Articles under Review

Peer-reviewed Journals

Chapters in Books

International Peer Reviewed Conference Papers

Selected Oral Presentations and Prototype Demos

 Ph.D. Thesis

In his Ph.D. with a thesis titled Context-Aware Personalization for Mobile Multimedia, which was defended in May 2015, he researched, designed, and developed a system that explores existing sensors in mobile devices, such as accelerometer, gyroscope, magnetometer, GPS, light, WiFi, sound sensors, etc. to obtain information about mobile users’ contexts to provide personalized mobile content. Simultaneously, the system monitors users’ consumption to build contextualized user profiles.

Using the data collected and the contextualized user profiles, it delivers seamlessly or on-demand content suggestions, such as movies, to mobile users, adapted to their current usage contexts, characteristics of the device, time of the day, location, network connections, environmental conditions, among others.

The system named “Context-Aware Personalized Multimedia Recommendations for Mobile Users” (CAMR) consists mainly of an Android-based mobile app and a Web-based application both serving as a proof-of-concept of the proposed solution in real world operating conditions.