BSIA Lab Members

Present Graduate/Undergraduate Students

Mustafa_2 Mustafa Shuqair is pursuing his Ph.D. degree in Electrical Engineering at Florida Atlantic University. His research interests are biomedical signal processing and machine learning. He is currently working on developing novel approaches for the adaptive analysis of biomedical time series data. Mustafa received his MS degree in Mechatronics Engineering from the University of Siegen, Germany, and his BS in Mechatronics Engineering from Al-Balqa Applied University, Jordan. Contact: Mustafa Shuqair

Jasmine_4 Jasmine Chan is pursuing her Ph.D. degree in Experimental Psychology at Florida Atlantic University. Her research interests are in memory and decision-making. She is currently working on applying novel techniques to analyze functional near-infrared spectroscopy (fNIRS) data. This project is co-supervised by Dr. Teresa Wilcox, Professor of Psychology, and Dr. Ghoraani. Jasmine received her B.S. in Psychology from Texas A&M University. Contact: Jasmine Chan

Mahmoud Mahmoud Seifallahi is persuading his Ph.D. degree in Electrical Engineering at Florida Atlantic University. His research interests are signal processing and machine learning, especially in the field of aging and its related disorders like Alzheimer’s disease (AD). He is currently working on developing novel approaches for early diagnosis of AD using various data like gait and balance and machine learning methods. Mahmoud received his MS degree in Electrical Engineering from Shahrood University of Technology, Iran, and his BS in Electrical Engineering from Hakim Sabzevari University, Iran. Contact: Mahmoud Seifallahi

Marjan Marjan Nassajpour is pursuing her Ph.D. degree in Electrical Engineering at Florida Atlantic University. Her research interests are biomedical signal processing and machine learning. She is currently developing signal processing and machine learning models for the early detection of Alzheimer's disease. Marjan received both her MSc and BSc degrees in Electrical Engineering from the Isfahan University of Technology (IUT). Contact: Marjan Nassajpour Esfahani.

Shelly Shelly Davidashvilly is an undergraduate senior majoring in Computer Science with a certificate in Data Science. Her research aims to develop machine learning models to recognize activity data from wearable body sensors on Parkinson's patients for better treatment options. Contact: Shelly Davidashvilly

Thu Pyae Phyo Thu is pursuing a Master’s Degree in Electrical Engineering at Florida Atlantic University. His research interests are biomedical signal processing and machine learning. He is currently working on investigating gait features from wearable sensors for the early detection of Alzheimer’s disease. Contact: Pyae Phyo Thu

Emari Emari Wiles Lee is pursuing his B.S. degree in Computer Science at Florida Atlantic University. His research interests are in machine learning and computer vision. He is currently working on the use of computer vision techniques for the early diagnosis of Alzheimer’s and Parkinson’s disease. Contact: Emari Wiles Lee

Chris Christopher Chi is currently pursuing a BS in Computer Science at Florida Atlantic University. His research interests are in data mining and machine learning. His project is focused on developing a mobile application that retrieves data from a FitBit's internal accelerometer and gyroscope for analysis. A simple interface will be developed to allow users to report their medical symptoms and provide a response to health-related questions. Contact: Christopher Chi

Danny Danny Silvestrei is an undergraduate working towards my dual B.S. degree in computer science and computer engineering. He is also a part of an NSF-STEM AI program at FAU and will be pursuing my M.S. in artificial intelligence. His project is developing a mobile application for real-time activity recognition. Danny is an entrepreneur and his goal is to build new technology that is appealing for an average everyday user. Contact: Danny Silvestre

Past Students

Murtadha Hssayeni Ph.D. Computer Engineering degree, Florida Atlantic University (2022). Dissertation: Deep Learning Regression Models for Limited Biomedical Time-series Data. Read Here

Lillian Boettcher BS Computer Science, Florida Atlantic University (2020). Project: Characterizing gait features to detect early signs of cognitive decline.

Prasanth Ganesan Ph.D. Electrical Engineering degree, Florida Atlantic University (2019). Dissertation: Development of an algorithm to guide a multi-Pole diagnostic catheter for identifying the location of atrial fibrillation sources.

Sathyashree Basavaraju MS Electrical Engineering degree, Rochester Institute of Technology (2018). Thesis: Segmentation of the left atrium from the LGEMRI using graph cuts.

Anthony Salmin BS/MS Electrical Engineering degree, Rochester Institute of Technology (2016). Thesis: Determining the locations of Atrial Fibrillations using simulated electrograms and multipolar sensing catheters.

Vignesh Ramji MS degree in Electrical Engineering with a specialization in Communications and Signal Processing at Rochester Institute of Technology (2016). Thesis: Tensor approach of multi-channel sensors for Parkinson's Disease assessment.

Murtadha Hssayeni M.S. Computer Engineering student at the Rochester Institute of Technology (2016). Thesis: Developing an automated method to estimate medication fluctuation of Parkinson's Disease using motion analysis and deep learning.

