I am a fourth year Ph.D. student in Electrical and Computer Engineering at Georgia Institute of Technology. I am a Fulbright Scholar and a research assistant in the Inan Research Lab, led by Prof. Omer Inan.
E-mail: bsemiz at gatech dot edu
Office: Technology Square Research Building
85 Fifth St NW
Atlanta, GA 30308
My research interests include biomedical signal processing, applied machine learning, and non-invasive wearable device design. To meet the compelling need for quantitative schemes for assessing disease or injury state, my research (i) proposes novel sensor modalities that can perform continuous and non-invasive health monitoring to provide longitudinal insights regarding a person's health, (ii) develops algorithms to extract clinically useful information from the acoustical and vibrational signals captured through these sensors, and (iii) uses this information to derive digital biomarkers for quantifying human health.
My research is in collaboration with scientists and physicians from Emory University School of Medicine, University of California San Francisco, and Northwestern University.
Jan 08, 2020 : New paper in press! "Detecting Suspected Pump Thrombosis in Left Ventricular Assist Devices via Acoustic Analysis", IEEE Journal of Biomedical and Health Informatics (JBHI).
Sep 18, 2019 : Fox 5 Atlanta featured our research: "Georgia Tech researchers develop patch to track heart failure", Our advisor, Prof. Omer Inan, talks about our joint work with UCSF. Have a listen/read: [link]
Sep 16, 2019 : Fox 5 Atlanta featured our research: "Georgia Tech researchers say knee sounds reveal secrets about joint health". Our advisor, Prof. Omer Inan, talks about our joint sounds projects. Have a listen/read: [link]
July 26, 2019 : New paper in press! "A Globalized Model for Mapping Wearable Seismocardiogram Signals to Whole-Body Ballistocardiogram Signals Based on Deep Learning", IEEE Journal of Biomedical and Health Informatics (JBHI).
July 17, 2019 : New paper in press! "A Unified Framework for Quality Indexing and Classification of Seismocardiogram Signals", IEEE Journal of Biomedical and Health Informatics (JBHI).