IbPRIA 2023 image number 2
IbPRIA 2023: 11th Iberian Conference on Pattern Recognition and Image Analysis
Alicante, Spain. June 27-30, 2023

June 27, 2023

Sergio Orts

Sergio Orts-Escolano is a Staff Research Scientist at Google. His research interests include human-centric 3D computer vision and machine learning, with a special focus on topics such as depth sensing, segmentation and matting, image relighting, neural rendering, generative models, volumetric reconstruction, and immersive 3D telepresence. Before joining Google, he was an assistant professor in the department of Computer Science and Artificial Intelligence at the University of Alicante, Spain. Previously, he was a Senior Scientist at PerceptiveIO and a researcher at Microsoft Research where he was one of the leading members of the Holoportation project (3D virtual human teleportation in real-time). He has authored more than 50 publications in top journals and conferences like CVPR, ECCV, SIGGRAPH, 3DV, BMVC, IROS, and TPAMI.

Mikel Artetxe

Mikel Artetxe is a Research Scientist at FAIR (Meta AI). Prior to that, he did his PhD at the University of the Basque Country, advised by Eneko Agirre and Gorka Labaka, and interned at DeepMind, FAIR, and Google. Mikel's general research area is in Natural Language Processing and Machine Learning. His background is mostly on multilinguality, focusing on low-resource scenarios and, in particular, unsupervised machine translation and cross-lingual representation learning. More recently, he has also been working on natural language generation, few-shot learning and large-scale language models.

Karteek Alahari

Karteek Alahari is a senior researcher (known as chargé de recherche in France, which is equivalent to a tenured associate professor) at Inria. He is based in the Thoth research team at the Inria Grenoble - Rhône-Alpes center. He was previously a postdoctoral fellow in the Inria WILLOW team at the Department of Computer Science in ENS (École Normale Supérieure), after completing his PhD in 2010 in the UK. His current research focuses on addressing the visual understanding problem in the context of large-scale datasets. In particular, he works on learning robust and effective visual representations, when only partially-supervised data is available. This includes frameworks such as incremental learning, weakly-supervised learning, adversarial training, etc. Dr. Alahari's research has been funded by a Google research award, the French national research agency, and other industrial grants, including Facebook, NaverLabs Europe, Valeo.


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