Miguel Dominguez, M.S. Electrical Engineering student at the Rochester Institute of Technology (2016). Thesis: Developing a higher-quality and lower-bitrate vocoders for voice communications applications.

Prasanth Ganesan, M.S. Electrical Engineering student at the Rochester Institute of Technology (2015). Thesis: Characterization of cardiac electrogram signals during atrial fibrillation.

Kristina Shillieto B.Sc. Electrical Engineering, Rochester Institute of Technology (RIT). Project: Simulataion of a Lasso multi-pole diagnostic catheter on a 3D atrial endocardium for virtual cardiac testing and analysis of an Atrial Fibrillation.

Alison Kahn, Biomedical Engineering student at the Rochester Institute of Technology (2016). Project: Quantify EEG signals from children with infantile spasms through the comparison of different aspects of EEGs in both normal and abnormal subjects.

Nicholas DaCosta B.S in Biomedical Engineering, at the Rochester Institute of Technology (RIT). Project: Developing a novel algorithm to automatically detect Parkinson’s Disease patient medication state fluctuations using unobtrusive and easily available sensors.

Isaac Arabadjis B.S in Biomedical Engineering, at the Rochester Institute of Technology (RIT). Project: Developed Matlab Algorithms to determine electroencephalogram (EEG) coherence for infants experiencing infantile spasms (IS).

Ronak Patel, M.S. Electrical Engineering student at the Rochester Institute of Technology (Fall 2015). Project: Characterization of the mechanism of atrial fibrillation using probabilistic and machine learning.

Supachan Traitruengsakul, Electrical Engineering Graduate at the Rochester Institute of Technology (2015). Thesis: Extracted features of hyppsarrthymia EEG from children with infantile spasms.

Jefferson Medel, BS/MS Computer Engineering student at the Rochester Institute of Technology (summer 2015). Project: Dictionary Learning and its versatility and applicability regarding different modes of classification.

Sriram Kumar , M.S. in Electrical Engineering at Rochester Institute of Technology (summer 2015). Project: Discovering discriminative dictionaries for robust signal classification.

Ryan Selby, Electrical Engineering student at the Rochester Institute of Technology, (Summer 2015). Project: The examination of cardiac surface unipolar electrograms in conjunction with ECG T-wave alternans.

Anup Jonchhe, Biomedical Engineering undergraduate student at the Rochester Institute of Technology (Summer 2015). Project: The Design and construction of an ECG data acquisition chamber for ex vivo rabbit hearts sustained through the Langendorff system.

Erik Messier, Biomedical Engineering undergraduate at the Rochester Institute of Technology (summer 2015). Project: Analysis of the relationship between Sudden Cardiac Death, and abnormalities in T-wave configurations.

Rachel Baumgarten, Biomedical Engineering undergraduate at the Rochester Institute of Technology (summer 2014). Project: Developing a sonification system that alerts patients of Paroxysmal Atrial Fibrillation through music.

Daniel Sinkiewicz, M.S. in Electrical Engineering at Rochester Institute of Technology (2013-2014). Thesis: Developed a novel method for extraction of neural response from cochlear implant auditory evoked potentials.

Mark Sterling, Postdoc, Rochester Institute of Technology, (2013-2014). Project: Characterization of cardiac arrhythmias by applying novel signal processing and learning analyses to physiological signals including the surface ECG.

Steven Ladavich, M.S. in Electrical Engineering at Rochester Institute of Technology (2013-2014). Thesis: Rate-independent detection of atrial fibrillation by statistical modeling of atrial activity.

Amy Zeller, Biomedical Engineering undergraduate, Rochester Institute of Technology (summer 2013). Project: Analysis of body surface mapping of T-wave alternans distribution in patients with myocardial scarring.

Baabak Mamaghani, M.S. in Electrical Engineering, Rochester Institute of Technology (2013). Thesis: Lead optimization for accurate atrial fibrillation detection using an ambulatory ECG recording device.

Andrew Tock, Biomedical Engineering undergraduate, Rochester Institute of Technology (summer 2013). Project: Minimization of cochlear implant stimulus artifact in deaf and hard-of-hearing individuals.

Alexander Martin, M.S. in Health Systems Administration, Rochester Institute of Technology (2012-2013). Project: Investigation of thermal imaging for Atrial Fibrillation treatment.

Brandon Micale, Biomedical Engineering undergraduate, Rochester Institute of Technology (fall 2012). Project: Evaluation of atrial fibrillation organization in left atrium.

Suba Seevaratnam, Biomedical Engineering undergraduate, Ryerson University (2008-2009). Project: Performed MATLAB coding for detection of Twave alternans in body surface mapping ECG recordings.

Mohammad Parahoo, Biomedical Engineering undergraduate, Ryerson University and Sunnybrook Hospital (2009-2010). Thesis: Developed a Graphical User Interface (GUI) for the Research Interface Box (RIB2 Box) in cochlear implant research.

Angela Ip, Biomedical Engineering undergraduate, Ryerson University (summer 2008). Project: Developed C programing for Matching Pursuit analysis for detection of Twave alternans.