Seifollah Gholampour
Senior Data Scientist Iii @Margaret Hackett Family Program In Cns Anomaly Research
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WORK HISTORY
Senior Data Scientist Iii @Margaret Hackett Family Program In Cns Anomaly Research
Chicago, IL, US
EDUCATION
University of Chicago
Postdoctoral Fellow, Biomedical/Medical Engineering, Neuroscience
Azad University, Science and Research Branch
MSc in Biomedical Engineering
Azad University, Science and Research Branch
PhD in Biomedical Engineering
ABOUT SEIFOLLAH GHOLAMPOUR
As a Senior Data Analyst at the University of Chicago Medicine, I bring over 17 years of experience at the intersection of healthcare research and industry innovation. My expertise lies in leveraging applied artificial intelligence (AI) and advanced statistical analytics to develop innovative solutions for diagnosing, treating, and managing complex medical conditions. By integrating cutting-edge techniques—including predictive modeling, machine/deep survival learning, natural language processing (NLP), and morphometric image processing—I aim to advance precision medicine and transform clinical practices in neurosurgery and neurology. My work also extends to computational biology and biomedical simulations, where I develop tools to optimize surgical planning and optimize therapeutic strategies for complex neurological conditions. Throughout my career, I’ve led cross-functional initiatives that bridge academia and industry by translating real-world clinical challenges into actionable AI projects. By fostering collaborations between researchers, clinicians, and technologists, I accelerate the translation of cutting-edge research into tools that measurably improve patient outcomes, operational efficiency, and hospital performance. In addition to my technical work, I am deeply committed to cultivating the next generation of scientific leaders. I’ve advised 15+ PhD and MSc candidates and authored 60+ peer-reviewed publications, many in high-impact journals, to share insights that push the boundaries of medical AI, data science and computer simulation in biology. My teaching philosophy centers on empowering students to merge analytical rigor with translational thinking, ensuring their work addresses real-world healthcare challenges. Driven by a mission to improve patient care, I thrive in dynamic, interdisciplinary environments where collaboration and innovation converge. I welcome partnerships with clinicians, healthcare stakeholders, researchers, and organizations passionate about harnessing AI to reimagine the future of healthcare.
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