistry from the University of Montreal, after conducting thesis work on signalling and transcriptional mechanisms regulating cell fate heterogeneity and totipotent stem cells.
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Debarun Patra
Postdoctoral Scholar, Cardiovascular Institute
BioDebarun Patra is a postdoctoral researcher at Stanford Medicine, with a background in inflammation research. His research focuses on metabolic disease modeling and identifying novel therapeutic targets. His current work integrates inflammatory and metabolic diseases (IBD, MASH, and diabetes), using patient-derived iPS cells and primary cells, and employs advanced multi-omics.
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Mojtaba Sedigh Fazli
Visiting Instructor/Lecturer, Cardiovascular Institute
Postdoctoral Scholar, Cardiovascular InstituteBioDr. Mojtaba Fazli is a leading artificial intelligence scientist and Lecturer at the Stanford Cardiovascular Institute and Stanford School of Medicine. His research connects machine learning, biomedical imaging, and cardiovascular physiology to address a central challenge in clinical AI: translating complex biomedical data into interpretable insights that can support better clinical decisions.
Working under the mentorship of François Haddad and Suzanne Tamang, Dr. Fazli develops AI approaches that integrate electrocardiography, echocardiography, invasive hemodynamic measurements, and clinical data. His current research spans pulmonary hypertension, right-heart function, and the estimation of cardiovascular pressures and function from noninvasive measurements. A defining focus of his work is explainability—understanding not only what a model predicts, but also how its predictions relate to clinically meaningful physiological patterns. Through this work, he investigates how AI can complement established cardiovascular assessment and support more informative, accessible approaches to disease evaluation.
Before his current appointment, Dr. Fazli held successive postdoctoral positions in Stanford’s Division of Immunology and Rheumatology and at the Cardiovascular Institute. Under the supervision of Suzanne Tamang and Rob Fairchild, his rheumatology research focused on AI-enabled ultrasound analysis, rheumatoid arthritis assessment, and the integration of multimodal clinical data. This experience helped shape his broader research approach: connecting imaging, quantitative measurements, and clinical context to address questions that matter in patient care.
His background spans academic medicine and pharmaceutical research, including postdoctoral training and senior research experience at the Harvard Ophthalmology Artificial Intelligence Lab and Harvard AI and Robotics Lab. He also served as a Senior Open Innovation Scholar and Gates Fundation Fellow at the Novartis Institutes for BioMedical Research, applying computational methods to biomedical research and drug discovery. Across these settings, his work has encompassed computer vision, 2D and 3D biomedical image analysis, computational disease modeling, and AI-driven analysis of complex biological data.
Dr. Fazli’s broader research interests include multimodal learning, computer vision, agentic AI, generative AI, and large language models for medical data analysis, integration of clinical knowledge, and clinical decision support. Across these areas, he emphasizes rigorous evaluation, transparent modeling, and close collaboration between computational scientists and clinicians.
He holds a PhD in Computer Science, with a minor in Mathematics, from the University of Georgia, a Doctorate in Business Administration, and master’s degrees in Economics and Management and in Artificial Intelligence and Robotics. This interdisciplinary foundation informs his approach to developing AI that is technically rigorous, clinically grounded, and responsive to the practical challenges of healthcare. -
Han Sun
Postdoctoral Scholar, Genetics
Biostatistician 2, Pediatrics - EndocrinologyBioHan had been a postdoc with Dr. Steinmetz at the genetics department for five years, working on both cancers and heart diseases, trying to understand the mechanisms linking from variants to disease phenotypes. This led to a few very interesting findings of aberrant splicing regulation, such as splicing-mediated readthrough stabilization (SRS), one more mechanism for oncogene activation in multiple types of cancers, and tissue-specific splicing of a mitochondrial inner membrane protein, suggesting a molecular connection between deficiency in energy-supplying and dilated cardiomyopathy.
After being a senior computational biologist with Dr. Gloyn, who has been dedicated to the research of type 2 diabetes for decades, Han switched to the field of this multifactorial metabolic disease. It did take some courage to make such a switch at his post-postdoc stage, however, Han has a consistent interest in studying PG&E, which is not pacific gas and electric nearby, but the interaction between phenotype, genotype, and environment. With years of hands-on experience in statistical modeling and the analysis of next-generation sequencing and mass spectrometry data, in addition to a good understanding of disease genetics, cancer biology, and systems biology, Han is highly confident that he will enjoy the adventure and contribute to our understanding of diabetes.
