Duc is a research consultant at the University of Luxembourg. Duc is passionate about machine learning and deep learning, specializing in computer vision and image processing. His research focuses on developing and applying computer vision algorithms for object segmentation and recognition in image data. Duc's expertise in programming and machine learning extends to data processing and analysis, where he constructs robust data pipelines foundational for creating predictive models.
Before becoming a consultant with team MIDAS, Duc applied his knowledge to real-world problems at Goodyear SA in Colmar-Berg, Luxembourg. He completed his postdoctoral research at the Memorial Sloan Kettering Cancer Center in New York, NY, USA. Duc earned his PhD in Computer Science from the University of Minnesota, MN, USA, following his master and engineering degrees from the University Louis Pasteur I, Strasbourg, France.

Research interests

#computer-science#computer-vision#deep-learning#machine-learning

Recent publications

Covariance based point cloud descriptors for object detection and recognition
Fehr, Duc; Beksi, William J.; Zermas, Dimitris; Papanikolopoulos, Nikolaos in Computer vision and image understanding (2016)

Automatic classification of prostate cancer Gleason scores from multiparametric magnetic resonance images
Fehr, Duc; Veeraraghavan, Harini; Wibmer, Andreas; Gondo, Tatsuo; Matsumoto, Kazuhiro; Vargas, Herbert Alberto; Sala, Evis; Hricak, Hedvig; Deasy, Joseph O. in Proceedings of the National Academy of Sciences (2015)

Rgb-d object classification using covariance descriptors
Fehr, Duc; Beksi, William J.; Zermas, Dimitris; Papanikolopoulos, Nikolaos in 2014 IEEE International Conference on Robotics and Automation (ICRA) (2014)

Occlusion alleviation through motion using a mobile robot
Fehr, Duc; Beksi, William J.; Zermas, Dimitris; Papanikolopoulos, Nikolaos in 2014 IEEE International Conference on Robotics and Automation (ICRA) (2014)