Dan Wilkins
Contact Information
Research Assistant Professor
he/him
Areas of Expertise
- Black Holes
- Active Galactic Nuclei
- X-ray Binaries
- Neutron Stars
- Accretion Physics
- General Relativity
- X-ray Astronomy
- Astronomical Instrumentation
Education
- PhD, 2013, Astronomy, University of Cambridge
- BA (Hons), MSci, MA (Cantab), 2009, Natural Sciences (Experimental and Theoretical Physics), University of Cambridge
Dr Wilkins joined the Ohio State faculty in 2025 as Research Assistant Professor in Astronomy. His research focuses on how material spiraling into a supermassive black hole in the centre of a galaxy is able to release huge amounts of energy, powering some of the brightest objects we see in the Universe. Dr Wilkins' research bridges the divide between observational and theoretical studies of black holes, using state of the art space telescopes, developing novel data analysis techniques and designing computer simulations of how light travels around black holes. His research utilizes the X-rays that are emitted and measurements of how they reflect off of the material in its final moments before it falls in to create a 3D map of the extreme environment just outside the event horizon. He is interested in what happens to material and light just before it is lost into the black hole, how the corona that produces the radiation we see is powered, how black holes are able to launch jets at almost the speed of light, how supermassive black holes grow, and the profound effect they have on the formation of galaxies and structure in our Universe.
Dr Wilkins works with NASA, the European Space Agency (ESA) and the Japanese Aerospace Exploration Agency (JAXA) on the development of next-generation X-ray missions. He is a member of the science team for the JAXA-led XRISM X-ray observatory, a member of the ESA Athena Science Working Group and of the Wide Field Imager instrument team, and has played an active role in the development of NASA's probe-class X-ray mission concepts. He is also contributing to the development of next-generation, high-speed, low-noise X-ray imaging detectors that are based on CCD technology, and leading research into how we may augment next-generation detectors with artificial intelligence (AI) and machine learning (ML) algorithms to enhance their sensitivity.