Speakers
Dr. Nicola Strisciuglio
Nicola Strisciuglio is an Associate Professor in Computer Vision and Machine Learning at the University of Twente (Netherlands). He obtained a joint PhD degree cum laude from the University of Groningen (NL) and the University of Salerno (IT), in 2016. He serves as Associate Editor of Pattern Recognition and Area Chair at NeurIPS2024 and has been Program Chair of CAIP2019.
Dr. Fabian Caba Heilbron
Fabian is a Research Scientist at Adobe Systems. His research interests span Computer Vision and Machine Learning. He is particularly interested in video understanding and human activity analysis. Fabian received his Ph.D. from KAUST in 2019 under the supervision of professor Bernard Ghanem. He was an intern twice at Adobe (2017, 2018) and once at Amazon Berlin (2018). He is a program chair of the International Challenge on Activity Recognition (ActivityNet), which has been hosted yearly at CVPR since 2016.
Dr. Tolga Birdal
Tolga Birdal is an assistant professor in the Department of Computing of Imperial College London. Previously, he was a senior Postdoctoral Research Fellow at Stanford University within the Geometric Computing Group of Prof. Leonidas Guibas. Tolga has defended his masters and Ph.D. theses at the Computer Vision Group under Chair for Computer Aided Medical Procedures, Technical University of Munich led by Prof. Nassir Navab. He was also a Doktorand at Siemens AG under supervision of Dr. Slobodan Ilic working on “Geometric Methods for 3D Reconstruction from Large Point Clouds”. His current foci of interest involve topological / geometric machine learning and 3D computer vision. More theoretical work is aimed at investigating and interrogating limits in geometric computing and non-Euclidean inference as well as principles of deep learning. Tolga has numerous publications at the well-respected venues such as NeurIPS, CVPR, ICCV, ICML, ECCV, ICLR, T-PAMI, ICRA and IROS. Aside from his academic life, Tolga has co-founded multiple companies including Befunky, a widely used web-based image editing platform.
Dr. Petia Ivanova Radeva
Prof. Petia Radeva is a Full professor at the Universitat de Barcelona (UB), PI of the Consolidated Research Group “Computer Vision and Machine Learning” at the University of Barcelona (CVUB) at UB (www.ub.edu/cvub) and Senior researcher in Computer Vision Center (www.cvc.uab.es). She was PI of UB in 6 European, 3 international and more than 30 national projects devoted to applying Computer Vision and Machine learning for real problems like food intake monitoring (e.g. for patients with kidney transplants and for older people). Petia Radeva is a REA-FET-OPEN vice-chair since 2015 on, and international mentor in the Wild Cards EIT program since 2017. She is an Associate editor of Pattern Recognition journal (Q1) and International Journal of Visual Communication and Image Representation (Q2). Petia Radeva has been awarded IAPR Fellow since 2015, ICREA Academia assigned to the 30 best scientists in Catalonia for her scientific merits since 2015, received several international awards (“Aurora Pons Porrata” of CIARP, Prize “Antonio Caparrós” for the best technology transfer of UB, etc). Homepage: http://www.ub.edu/cvub/petiaradeva/
Dr. Mengwei Ren
Mengwei recently joined Adobe as a Research Scientist. Previously, she obtained her Ph.D. in Computer Science from NYU in 2023. Her research focuses on generative modeling and representation learning, with their diverse applications in computer vision and neuroimage analysis, such as image restoration, harmonization, and spatiotemporal neuroimage analysis. During her PhD, she has gained valuable research experience through internships at Siemens Healthineers, Google Research and Adobe. Homepage: https://www.mengweiren.com/
Dr. Carlos Hinojosa
Dr. Carlos is a Postdoctoral researcher at King Abdullah University of Science and Technology (KAUST) working with Prof. Bernard Ghanem. His research interests span Computer Vision, Machine Learning and Computational Imaging. In particular, he is interested in developing efficient vision systems and machine-learning models that can efficiently recognize and understand human actions and activities, objects, scenes and events while also obtaining additional benefits like privacy protection, compression, and robustness. Carlos received his Ph.D. from Universidad Industrial de Santander, Colombia, in 2022 under the supervision of Professor Henry Arguello. He was an intern researcher at Stanford Vision and Learning Lab (SVL) in 2021. He has co-organized the LXCV workshop at CVPR (2 times), ICCV (2 times) and ECCV (1 time). Carlos has publications at top conferences such as CVPR, ICCV, and ECCV, IEEE journals such as TMI, and JSTSP and has published two US patents. Homepage: https://carloshinojosa.me