Stanford University
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Aleesha Jethwa
Postdoctoral Scholar, Anesthesiology, Perioperative and Pain Medicine
BioDr Jethwa is a postdoctoral fellow working in Dr Sultan's lab, within the Obstetric Anesthesiology Department. She is funded by the R90 HEAL/Pain Cohort grant. Her research focuses on the peripartum period and how targeted interventions can alter recovery trajectories.
Dr Jethwa previously worked as a resident anesthesiologist in the UK for 7 years including rotations in Internal Medicine, Obstetrics, and Pain Medicine and completed a Masters in Education at the University of Pennsylvania focused on medical education. -
Rathinaraja Jeyaraj
Postdoctoral Scholar, Pathology
BioI work at the intersection of AI, multimodal learning, and large-scale image analytics, with a strong focus on computational pathology and foundation models for healthcare. My current research interests include LLMs, VLMs, multimodal reasoning, whole-slide image analysis, retrieval-augmented generation (RAG), and trustworthy AI for medical decision support.
I develop scalable deep learning systems spanning WSI preprocessing, multiple instance learning, segmentation, survival prediction, and multimodal image-text modeling. My work also involves attention interpretability, contrastive learning, pathology foundation model adaptation, and large-scale AI pipelines. Beyond healthcare AI, I have experience in time-series forecasting, distributed computing, cloud infrastructure, and real-time computer vision systems for industrial and smart-city applications.
I am particularly interested in building reliable, interpretable, and clinically meaningful AI systems that bridge computer vision, multimodal learning, and large-scale reasoning. -
Hanlee P. Ji
Professor of Medicine (Oncology) and, by courtesy of Electrical Engineering
Current Research and Scholarly InterestsCancer genomics and genetics, translational applications of next generation sequencing technologies, development of molecular signatures as prognostic and predictive biomarkers in oncology, primary genomic and proteomic technology development, cancer rearrangements, genome sequencing, big data analysis