School of Medicine
Showing 10,141-10,150 of 12,863 Results
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Mohammad Shahrokh Esfahani
Assistant Professor of Radiation Oncology (Radiation and Cancer Biology)
BioI lead a computational oncology laboratory that develops machine learning and statistical methods for high-dimensional genomics, with particular expertise in Bayesian and uncertainty-aware modeling to integrate prior biological knowledge with large-scale datasets.
Our research centers on liquid biopsy analytics—especially cell-free DNA (cfDNA)—to noninvasively quantify genetic and epigenetic states relevant to cancer detection, monitoring, and tumor evolution. We developed EPIC-seq, a fragmentomics-based method that uses cfDNA fragmentation patterns to infer regulatory activity and gene expression programs, providing a scalable framework for epigenetic profiling from blood.
A core methodological focus of the lab is enabling reliable inference in extremely low signal-to-noise settings that are typical of cfDNA and early-stage disease. We build robust, interpretable models and benchmarking frameworks that support clinical translation, with the long-term aim of democratizing access to sensitive, minimally invasive cancer diagnostics. -
Hormoz Shahrzad
Graduate, Medicine, Psychiatry and Behavioral Sciences
BioHormoz has worked on many topics in evolutionary computation, both in theory and practice. His master's thesis focused on BLADE, a method for automatically focusing evolutionary search on the most promising part of the genome, with the search distributed over multiple hosts. He is currently a PhD candidate at UT Austin, continuing his research at the Cognizant AI Lab (https://www.cognizant.com/us/en/ai-lab) and as a visiting student researcher at Stanford University, where he is working on his dissertation.
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Mohammed Abdul Saqhlain Shaik
Temp - Non-Exempt, Ophthalmology Research/Clinical Trials
BioSaqhlain is a Research Assistant at the Byers Eye Institute, where he applies his expertise in data science and statistical analysis to ophthalmic research. He holds a master’s degree in Statistics - Data Science from Cal State University East Bay and a bachelor’s degree in Computer Science from Hyderabad, India.
His work focuses on data analysis, management, and standardization of ophthalmic imaging data to support clinical research. He collaborates with researchers to design and execute data-driven projects, ensuring data quality control and validation. Additionally, he assists with data acquisition, statistical analysis, and streamlining research workflows to enhance efficiency in ophthalmology studies.
Saqhlain is particularly interested in leveraging data science to improve research methodologies and facilitate insights in medical imaging. -
Shailja
Postdoctoral Scholar, Radiological Sciences Laboratory
BioShailja is an engineer and computational scientist interested in the modeling of the human brain to study neurological diseases and guide neurosurgeries. As a Wu Tsai Neuroscience Institute’s postdoctoral fellow with Prof. Jennifer A. McNab and Prof. Josef Parvizi, she investigates tractography-based neurosurgical targeting. She is interested in mapping the whole brain structural connectivity network from diffusion MRI to functional connectivity in the human brain. Shailja received her PhD in Electrical and Computer Engineering from the University of California, Santa Barbara and BS from Electrical Engineering Department, Indian Institute of Technology, Kharagpur. Her doctoral research is on Reeb graphs for modeling white matter fibers in the human brain, which was awarded the Winifred and Louis Lancaster Best PhD Dissertation at UC Santa Barbara.
