Dr. Chang is a mathematical and statistical scientist with a strong focus on both developing and applying advanced computational and mathematical methods to solve complex problems in healthcare, neuroscience, and theoretical
biophysics. He earned his Ph.D. in Biomathematics from the University of California, Los Angeles (UCLA), where he developed mathematical models for understanding brain pathologies and utilizing images to inform models. His academic
journey also includes an M.S. in Statistics from UCLA, where he analyzed ambulance response performance, and a B.S. in Pure Mathematics, complemented by pre-medical and physical science coursework. Dr. Chang’s, interdisciplinary
background has enabled him to bridge the gap between mathematics, biology, and healthcare, making significant contributions to fields such as machine learning, Bayesian statistics, and biomedical informatics. His work has resulted in
numerous peer-reviewed publications in top-tier journals and conferences, such as Brain, Biophysical Journal, PNAS, AISTATS, ICLR, and NeurIPS, and MLHC, where he has explored topics like image segmentation, matrix factorization,
mathematical underpinnings of deep learning, Bayesian inference, and medical claims modeling.I’m leading experts in disciplines ranging from data science and neural networks to low-level devices, software engineering, and architecture.
Throughout his career, Dr. Chang has held several prestigious positions, including roles at the National Institutes of Health (NIH). At the NIH, he worked on reducing the USA disability adjudication backlog, disability assessments, calcium
dynamics in phases of brain pathophysiology, and interpretable machine learning solutions for healthcare. Previously, Dr. Chang also served as an NSF Postdoctoral Fellow at the Mathematical Biosciences Institute at Ohio State University,
where he conducted research on mathematical modeling of biological systems, including developmental biology and nucleation/aggregation phenomena in biology.
As the founder and principal investigator of Mederrata Research and Sound Prediction Inc, he has led interdisciplinary teams of data scientists, clinicians, and developers in healthcare innovation challenges. His teams earned recognition
as a finalist in the inaugural CMS AI Health Innovations Challenge.
In addition to his research, Joshua is passionate about teaching and mentorship. He has designed and taught courses in linear algebra and calculus for post-baccalaureate students at the NIH, fostering a diverse and inclusive learning
environment.Joshua’s dedication to advancing mathematical and computational methods in biology and healthcare, combined with his commitment to education and mentorship, positions him as a leader in the field of mathematical and
statistical biology
Want to learn more, contact us
to see how we can help
By subscribing you agree with our
© 2025 DeepimpactAI. All right reserved. Powered by Esshva