School of Medicine
Showing 11-20 of 195 Results
-
Cameron Scott Bader
Postdoctoral Scholar, Bone Marrow Transplantation
BioMy research is focused on using preclinical models to develop novel therapies which improve outcomes for patients receiving allogeneic hematopoietic stem cell transplantation. Currently, my work aims to establish strategies to reduce the risk of relapse after allogeneic hematopoietic stem cell transplantation without exacerbating graft-versus-host disease or interfering with donor stem cell engraftment.
-
Xiangqi Bai
Postdoctoral Scholar, Oncology
BioMy research is focused on computational and systems biology. My primary research interest lies in developing new computational algorithms and statistical methods for the analysis of complex data in biological systems, especially related to the large-scale single-cell RNA sequencing data. The specific topics I have examined include:
1. Integration of single-cell multi-omics datasets for tumor
2. Statistical test of cell developmental trajectories
3. Visualization and reconstruction of single-cell RNA sequencing data
4. Computational analysis of the bifurcating event revealed by dynamical network biomarker methods -
Vasiliki (Vicky) Bikia
Postdoctoral Scholar, Biomedical Informatics
BioDr. Vasiliki Bikia is a Fellow at the Institute for Human-Centered Artificial Intelligence and Postdoctoral Scholar at Stanford University, working with Prof. Roxana Daneshjou. She received her Advanced Diploma degree in Electrical and Computer Engineering from the Aristotle University of Thessaloniki (AUTH), Greece, in 2017, and her Ph.D. degree in Biomedical Engineering from the Swiss Federal Institute of Technology of Lausanne (EPFL), Switzerland, in 2021. Her Ph.D. research addressed the clinical need for providing non-invasive tools for cardiovascular monitoring leveraging machine learning and physics-based numerical modeling. In particular, she developed and tested novel healthcare algorithms for major biomarkers including central blood pressure, stroke volume, left ventricular elastance and arterial stiffness.
Her current work focuses on developing large multimodal models to enhance biomarker identification and predict patient outcomes. She leverages representation learning for both textual and visual medical data, creating models that are applied to downstream tasks, yielding more nuanced and precise clinical predictions. At Stanford, she has also contributed to the Stanford Spezi framework, designing and prototyping the Spezi Data Pipeline tool for enhanced digital health data accessibility and analysis workflows.
Her research interests include health algorithms, clinical and digital biomarkers, machine learning, non-invasive monitoring, and the application of large language models for personalized healthcare, predictive analytics, and enhancing patient-clinician interactions.
