Data Science News
Exoplanet Validation with Machine Learning: 50 new validated Kepler planets
Dr Theo Damoulas (Department of Computer Science) along with Dr David Armstrong (Department of Physics) and Jevgenij Gamper (Department of Mathematics) have developed probabilistic machine learning algorithms that can separate out real planets from fake ones in the large samples of thousands of candidates found by telescope missions such as NASA’s Kepler and TESS. The results of which have led to fifty new confirmed planets, the first to be not only ranked but also probabilistically validated by machine learning.
The paper "Exoplanet Validation with Machine Learning: 50 new validated Kepler planets" has been accepted to the Monthly Notice of the Royal Astronomical Society, DOI: 10.1093/mnras/staa2498
Wearable IoT Electronic Nose for Urinary Incontinence Detection
Work performed by Computer Systems Engineering student Michael Shanta for his 3rd year project, supervised by Dr. Marina Cole and Dr. Siavash Esfahani in the School of Engineering, was written up in a paper that was recently accepted for presentation at the IEEE Sensors 2020 Conference.
For his 3rd year project Michael worked on developing machine learning techniques for an Electronic Nose in order to classify odours based on the sensor responses. The system aims to detect incontinence incidents, allowing alerts to be sent to relevant personnel from an IoT network via a cloud server.
WATE PGR commendation for Alexander Noll
We are very happy to report that Alexander Noll, PhD student at the department’s Institute for the Science of Cities, has been rewarded with the 2019/2020 Warwick Award for Teaching Excellence for Postgraduates who Teach. As a commendee, the recognition of his teaching comes in addition to a £200 teaching endowment. Alexander, who comes from an interdisciplinary academic background and has been teaching on several undergraduate modules of our department as well as the Department of Sociology, commented:
The thought that I was able to contribute positively to somebody’s learning and their time at Warwick in general sparks great joy. It is a great honour to be recognised for my tiny contribution to a community of teachers who work hard on creating a positive learning environment.
WATE seek to recognise outstanding teaching and support of learning across the University. Since 2003, the Awards have helped showcase innovation and commitment from across Warwick's teaching community. Nominations can be made by both students and staff and a panel of judges then creates a shortlist of up to ten nominees. Based on additional personal statements, 10 winners are selected from the shortlist, split into five awards and five commendations.