Pablo Arbeláez received a Ph.D. with honors in Applied Mathematics from the Université Paris-Dauphine in 2005. He was a Research Scientist with the Computer Vision Group at UC Berkeley from 2007 to 2014. He currently holds a faculty position in the Department of Biomedical Engineering at Universidad de los Andes in Colombia. Since 2020, he has led the Center for Research and Formation in Artificial Intelligence (CinfonIA) at UniAndes. His research interests are in computer vision and machine learning, in which he has worked on several problems, including perceptual grouping, object recognition, and the analysis of biomedical images.
Computer Vision and AI in medical Imaging
The lectures will overview our recent biomedical research at UniAndes and include theory and hands-on tutorials. The first lecture will focus on the problem of robust segmentation on three-dimensional diagnostic images, emphasizing the methodology presented in [1, 2]. The second lecture will be divided into two. We will first delve into robotic surgery, presenting the work in [3, 4] and the winning entry of the ENDOVIS 22 Challenge. We will then conclude the series with the topic of automated pharmaceutical discovery .
- Daza et al. “Towards robust general medical image segmentation”. MICCAI 2021.
- Valderrama et al. “JoB-VS: Joint Brain-Vessel Segmentation in TOF-MRA Images”. ISBI 2023.
- Valderrama et al. “Towards holistic surgical scene understanding”. MICCAI 2022.
- Ayobi et al. “MATIS: Masked-Attention Transformers for Surgical Instrument Segmentation”. ISBI 2023.
- Puentes et al. “Modeling Protein-Ligand Interactions with Graph Convolutional Networks for Interpretable Pharmaceutical Discovery”. Scientific Reports 2022.