Rising Star

Cardiff, UK, June 29th - July 3rd, 2026

QoMEX 2026 - Quality of Multimedia Experience Meets Machine Intelligence

The QoMEX 2026 Organizing Committee received a total of 11 applications for the QoMEX Rising Star Award. The QoMEX Rising Star Program aims to recognize and promote outstanding early-career researchers who have demonstrated strong potential and impactful contributions to the field of Quality of Multimedia Experience (QoE), while highlighting emerging leaders whose work advances the understanding, modeling, measurement, and optimization of multimedia quality and user experience.

The applications were evaluated by a Selection Committee composed of senior and internationally recognized researchers in the field of Quality of Experience. The evaluation was based on the criteria outlined in the call for nominations, including research quality and technical depth; originality, vision, and research trajectory; leadership and independence potential; academic, industrial, and societal influence; community and ecosystem contributions; and the quality and relevance of the proposed talk.

The evaluation panel was composed as follows (listed in alphabetical order):

  • Touradj Ebrahimi (EPFL, Switzerland)
  • Narciso García (Universidad Politécnica de Madrid, Spain)
  • Patrick Le Callet (Nantes Université, France)
  • Fernando Pereira (Instituto Superior Técnico, Portugal)
  • Christian Timmerer (Alpen-Adria-Universität Klagenfurt, Austria)
 
Finalists (listed in alphabetical order):
  • Sara Baldoni
    University of Padova, Italy
    Invited Talk: The Quality Continuum of Collaborative Virtual Reality: Bridging Human Interaction, Communication Services, and Quality of Experience
  • Huiyu Duan
    Shanghai Jiao Tong University, China
    Invited Talk: Towards Next-Generation QoE: Perception, Evaluation, and Optimization
  • Simone Procu
    Università degli Studi di Cagliari, Italy
    Invited Talk: Towards Generative Models of Quality of Experience: Leveraging Large Language Models for Human-Centered QoE Prediction