Daniel Gatica-Perez

Adjunct Professor

daniel.gatica-perez@epfl.ch +41 21 693 19 51

EPFL STI IEM LIDIAP
ELD 241 (Bâtiment ELD)
Station 11
1015 Lausanne

+41 21 693 19 51
Office: 
EPFL > STI > IEM > LIDIAP

Web site:  Web site:  https://idiap.epfl.ch/

EPFL > VPA-AVP-PGE > AVP-PGE-EDOC > EDEE-ENS

EPFL > VPA-AVP-E > AVP-E > AVP-E-CDS

Web site:  Web site:  https://dms.epfl.ch/DOCS/E/CDS

EPFL CDH SODH-GE
INF 136 (Bâtiment INF)
Station 14
1015 Lausanne

+41 21 693 19 51
Office:  INN 138
EPFL > CDH > DHI > DHI-GE

EPFL CDH SODH-GE
INN 138 (Bâtiment INN)
Station 14
1015 Lausanne

+41 21 693 19 51
Office:  INN 138
EPFL > CDH > CDH-SODH > SODH-GE

EPFL > CDH > CDH-SODH > SODH-ENS

EPFL > CDH > DHI > SCI-CDH-DGP

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Administrative data

Teaching & PhD

Teaching

Digital Humanities

PhD Students

Annapureddy Ravinithesh Reddy, Bros Victor, Coman Andrei Catalin, Fehr Fabio James, Mostaani Zohreh,

Past EPFL PhD Students

Biel Tres Joan Isaac , Can Gülcan , Farrahi Katayoun , Jayagopi Dinesh Babu , Johari Seyed Mohammad Mahdi , Mai Jan Frederik Jonas Florian , Marfurt Andreas Thomas , Meegahapola Lakmal Buddika , Muralidhar Skanda , Negoescu Radu Andrei , Nguyen Laurent Son , Parthasarathi Sree Hari Krishnan , Phan Thanh Trung , Pidoux Jessica Carolina , Roman Rangel Edgar , Sajadmanesh Sina , Sanchez Cortes Dairazalia , Santani Darshan , Shetty Suhan Narayana , Smith Kevin , Tornay Sandrine , Zhang Dong ,

Courses

Computational Social Media

The course integrates concepts from media studies, machine learning, multimedia, and network science to characterize social practices and analyze content in platforms like Twitter, Instagram, YouTube, and TikTok. Students will learn computational methods to understand phenomena in social media.