TelecomBCN DLAI

Monday 17th December-4pm

UPC ETSETB TelecomBCN organises an open lecture as a conclusion of the second edition of the Deep Learning for Artificial Intelligence course of Master MET. The lecture will be taught by Petia Radeva, from the Universitat de Barcelona and Computer Vision Center, and Xavi Gonzalvo, from Google AI New York. This master class will also include a prologue where the students of the master course will present their projects developed during the Autumn semester.

This activity is of free access.

Location: Aula Master in the ground floor of building A3 in Campus Nord UPC (entrance from Plaça Telecos)

Schedule

14:00 Welcome & MSc offers on deep learning at GPI & TALP UPC

14:15 Student projects

15:45 Class of 2018 photo at B3 stairs

16:00 Petia Radeva (UB-CVC)

16:45 Xavi Gonzalvo (Google AI)

17:30 Closing of the DLAI 2018 course

You are invited to prepare this session beforehand with the course material available online at:

http://bit.ly/dlai2018

Petia Radeva

Universitat de Barcelona /

Computer Vision Center

Petia Radeva did her undergraduate study at the University of Sofia, Bulgaria, at 1989. In 1991 she moved to Spain where in 1993 she presented my Master at the Universitat Autònoma de Barcelona in the field of Image Processing, Computer Graphics and Artificial Intelligence. In 1996, she received my Ph.D. degree from the Universitat Autònoma de Barcelona. Currently, she is Head of Barcelona Perceptual Computing Laboratory (BCNPCL) at the University of Barcelona, and Head of Medical Imaging Laboratory (MILab) of Computer Vision Center.

Xavi Gonzalvo

Google AI New York City

Talk: "AdaNet: Adaptive structural learning of Deep Neural Networks" (ICML 2018)

Xavier Gonzalvo was born in Barcelona, Spain, in 1980. He received his M.Sc. degree in Electrical Engineering from Enginyeria i Arquitectura La Salle, Universitat Ramon Llull (URL), Barcelona, Spain in 2004. In 2010 he completed his Ph.D. studies in Information and Communications Technologies also at Ramon Llull. His thesis work focused on the development of hybrid systems merging HMM and unit selection approaches. He was with the Department of Communications and Signal Theory, Enginyeria i Arquitectura LaSalle, as an Assistant Researcher from 2003 to March 2008. He worked at Phonetic Arts Ltd in Cambridge, UK until he joined Google Speech Research in January 2011 and was managing the Google TTS research team until 2016. He is now in Google AI in NYC leading a team of researchers working on AdaNet, a flexible deep learning AutoML algorithm.