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Curriculum breve
  CLIMENT PEREZ, PAU

Brief curriculum
CLIMENT PEREZ, PAU

Personal data

E-mail:
Tel. No.
+34 965903400 x 3204
Location:

Current professional activity

Position:
PROFESOR/A AYUDANTE DOCTOR/A
Dept.
Institutes:
I.U. INVESTIGACION INFORMATICA
Groups:

Academic background

  • Ph.D, Doctor of Philosophy (Artificial Intelligence)
    Kingston University London (10/10/2016)
  • Máster en Tecnologías de la Informática
    UNIVERSIDAD DE ALICANTE (28/09/2010)
  • Ingeniería Informática
    Universitat d`Alacant (21/09/2009)
  • Ingeniería Técnica en Informática de Sistemas
    Universitat d`Alacant (11/09/2006)

He is currently an Assistant Professor at the University of Alicante (09/2022-present). Before that, in 2021, he was Senior Collaborator in the national project "GLORiA-", by the the Biodiversity Foundation (Fundación Biodiversidad). He was also Senior Collaborator in the European project PAAL (privacy-aware and acceptable life-logging services for older and frail people) of the Horizon 2020 EU framework, under the initiative "More years, better lives".

From 2016 to 2018, he gained industry experience in the department for research and development of new algorithms at VCA Technologies, Ltd., UK. The company collaborated in the European project MONICA (Horizon 2020).

He received his PhD from Kingston University London in 2016, after a doctoral scholarship for 3 years (2012-2015), plus one year for thesis writing (2016). The PhD was associated with the European project PROACTIVE (FP7).

Prior to that grant, he had gained research experience at the UA, with a Collaboration Grant (2008) and several direct award grants (2010-2011), as well as a senior technician contract (I-PAS 33/11), associated to the national project "Talismán+" (TIN2010-20510-C04-02).

His current research interests include computer vision based solutions for active and assisted living (AAL), more specifically the recognition of activities of daily living (ADLs), taking into account privacy for better acceptability by end users. This includes deep learning-based methods for privacy preservation in videos, using context information (i.e. using a "context-aware privacy" principle). In addition, his medium-term objectives include the use of alternative views in the deployment of cameras in the home, such as ceiling-mounted cameras, or the study of this type of recognition with 'first-person view' cameras (i.e. 'wearable cameras').