Ritratto di fabio.galasso@uniroma1.it

News 25/07/2020: the websites for my next winter semester courses (AY 2020/2021) are online. Both courses would start on October 6th, 2020.
Find on the websites the link to the course mailing lists. Please join those mailing lists with your institutional email addresses.


Advanced Machine Learning (AML):


(note: the course has moved from the II to the I semester, 2nd year)


Fundamentals/Foundations of Data Science and Laboratory (FDS):



Thursdays at 13:00-15:00 (on request)

Prof. Fabio Galasso heads the Perception and Intelligence Lab (PINLab) at the Dept. of Computer Science, Sapienza University in Rome (Italy). Our group is interested in fundamental research and innovation transfer in computer vision and machine learning. Our specific research interests include distributed and multi-agent intelligent systems, perception (detection, recognition, re-identification, forecasting) and general intelligence (reasoning, meta-learning, domain adaptation), within sustainable (low-power-consumption and constrained-computational-resource sensors and devices) and interpretable (interpretable and verifiable AI) frameworks.

Previously, Fabio founded and directed the Computer Vision Department at OSRAM (Munich, Germany), an international team conducting R&D in artificial intelligence, computer vision and machine learning, in relation to smart lighting applications.
We made long-term strategic propositions and cared about the entire life cycle of ideas, from the creation of new value propositions to the implementation of prototypes and pilots. Pilot installations include large industrial partners such as Edeka. Innovation transfer successes include the VISN product, which was awarded the 2019 IoT/WT Innovation World Cup, the 2019 Digital Champions Award, and the 2018 Deutscher Digital Award.

Prior to OSRAM, he has conducted research on video analysis and segmentation, scene understanding and clustering at the University of Cambridge (UK) and at the Max Planck Institute for Informatics (Germany).
He received his Master's Degree cum laude from the RomaTre University (Italy) and his PhD from the University of Cambridge (UK), following research work on texture analysis and 3D reconstruction.
Before and after his Master's Degree, he gained experience as a Researcher in the Ericsson Laboratories and as a Project Engineer in Telecom Italia. In his career, he has been involved in consulting work relating to computer vision.

Fabio has recently coordinated a Marie Sk odowska-Curie Actions project (Horizon 2020) and was Principal-Co-Investigator in several German-funded projects, from the Ministry of Education and from the Ministry of Economics. He has served as area and industrial chair at international conferences, as reviewer for journals and conferences, and as co-chair of international workshops.

More information is available at: https://fgalasso.bitbucket.io/

Titolo Rivista Anno
Joint Detection and Tracking in videos with Identification Features IMAGE AND VISION COMPUTING 2020
Human-centric light sensing and estimation from RGBD images: the invisible light switch 2019
RGBD2lux: dense light intensity estimation with an RGBD sensor 2019
UA-DETRAC 2018: report of AVSS2018 IWT4S challenge on advanced traffic monitoring 2019
Adversarial network compression 2019
Forecasting People Trajectories and Head Poses by Jointly Reasoning on Tracklets and Vislets IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 2019
Query-guided end-to-end person search 2019
Knowledge Distillation for End-to-End Person Search 2019
MX-LSTM: mixing tracklets and vislets to jointly forecast trajectories and head poses 2018
'Seeing is believing': pedestrian trajectory forecasting using visual frustum of attention 2018
Tiny head pose classification by bodily cues 2018
UA-DETRAC 2017: report of AVSS2017 & IWT4S challenge on advanced traffic monitoring 2017
“Don’t turn off the lights”: modelling of human light interaction in indoor environments 2017
Geometric proposals for faster R-CNN 2017
Towards segmenting consumer stereo videos: benchmark, baselines and ensembles 2017
LIT: a system and benchmark for light understanding 2017
People detection in fish-eye top-views 2017
Insegnamento Codice Anno Corso - Frequentare
ADVANCED MACHINE LEARNING 10589621 2020/2021 Data Science
FOUNDATIONS OF DATA SCIENCE 1047627 2020/2021 Computer Science - Informatica
ADVANCED MACHINE LEARNING 10589621 2019/2020 Data Science
FOUNDATIONS OF DATA SCIENCE 1047627 2019/2020 Computer Science - Informatica