TALES School II: Hands-on workshop on machine learning applications to astrophysics

Rationale

The second TALES training will be organized in a form of a Hackathon, offering real-world training in machine learning applications to astrophysics. This 3-day intensive data challenge/hackathon aims for the TALES's doctoral candidates (DCs) to develop advanced computational tools for analyzing AGN light curves and time-series in general. The objectives of the challenge may range from the selection/classification to characterization of AGNs using multi-wavelength time-series data. Datasets (observed/simulated light curves) and challenge requirements (e.g. anomaly detection, reconstruction of data, classification, etc.) will be designed by the external experts. The complexity of the tasks and requirements may have a great range of difficulties, in coordination with the TALES supervisors. The DCs will form 3-4 teams (team members randomly selected) and will be supported by the lecturers and supervisors throughout the work.

This event will combine the Smart Data Technologies-2 workshop and the Core Professional Skills-2: Oral & Written Communication Skills workshop, to make the most out of this in-person gathering of the whole DC group.

Preliminary Agenda

(The detailed Timetable will be updated soon)

Sun, 13 Sept — Arrival
Mon–Wed, 14–16 Sept (morning) — Hackathon (2.5 days)
Wed, 16 Sept (afternoon) – Thu, 17 Sept — Skills4Science workshop
Fri, 18 Sept (preferably afternoon) — Departure

Participants

Experts:  Paula Sanchez-Saez (ESO), Paolo Bonfini (University of Crete | IA-FORTH) 

Supervisors:  Dragana Ilić, Andjelka Kovačević, (TBA)

Students:

1. Nicolò Belgiovine
2. Natale De Bonis
3. Amie-Louise Doherty
4. Prathamesh Ingale
5. Marios Kouzis
6. Tianying Lian
7. V. Madurga Favieres
8. Valerio Pandolfi
9. Michail Polioudakis
10. Shashanth Sriramanathan
11. Erin Umuzigazuba

Additional attendees: TBA