معرفی
Victor Churchill is an Assistant Professor of Mathematics at Trinity College since 2023. He holds a Ph.D. and A.M. from Dartmouth College, an M.S. from New York University's Courant Institute, and a B.A. from Boston College. His research focuses on computational mathematics, scientific machine learning, and image reconstruction, particularly in Bayesian uncertainty quantification for synthetic aperture radar imaging and learning unknown dynamical systems using neural networks. He has held a postdoctoral position at The Ohio State University under Dr. Dongbin Xiu and previously worked at Dartmouth under Dr. Anne Gelb.
Research Highlights: His work includes deep learning of PDEs, ensemble prediction for robust neural network training, and chaotic system learning from partial observations. Recent contributions address coarse time-scale observations and uncertainty quantification in SAR imaging. He was awarded the SIAM Science Policy Fellowship (2023-2024) to engage with federal science policy advocacy.
Teaching: He teaches computational science courses at both undergraduate and graduate levels, integrating his research into lectures through case studies and data-driven examples. His pedagogical approach emphasizes applied computational mathematics and real-world problem-solving.
Affiliations: Previously affiliated with The Ohio State University as a Visiting Assistant Professor of Scientific Computation. Active in computational math communities, including SIAM policy engagement.
Personal Interests: An avid runner with marathon personal bests, he also enjoys bonsai cultivation, architectural design, and animal care. His unconventional hobbies include experimenting with hair color transformations.
