Technische Universität München
Technische Universität München

Edoardo Mosca

M.Sc.

Room: FMI 01.05.057
E-Mail: edoardo.mosca(AT)tum.de
Phone: +49-89-289-18684
Address: TUM - Fakultät für Informatik, Boltzmannstr. 3, 85748 Garching

Personal Website

I exclusively supervise PhD Students. Please do not apply for Master/Bachelor theses or guided research, emails will be ignored.

Research Interests

I am a post-doc at TUM and I work in the field of eXplainable AI (XAI) for Machine Learning and Deep Learning with a strong focus on NLP. In other words, besides building accurate machine learning models, my goal is also to understand why those models make certain decisions. 

Here you can find my master thesis about XAI techniques applied in the field of Hate Speech Detection. There is also a blog post article, partially inspired by my thesis, that briefly discusses why XAI is so relevant in modern machine learning research and explores a possible definition of XAI (thanks to Cingis Alexander).

Teaching (Past)

Each semester, in collaboration with some of my colleagues, we offer advanced master-level practical courses for students motivated to get hands-on experience in XAI, NLP, and ML. In this courses you will team up with other participants and work on a concrete project that utilized or even tries to improve the current state of the art in the field. The projects last for the whole semester and will be under my close supervision. We will meet on a (bi-)weekly basis to discuss the current state and the next steps. At the end of the semester, you will be presenting your findings and results as well as delivering your code and a brief "paper-like" report.

Summer Semester:
Advanced Natural Language Processing (CIT4230002)
(5 ECTS) 

Winter Semester:
Master Lab Course - Explainable AI for Machine Learning (IN2016, IN4286)
(10 ECTS) 

Both Summer/Winter Semester:
Master Lab Course - Machine Learning for Natural Language Processing Applications (IN2016, IN4286) 
(10 ECTS) 

If you're interested, it is always a good idea to contact the advisor/manager of your study program. Ask them if the courses are recognized for your master degree.