School of Medicine


Showing 81-100 of 199 Results

  • Izabela Kowalczyk

    Izabela Kowalczyk

    Postdoctoral Scholar, Developmental Biology

    BioDr. Izabela Kowalczyk is a postdoctoral fellow in the laboratory of Dr. Sarah Bowling, Department of Developmental Biology. She is studying embryonic development, with a focus on heart valve formation and the influence of the maternal environment on this process. Dr. Kowalczyk completed her Ph.D. at the Max-Delbrück-Center for Molecular Medicine in Berlin, under the supervision of Dr. Annette Hammes, where she investigated cell and tissue morphogenesis during early forebrain development. Her work identified novel components of Sonic Hedgehog (SHH) signaling and primary cilia biology, providing new insights into the variable penetrance of holoprosencephaly in mouse models.

  • Manoj Kumar

    Manoj Kumar

    Postdoctoral Scholar, Radiology

    Current Research and Scholarly InterestsI work on imaging-guided therapy using PET and MR imaging approaches. My academic training and background is in molecular imaging. During my doctoral training, I developed and validated a PET imaging approach for evaluating endocrine therapy responses in advanced breast cancer. My current research focuses on imaging tumor immune markers and responses to cancer immunotherapy. The goal is to develop new imaging toolboxes to monitor and guide treatment. Specifically, I employ antibodies, nanoparticles, and reporter genes for imaging and combinations of therapies to modulate and restore the body's suppressed immune functions against cancer cells. This is being done in collaboration with teams of researchers in early clinical development and teams in clinical practice.

  • Linda (Yu-Ling) Lan

    Linda (Yu-Ling) Lan

    Postdoctoral Scholar, Genetics

    BioLinda Lan, DVM, PhD is a postdoctoral fellow in the Snyder Lab. Her research focuses on understanding long-term illness post-acute infections by using a combination of different types of data (multi-omics) and wearable technologies. Currently, Linda is working on three projects.

    The first project involves studying the shared mechanisms of long COVID, ME/CFS, and PTLDS using smartwatches and micro-sampling. The second project involves examining the role of autoantibodies in long COVID patients and COVID vaccine side effects. The third project involves exploring the changes in the molecular and physiological responses of astronauts during short space flights using multi-omics and wearable devices.

    Linda previously conducted her PhD research at the University of Chicago, where she studied memory B cell responses to a chimeric-based universal influenza virus vaccine candidate. In her leisure time, she enjoys running, hiking, and listening to audiobooks.

  • Matthew Landry

    Matthew Landry

    Member, Maternal & Child Health Research Institute (MCHRI)

    BioCurrent research focuses on identifying the optimal diet (or diets) for chronic disease prevention and addressing the challenges of designing, implementing and reporting clinical trials that test dietary patterns. Particularly interested behavioral interventions that promote plant-forward and plant-based diets. Passionate advocator for policies that address nutrition-related health inequalities particularly in low resource settings and/or with communities experiencing health inequalities related to food insecurity and structural disparities.

    Assistant Professor of Population Health and Disease Prevention at University of California, Irvine (effective July 1, 2023)

  • Jeehee Lee

    Jeehee Lee

    Postdoctoral Scholar, Orthopedic Surgery

    BioDr. Lee is a dedicated researcher in the field of biomedical engineering, driven by a strong desire to help individuals suffering from illnesses. With a particular interest in disease treatment and regeneration, she embarked on her journey in this field. During her doctoral studies, Dr. Lee focused on developing functional biomaterials by leveraging chemical bonding at interfaces. Her expertise in this area led her to successfully create functional medical devices. Currently, as a postdoctoral researcher at Stanford University, Dr. Lee is actively involved in drug screening using a bone-mimicking 3D in vitro cancer model that utilizes biomaterials. Her research is centered around the utilization of biomaterials to develop innovative approaches for tuning the communication between cells and biomaterials. By advancing in the field of biomaterials, Dr. Lee aims to facilitate a better understanding of cell-biomaterial interactions, with the ultimate goal of improving healthcare outcomes. With her passion for cutting-edge research and her commitment to the development of biomaterials, Dr. Lee is dedicated to making significant contributions to the field and shaping the future of healthcare.

  • Yunkyeong Lee

    Yunkyeong Lee

    Postdoctoral Scholar, Endocrinology and Metabolism

    BioYun is a postdoctoral research scholar in the Translational Genomics of Diabetes Laboratory under the mentorship of Dr. Anna Gloyn. Since joining the lab in August 2022, she has been investigating type 2 diabetes (T2D) susceptible genes and their molecular mechanisms in pancreatic β-cell dysfunction and the development of T2D. Her primary focus is on how T2D effector transcripts alter autophagy/mitophagy pathways in human pancreatic β-cells, contributing to β-cell failure, mitochondrial dysfunction, and T2D pathology. She also investigated the impact of genetic mutations underlying neonatal diabetes using CRISPR HDR knockin genome editing in human induced pluripotent stem cell (hiPSC) models and their derivatives.

    During her PhD, she explored the role of an epigenetic regulator and its molecular machinery in the pathogenesis of non-alcoholic fatty liver disease (NAFLD), now termed metabolic dysfunction-associated steatotic liver disease (MASLD). In parallel, she studied the interplay between endoplasmic reticulum (ER) stress-mediated unfolded protein response (UPR) signalling and autophagy, and examined how these processes are modulated by bioactive plant extracts in various cellular contexts.

    She is particularly interested in exploring inter-organ communication, such as pancreas-liver-heart crosstalk, and how these interactions influence systemic metabolism and contribute to the onset and progression of T2D, along with its complications. Her long-term research goal is to advance our understanding of the cellular and molecular mechanisms driving T2D and to identify novel therapeutic targets and strategies.

  • Lili Liu

    Lili Liu

    Postdoctoral Scholar, Epidemiology

    BioLili (Larry) Liu, PhD, is a postdoctoral fellow in the Department of Epidemiology & Population Health at Stanford University. As an integrative epidemiologist, Dr. Liu unifies molecular biomarkers, large-scale population cohorts, and real-world health data into coherent, hypothesis-driven research with a sustained focus on how early-life exposures, genetic variation, lifestyle, and pharmacological factors shape inflammation, biological aging, and chronic disease risk across the life course. Trained in cancer genetic and nutrition epidemiology with complementary expertise in pharmacoepidemiology, his doctoral research at Vanderbilt University included a multi-ancestry GWAS of urinary prostaglandin E2 metabolite (PGE-M), development of PGE-M–derived dietary and lifestyle scores via elastic net with extensive bootstrapping, and Mendelian randomization analyses linking PGE-M to colorectal cancer across ancestries. At Stanford, Dr. Liu extends his research to maternal–fetal and placental epidemiology, building nationwide claims-based pregnancy cohorts (e.g., MarketScan) to examine gestational diabetes and downstream liver disease risk, and creating mother–infant pair cohort to investigate systemic antibiotic exposure in relation to subsequent inflammatory bowel disease and celiac disease. Parallel collaborations focus on extracellular vesicles and angiogenic signaling in placental health. Methodologically, Dr. Liu works at the interface of causal inference, pharmacoepidemiology, and machine learning with reproducible data engineering (R/Python, SQL, HPC), with the overarching goal of translating mechanistic insights into actionable biomarkers and risk tools for chronic disease prevention in diverse populations.