The Data Science Core was established through a Data Science to Promote Precision Medicine grant funded through the Wisconsin Partnership Program (WPP). The Data Science Core provides essential data science and omics support and training for SMPH researchers, faculty, and students, empowering them with the tools to drive impactful discoveries.
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Motivation
Today’s clinical researchers are poised to make breakthrough discoveries. However, turning complex health data into medical advances presents significant challenges for even the most brilliant research teams.
- The Expertise Gap: Researchers are experts in their domain, but applying specialized data science and artificial intelligence requires dedicated time, tools, and expertise that are often outside their primary focus.
- Disconnected Data: Powerful insights remain locked in separate, unlinked datasets, from clinical notes and medical images to omics data.
- The Opportunity: By centralizing these diverse datasets and providing expert analytical support, the Data Science Core can bridge this gap and accelerate the pace of discovery.
Services
- Collaborative data science support for precision medicine research projects at the University of Wisconsin.
- Creation of ready-to-use, linked datasets within an accessible analysis environment.
- Training for researchers on the effective use of large-scale biomedical data.
Meet the Team
Jomol Mathew
Co-Principal Investigator
jomol.mathew@wisc.edu
Dustin Deming
Co-Principal Investigator ddeming@medicine.wisc.edu
Amitha Domalpally
Co-Principal Investigator domalpally@wisc.edu
Joel Swenson, PhD – Data Science Team Lead
jmswenson@wisc.edu
Joel has been leading data science teams for almost a decade and loves to help other unlock insights in their data. He has a broad set of experiences from analyzing ‘omics data to classic machine learning to building a multi-modal RAG systems. Funded through WPP.
Yuetiva Robles, PhD – Research Data Scientistyrobles@wisc.edu
With over 12 years of experience in academic biomedical research, Yuetiva specializes in multi-omics data management and analysis. A skilled collaborator on multidisciplinary teams, she leverages her background in genetics, molecular biology, and neuroscience to translate complex data into scientifically relevant insights for investigators.
Michelle Stephens, MS – Research Data Scientist
mdstephens@wisc.edu
Michelle is a data scientist focused on bridging the gap between laboratory genomics and computational analysis. With a background in cancer diagnostic development and computer science, she is driven to support precision medicine by developing robust data pipelines. Funded through WPP.
Jaehwan Han, MS – Research Data Scientist
jhan58@wisc.edu
Jaehwan is a research data scientist specializing in machine learning, deep learning, and NLP for public health and EHR data. With a background in statistics and epidemiology, he develops models and analytical pipelines that transform complex healthcare data into actionable insights to support population health research and predictive analytics. Funded through WPP.
Mahmudur Rahman, PhD – Research Data Scientist
Mahmudur specializes in multimodal data science for clinical imaging and electronic health records. As a collaborative researcher across multidisciplinary teams, he leverages expertise in computer vision, machine learning, large language models, natural language processing, and clinical data to translate complex datasets into actionable insights that support precision medicine and patient care. Funded through WPP.
Molly Moran, MS – Research Data Scientist
Molly is a data scientist hired through the Research, Innovation and Scholarly Excellence (RISE) Initiative, specializing in NLP methods for EHR data. She utilizes her background in formal and computational linguistics to develop workflows that extract precise clinical insights from unstructured healthcare text. With extensive experience in the medical data space, she is focused on improving the accuracy of data-driven findings to support clinical research. Funded through RISE-AI initiative.
Lijin Gopi – Researcher IILijin Gopi focuses on data-driven analysis of multi-omics and clinical datasets, supporting large-scale research initiatives. Working closely with interdisciplinary teams, he applies expertise in bioinformatics, computational biology, and advanced analytics to interpret complex biological data and generate meaningful insights that advance scientific discovery.
Funded by
Sahar Zafari, PhD – Research Data Scientist
Sahar has a extensive background in medical imaging and deep learning, with experience spanning academia and industry. She has worked across CT, MRI, and ultrasound, leading projects in image segmentation, classification, and disease identification, and collaborating closely with clinicians in regulated, FDA-facing environments. Her work bridges research and production, with a focus on applying machine learning to real-world clinical problems. Funded through WPP.
Funding