Daniel Gatica-Perez

Expertise Social computing, social media, ubiquitous computing, crowdsourcing, machine learning. Current work My research integrates theories and methods from ubiquitous computing, social media, machine learning, and social sciences to understand human behavior in daily life and to create applications for social good.My current research interests include:* Mobile crowdsourcing and social media analytics for social good.* Crowdsourcing for cities.* Social video analytics, with focus on conversational behavior. * Ubiquitous computing in face-to-face interaction. * Analysis of ancient Maya hieroglyphic collections.My recent research has been supported by the Swiss National Science Foundation, the Swiss Commission for Technology and Innovation, the European Commission, and industry partners including Nokia, NTT, and Swiss startups. Website www.idiap.ch/~gatica I am Professeur Titulaire at EPFL and direct the Social Computing Group at Idiap. I am a faculty member of the School of Engineering (STI) and the College of Humanities (CDH), where I am member of the Digital Humanities Institute (DHI). Education PhD | Electrical Engineering 2001 – 2001 University of Washington Teaching & PhD PhD Students Ravinithesh Reddy Annapureddy, Stefano Sorrentino, Matilde Barbini, Isabelle Mohr, Aurel Ruben Mäder, Victor Bros, Pierre Anton Beckmann, Kimia Alavi, Nil Yagmur Ilba Past EPFL PhD Students Dinesh Babu Jayagopi, Radu Andrei Negoescu, Katayoun Farrahi, Dairazalia Sanchez Cortes, Edgar Roman Rangel, Joan Isaac Biel Tres, Laurent Son Nguyen, Darshan Santani, Gülcan Can, Skanda Muralidhar, Thanh Trung Phan, Jessica Pidoux, Sandrine Tornay, Andreas Thomas Marfurt, Jan Frederik Jonas Florian Mai, Sina Sajadmanesh, Lakmal Buddika Meegahapola, Suhan Narayana Shetty, Mostaani Zohreh, Fabio James Fehr, Andrei Catalin Coman Past EPFL PhD Students as codirector Dong Zhang, Florent Monay Michaud, Kevin Smith, Dinesh Babu Jayagopi, Radu Andrei Negoescu, Katayoun Farrahi, Sree Hari Krishnan Parthasarathi, Dairazalia Sanchez Cortes, Seyed Mohammad Mahdi Johari Courses Computational Social Media DH-500 The course integrates concepts from media studies, machine learning, multimedia, and network science to characterize social practices and analyze content in platforms like Twitter/X, Instagram, YouTube, and TikTok. Students will learn computational methods to understand phenomena in social media. Awards ACM ICMI Community Service Award 2017