Unlock your academic potential and expand your network by joining us!
Dan Popescu graduated from the University of POLITEHNICA of Bucharest (UPB), Faculty of Automatic Control and Computer Science, and the UNIVERSITY of Bucharest, Faculty of Mathematics. He has a Ph.D. from UPB. Currently, he is a full professor at UPB, a scientific leader in the Doctoral School of Automation and Computers, and head of the Laboratory for Innovative Processes and Products to Increase the Quality of Life from UPB (PRECIS Center). He was vice-dean of research activity at the Faculty of Automatic Control and Computer Science and a member of the UPB Senate. His main research areas are the following: medical image processing, image classification and segmentation, neural networks, digital signal processing, alerting systems, wireless sensor networks, measurement systems, and robotic systems. The research activity is validated by more than 10 projects in the mentioned fields as director, over 300 papers in journals or proceedings of prestigious international conferences, and over 20 books. In the medical imaging domain, the research was oriented towards image segmentation, detection of regions of interest, neural networks and machine learning (melanoma, retinal images, blood vessels, emotions, iris, skin cancer diagnosis), IT solution for monitoring and treatment of a patient with liver cirrhosis, healthcare hybrid cloud computing platform, identification of red blood cells, and breast cancer detection.
Dan Popescu graduated from the University of POLITEHNICA of Bucharest (UPB), Faculty of Automatic Control and Computer Science, and the UNIVERSITY of Bucharest, Faculty of Mathematics. He has a Ph.D. from UPB. Currently, he is a full professor at UPB, a scientific leader in the Doctoral School of Automation and Computers, and head of the Laboratory for Innovative Processes and Products to Increase the Quality of Life from UPB (PRECIS Center). He was vice-dean of research activity at the Faculty of Automatic Control and Computer Science and a member of the UPB Senate. His main research areas are the following: medical image processing, image classification and segmentation, neural networks, digital signal processing, alerting systems, wireless sensor networks, measurement systems, and robotic systems. The research activity is validated by more than 10 projects in the mentioned fields as director, over 300 papers in journals or proceedings of prestigious international conferences, and over 20 books. In the medical imaging domain, the research was oriented towards image segmentation, detection of regions of interest, neural networks and machine learning (melanoma, retinal images, blood vessels, emotions, iris, skin cancer diagnosis), IT solution for monitoring and treatment of a patient with liver cirrhosis, healthcare hybrid cloud computing platform, identification of red blood cells, and breast cancer detection.
