Prof. Vasilis Megalooikonomou received his B.E. in Computer Engineering and Informatics from the University of Patras, Greece, in 1991, and his M.S. and Ph.D. in Computer Science from the University of Maryland, Baltimore County in 1995 and 1997, respectively. He is currently a Professor in the Computer Engineering and Informatics Department (CEID) of UoP, Greece. Prior to his appointment at UoP, he held faculty positions at Temple University, Dartmouth College, and Johns Hopkins University, School of Medicine.
His research interests include medical informatics and bioinformatics, data mining, data compression, pattern recognition, intelligent information systems, medical image analysis, and multimedia database systems. He has co-authored over 200 refereed articles in journals and conference proceedings and six book chapters. He has been on the program committees of a number of premier conferences and serves regularly as a referee. He received a CAREER award from the National Science Foundation in 2003 to work on developing data mining methods for extracting patterns from medical image databases.
During the last 8 years he has coordinated major projects including FP7 ARMOR, BIOMEDMINE, and the H2020 FRAILSAFE project. His work has been supported by the NSF, NIH, Pennsylvania Department of Health, and Lockheed Martin Corporation. He is a member of IEEE, IEEE CS, ACM, SIAM, and OHBM.
Engineer (M.Eng.) with MSc degrees in Biomedical Engineering and Machine Learning. Currently a PhD candidate at the MDAKM Lab under Prof. Megalooikonomou. His research focuses on multimodal deep learning architectures for biomedical data analysis.
Quantum computing PhD candidate and interdisciplinary researcher working at the intersection of quantum algorithms, bioinformatics, and mathematical modeling. Skilled in quantum theory, algorithm design, and data-driven problem solving for healthcare and optimization.
Researcher at the University of Patras, CEID. PhD candidate focusing on AI in biomedicine, machine learning models for omics data integration and patient classification. Background in Physics, Polymer Science, and Quantum Physics with expertise in spectroscopy and signal analysis.