PhD in Engineering and Applied Sciences, University of Barcelona, 2019. Postdoctoral fellow at Computer Vision Center (CVC-UAB). Part-time professor at University of Barcelona. Fellow member of Human Pose recovery and Behavior Analysis group (HuPBA).

Short bio

I completed my B.Sc. degree in Computer Science at Universitat de Barcelona in 2012, my M.Sc. in Artificial Intelligence at Universitat Politècnica de Catalunya in 2014, and my PhD in Engineering and Applied Sciences at Universitat de Barcelona in 2019. My PhD thesis, “Learning to recognize human actions: from hand-crated to deep-learning based visual representations”, explored the visual multimodality for visual human-related analyses and also how to handle the temporal information in action recognition problems. During this time, I was granted the FI-DGR (2015-2017) fellowship by Generalitat de Catalunya to conduct my pre-doctoral research.

In 2012 I became a fellow member of the Human Pose recovery and Behavior Analysis (HuPBA) research group led by Dr. Sergio Escalera, where I conducted most of my research. I also participated in numerous competitive international and national research projects. I also co-organized different challenges and workshops in international conferences ECCV2016, ICPR2016, and FG2020 in collaboration with ChaLearn LAP and Microsoft Research. In 2020, I became a member of the ELLIS society. Today, I am employed as a postdoctoral fellow by Computer Vision Center carrying tasks as the technical coordinator of the national Spanish project “SENIOR” (founded by the Ministerio de Ciencia, Innovación y Universidades and European Regional Development Fund). I co-advised 3 Bachelor thesis, and taught at Universitat de Barcelona: Programming II (2015/16) and Data Structures (2019/20) as a part-time professor now.

For my current research, I am looking forward to investigate potential ways to deal with the data starvation problem in state-of-the-art deep-learning models. My final goal is to contribute to the development of powerful tools for e-Health applications, and more precisely tailored intelligent systems to assist chronic patients in their everyday life activities.