Graduate Student Spotlight: Serhii Reznichenko
First-year Miami University graduate student Serhii Rezinchenko recently had his paper on Electrocardiogram (ECG) lead subsets accepted to be presented at the 2023 IEEE-EMBS conference in Sydney, Australia.
Serhii Reznichenko is a first-year Miami University graduate student studying Computer Science who recently had his paper that explored Electrocardiogram (ECG) lead subsets accepted to be present in Sydney, Australia, at the 2023 IEEE-EMBS conference.
Reznichenko’s area of research interest is the application of machine learning in analyzing ECG signals, which can record electrical signals from the heart to check for different heart conditions. He is particularly fascinated by the potential of technology in revolutionizing how we can more accurately diagnose and treat heart conditions.
His paper, titled “Optimization of Arrhythmia-based ECG-lead Selection for Computer-interpreted Heart Rhythm Classification,” looked at the clinical diagnostic criteria for different types of cardiac arrhythmias, which are often specific to certain ECG leads. The paper specifically aimed to explore and analyze the selection of ECG lead subsets that can be used to target and tailor to specific arrhythmia types.
The IEEE-EMBS (Engineering in Medicine and Biology Society) conference is an international conference that brings together professionals, researchers, students, and practitioners from diverse fields, including biomedical engineering, healthcare, and life sciences.
Reznichenko being chosen to present his work at the conference will also give him the chance to network and connect with a variety of professionals from diverse backgrounds and industries, as well as open up an opportunity for attendees to collaborate, partner with, and can eventually lead to future career prospects.
The opportunity was a thrilling surprise to Reznichenko, who credits Miami’s College of Engineering and Computing and its faculty for playing a large role in supporting his research and the financial support to cover expenses for him to go to the conference.
Shijie Zhou, Assistant Professor in the Chemical, Paper and Biomedical Engineering department at Miami, is Reznichenko’s advisor and provided guidance and support as a mentor throughout the project's research, development, and publication.
I am incredibly proud of Serhii’s dedication and hard work, especially given that he just finished his first semester,” Zhou said.
After his graduate studies at Miami, Reznichenko plans to pursue a doctorate in machine learning to advance his career and continue contributing to cutting-edge research and development projects involving machine learning.
“Ultimately, I am driven by my passion for using technology to solve complex problems, and I am confident that a Ph.D. in machine learning would enable me to make meaningful contributions to this dynamic and rapidly evolving field,” Reznichenko said.
The chart shows the process of finding an optimal subset of ECG leads using Machine Learning.
