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Thomas Killestein is a Prize Fellow in the Astronomy and Astrophysics group at the University of Warwick. His research focuses on the applications of machine learning techniques in time-domain astronomy, where he applies advanced algorithms to analyze vast amounts of astronomical data. He is committed to advancing the field of astrophysics through innovative computational methods, contributing significantly to the understanding of transient astronomical phenomena. Thomas is actively involved in various research projects aimed at improving detection capabilities and understanding the dynamic sky. His work is essential for enhancing observational strategies and methodologies in the study of celestial events.
Includes General, Mechanical, Civil, Electrical, Biomedical, and Manufacturing Engineering. Most programs fall under English Band A.