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Thomas Killestein

Hei!

If you've somehow stumbled across this old page, I am now based in Finland, as a postdoctoral researcher at the University of Turku in the transients group. You can get in touch via my new email address, thomas.killestein@utu.fi. Up to date contact details are on my website below.

About me

I am a PhD candidate and Research Assistant in the Astronomy and Astrophysics group at the University of Warwick. My supervisors are Danny SteeghsLink opens in a new window and Joseph Lyman, and I work as part of the GOTOLink opens in a new window team, searching for optical counterparts to gravitational wave-driven merger events. A key focus of my work is developing high performance deep learning classification algorithms for finding transient candidates in GOTO data, and leveraging the GOTO discovery stream to find and characterise fast and faint astrophysical transients.

I also have a growing interest in supernovae science, with a particular focus on how they can be used to probe the final stages of massive star evolution.

My personal website: https://tkilleste.in


First-author publications:

Precision Ephemerides for Gravitational-wave Searches - IV. Corrected and refined ephemeris for Scorpius X-1 (Killestein et al., 2023 -- published in MNRAS)

Transient-optimised real-bogus classification with Bayesian Convolutional Neural Networks -- sifting the GOTO candidate streamLink opens in a new window (Killestein et al., 2021 -- published in MNRAS)

For a complete record of all papers I've contributed to, please see this curated ADSLink opens in a new window library.

Conference talks/posters/duties:

NAM 2023 Outreach session [contributed talk]

NAM 2023 Gravitational Waves key session [contributed talk]

NAM 2023 Explosive Transients session [contributed talk]

ICG Transients Seminar [invited talk]

University of Turku Astronomy Seminar [invited talk]

Convenor of NAM2022 session Machine Learning in Modern Astronomy: Learning and Interpreting the Data Driven UniverseLink opens in a new window

NAM 2022 Massive Stars session [talk]

NAM2021 AstroML session [talk]

NAM2021 Transients Diversity session [talk]

RAS SDM Machine Learning and Artificial Intelligence Applied to Astronomy 2 [talk]

Statistical Challenges in Modern Astronomy VII [poster]

LSST:UK All-Hands Meeting [poster]

Peer reviewer for A&A (1), RASTI (1)


Research interests:

  • Detection and characterisation of astrophysical transients
  • Deep learning, Bayesian classification, contextual machine learning
  • Data-mining of large scale astronomical surveys
  • Reproducible science, and open-source software development

Alongside my work with GOTO, I am also a member of the ENGRAVE and ePESSTO+ collaborations


Teaching and Outreach:

I was a problems class tutor for the first year modules PX145, PX148, and PX120 for 2 years, delivering a weekly problems class based on the course material and providing marking and support for the assessed problems sheets.

I have a lot of experience with science communication and am always keen to give outreach talks to schools and astronomy societies, on a variety of topics -- previously I've done talks on the solar system, exoplanets, asteroids, and astrophotography. Please contact me via email for more information!

I am technical lead on the Kilonova Seekers citizen science project, developing real-time infrastructure for citizen science.

Picture of Thomas Killestein (2021)

Write to:

Thomas Killestein,
Department of Physics,
University of Warwick,
Coventry CV4 7AL
UK
 

Contact details:

Email: t dot killestein at warwick dot ac dot uk
Office: A1.23 (Millburn House)