MENTORS
(click on the mentor's name to view their profile and link to their lab)
Tarek Magdy Mohamed, PharmB, PhD
CPTR Sub-Project 1 Leader
iPSC and Cell Models Core Leader
Assistant Professor, Department of Pathology and Translational Pathobiology
Dr. Magdy is an expert in single nucleotide polymorphism analysis to uncover their role in regulating cell phenotype, focusing on the genomics of cardiometabolic disease using cell models derived from human iPSCs. In addition, he adopts state-of-the-art techniques, including somatic cell reprogramming into human iPSCs, multi-lineage iPSC differentiation, CRISPR/Cas9-mediated functional genomics methods, multi-omics approaches, and bioinformatics.
CPTR Sub-Project 2 Leader
Associate Professor, Department of Molecular and Cellular Physiology
Dr. Yurdagul has extensive expertise in studying polyamine metabolism, post-transcriptional regulatory mechanisms, hepatocyte function, and omics-based approaches over the past decade. He has led research that integrates molecular biology, advanced genetic models, and cutting-edge sequencing technologies to uncover critical pathways in cellular homeostasis.
CPTR Sub-Project 3 Leader
Assistant Professor, Department of Pathology and Translational Pathobiology
Employing advanced genetic models, omics platforms, and mechanistic assays, Dr. Dhanesha has uncovered metabolic triggers linking hepatocyte glycolysis to systemic coagulopathy. His recent work in hepatocyte biology explores liver-specific hypercoagulability and inflammation using in vitro hepatocyte cultures and transcriptomic approaches.
CPTR Co-Director
Senior Associate Dean of Basic and Translational Research and Associate Professor of Pathology and Translational Pathobiology
The long-term goal of my research is to elucidate metabolic and molecular mechanisms underlying cardiometabolic diseases to identify novel therapeutic targets. The focus of my laboratory is to shed light on yet undefined metabolic pathways that link metabolic dysfunction-associated steatotic liver disease (MASLD) to atherosclerotic cardiovascular disease (ASCVD). We employ a multidisciplinary approach that integrates newly developed animal models, patient samples from individuals with cardiometabolic diseases, and genome-wide association studies (GWAS), alongside a variety of advanced research tools, including transcriptomics, metabolomics, animal pathophysiology, and cellular and molecular biology.
CPTR Co-Director
Professor and Vice Chair, Department of Pathology and Translational Pathobiology; Director, Center for Cardiovascular Diseases and Sciences [CCDS]
Our lab investigates how Eph receptors and their ephrin ligands signal to regulate hepatocellular stress responses and lipid metabolism in metabolic dysfunction-associated steatotic liver disease and steatohepatitis. We use molecular, cellular, and transcriptomic approaches to define how Eph/ephrin pathways influence mitochondrial function, inflammatory activation, and transcriptional reprogramming in hepatocytes.
Metabolism and Machine Learning Core Leader
Associate Professor of Pharmacology, Toxicology and Neuroscience
Our research investigates molecular and cellular signaling in alcoholism and psychiatric disorders through brain-liver axis. We examine how genetic and metabolic factors shape alcohol addiction vulnerability and treatment outcomes. Focusing on alcohol-induced liver damage and its impact on brain metabolism, we integrate transcriptomics with mouse genetics, behavior neuroscience, and pharmacology to uncover mechanisms driving alcoholism.
Machine Learning and Data Harmonization sub- Core Leader
Assistant Professor of Internal Medicine, Director of Biostatistics and Computational Biology
Dr. Bhuiyan’s lab applies artificial intelligence (AI), machine learning, and mathematical modeling to investigate complex biological systems underlying cardiovascular, metabolic, and neurodegenerative diseases such as Alzheimer’s. Within the CPTR SUMMIT program, his group mentors students in projects that integrate multi-omics (transcriptomics, metabolomics), imaging, and clinical data to model disease mechanisms, identify biomarkers, and predict disease progression. The lab’s overarching goal is to develop data-driven, AI-enhanced approaches that transform the understanding and management of diverse human diseases through translational and precision medicine.