Giuseppe Riccardi

Giuseppe Riccardi

Prof. Giuseppe Riccardi, PhD, is founder and director of the Signals and Interactive Systems Lab at University of Trento, Italy.

He received his Laurea degree in Electrical Engineering and Master in Information Technology, in 1991, from the University of Padua and CEFRIEL/Politechnic of Milan (Italy), respectively.
From 1990 to 1993 he collaborated with Alcatel‐Telettra Research Laboratories (Italy).
In 1995 he received his PhD in Electrical Engineering from the Department of Electrical Engineering at the University of Padua, Italy.

From 1993 to 2005, he was at AT&T Bell Laboratories (USA) and then AT&T Labs‐Research (USA) where he worked in the Speech and Language Processing Lab.
In 2005 joined the faculty of University of Trento (Italy). He is affiliated with the Department of Information Engineering and Computer Science and Center for Mind/Brain Sciences.

Prof. Riccardi’s research on stochastic finite state machines for speech and language processing has been applied to a wide range of domains for task automation. He and his colleagues designed the AT&T spoken language system ranked first in the 1994 DARPA ATIS evaluation.
He and his colleagues pioneered the speech and language research in spontaneous speech for the well‐known “How May I Help You?” research program which led to breakthrough speech services.
His research on learning finite state automata and transducers has lead to the creation of the first large scale finite state chain decoding for machine translation ( Anuvaad ).
He lead University of Trento’s team that contributed to the IBM WATSON machine that won the Jeopardy! challenge.

Prof. Riccardi has co‐authored more than 140 conference and journal peerreviewed papers. He holds more than 60 patents in the field of automatic speech recognition, understanding, machine translation, natural language processing and machine learning.

He is member of ACL, ISCA, ACM and Fellow of IEEE. Prof. Riccardi has received many national and international awards and more recently the Marie Curie Excellence Grant by the European Commission, 2009 IEEE SPS Best Paper Award and IBM Faculty Award.


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