The Doctoral Programme in Information Engineering and Computer Science (IECS) organizes the fifth edition of the PI Stories, a series of seminars aimed at providing the opportunity for PhD students to learn the success stories of some of the most talented researchers in the world.
Abstract
After dedicating nearly two decades to a fulfilling career in Academia, I found myself at a crossroads three years ago. In a moment of what some might call madness, but I prefer to think of as inspired courage, I made the decision to leave the familiar halls of higher education, Ph.D. students, and publications for the dynamic and fast-paced world of Zoom Communications. This move was driven by a desire to challenge myself in the industry and to validate my years of applied research in a new, practical context. The transition from the structured environment of academia to the ever-evolving landscape of a tech giant like Zoom was both daunting and exhilarating. It represented not just a change in the workplace but a fundamental shift in my professional identity and day-to-day reality.
In this presentation, I'll share my journey and insights, distilling the key lessons I've learned in the AI industry. I aim to provide you with a valuable insider's perspective on the dynamic world of industrial artificial intelligence.
About the Speaker
Marco Turchi is the head of the machine translation activities at Zoom Video Communications. He received his PhD degree in Computer Science from the U. of Siena, Italy in 2006. Before joining Zoom in 2022, he led the machine translation unit at Fondazione Bruno Kessler, worked at the European Commission Joint Research Centre, Italy, at the University of Bristol, at the Xerox Research Centre Europe, and at Yahoo Research Lab. His research activities focus on various aspects of sequence-to-sequence modelling and large language modelling applied to machine translation, speech translation, and automatic post-editing. He has co-authored more than 200 scientific publications and served as a reviewer for international journals, conferences, and workshops. He is the co-organizer of the Conference on Machine Translation, the Conference on Spoken Language Translation, and the automatic post-editing evaluation campaigns. He has been involved in several EU projects such as SMART, Matecat, ModernMT, QT21, MateDUB, and Meetween. He was the recipient of the Amazon AWS ML Research Awards on the topic of end-to-end spoken language translation in rich data conditions.