معرفی
Dr Dalia Chakrabarty is a Reader in Statistical Data Science at the Department of Mathematics, University of York. Previously, she held positions as Senior Lecturer at Newcastle University and Lecturer at Lancaster University. Her research focuses on probabilistic methods, Bayesian inference, and machine learning applications in fields such as medicine, astronomy, and materials science. She specializes in kernel methods, random graph analysis, and causal forecasting. Notable contributions include developing methodologies for uncertainty quantification and non-parametric learning.
Her academic career includes a Royal Society Dorothy Hodgkin Fellowship and supervision of students like Kane Warrior. Dr Chakrabarty's work bridges theoretical statistics and real-world challenges, with publications spanning journals like Plos One and Artificial Intelligence in Medicine. She also authored the textbook Supervised Learning: Mathematical Foundations & Real-world Applications (2024, CRC Press).
- Research Highlights:
- Inter-graph distance metrics for medical data analysis
- Bayesian state-space modeling of galactic dynamics
- High-dimensional data applications in oncology and materials science
- Collaborations: Maintains ties with Brunel Mathematics for PhD supervision and international research networks.
- Contact: Email dalia.chakrabarty@york.ac.uk, Tel: +44 (0)1904 32 1486
