Dr. Aleksandar Jeremic – Faculty of Engineering
Aleksandar Jeremic

Dr. Aleksandar Jeremic

Expertise

Biomedical signal processing, statistical signal processing, biometrics, mathematical modeling of physiological systems, medical imaging. biochemical sensing, environmental monitoring, array signal processing
  • Associate Professor

    Electrical & Computer Engineering

  • Associate Professor

    McMaster School of Biomedical Engineering

Overview

My research interests are in the area of biomedical signal processes of physiological signals such as electrocardiography (ECG) and electroencephalography (EEG) with applications to optimization of healthcare treatments and biometrics/bioidentification using both small and large data sets.

Block Heading

Aleksandar Jeremic received the Dipl. Ing. degree in electrical engineering from the University of Belgrade, Belgrade, Serbia in 1995, Master of Science in Electrical Engineering (MSEE) from The University of Illionois at Chicago in 1997 (advisor: Dr. Arye Nehorai) and Ph.D. in electrical engineering from the University of Illinois at Chicago in 2002 (advisor: Dr. Arye Nehorai). He has authored more than 40 articles in the statistical and biomedical signal processing. His current research interest include small size machine learning techniques for biomedical applications. He was a reccipient of the teaching award by McMaster Electrical and Computer Engineering Society in 2018. He supervised/co-supervised 6 Ph.D. students and 12 M.Sc. students at McMaster Unviersity and University of Belgrade.

Dipl.Ing. (Belgrade, Serbia) ; M.S., Ph.D. (Illinois at Chicago, USA)

Received teaching award by McMaster Electrical and Computer Engineering Society in 2018.

Authored more than 50 technical articles and 2 book chapters in statistical and biomedical signal processing.

Supervised/co-supervised 7 Ph.D. students and 12 masters students.

Implemented neonatal seizure monitoring software in clinical settings.

List of selected publications:

A. Biran and A. Jeremic, “ECG Bio – Identification using Fréchet Classifiers: A proposed Methodology based on modeling the Dynamic Change of the ECG Features,” to appear in Biomedical Signal Processing and Control, Elsevier.

Natasa Radosavljevic, Dejan Nikolic, Milica Lazovic, Aleksandar Jeremic, “Hip Fractures in a Geriatric Population – Rehabilitation Based on Patients Needs,”, Aging and Disease, Vol. 5, pp. 177-182, 2014.

B. Liu, A. Jeremic, and K. M. Wong, “Optimal Distributed Detection of Multiple Hypotheses using Blind Algorithm,” IEEE Transactions on Aerospace and Electronic Systems, Vol. 47, pp. 317-331, 2011.