BSIA Lab Members
Present Graduate/Undergraduate Students
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
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 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.
Olamilekan Banjo is pursuing his PhD in Computer Science(Data Science and Analytics) at Florida Atlantic University. His research interest is in spiking neural networks and their applications to IoMT. He is currently working on how to enhance models deployed on medical devices. Olamilekan received his MSc in Thermal Power(Gas Turbine Technology) from Cranfield University, UK and his BSc in Mechanical Engineering from Obafemi Awolowo University, Nigeria. Contact: Olamilekan Banjo
Johnny Forde is pursuing a PhD in Computer Science at Florida Atlantic University with research interests in biomedical engineering and robotics. His diverse work experience includes teaching engineering, designing medical devices for structural heart disease, and consulting in the biopharmaceutical space, advising scientific and commercial strategy for top global biopharma firms. He is currently applying novel transformer architectures to improve real-time monitoring of motor symptoms in Parkinson's disease patients. He earned his BSE in Bioengineering and MSE in Mechanical Engineering and Applied Mechanics from the University of Pennsylvania (Philadelphia, PA). Contact: Johnny Forde
Abhishek Singh Kushwaha is pursuing a master's in computer science at FAU, with 3 years of experience in full-stack web development. His project, Biometric Authentication using ECG Signals with Fully Homomorphic Encryption, focuses on developing a secure and privacy-preserving system for authenticating individuals based on their unique electrocardiogram (ECG) signals. The system leverages fully homomorphic encryption (FHE) to enable the processing and analysis of ECG data in an encrypted format, ensuring that sensitive biometric information remains protected even during computation. By using ECG signals, which are difficult to replicate and specific to each individual, the project aims to provide a reliable, secure method of authentication, particularly suited for applications where data privacy is critical, such as healthcare or secure access systems. Contact: Abhishek Singh Kushwaha
Akhilesh Singh Kushwaha is pursuing his Master's in Computer Science at Florida Atlantic University and has two years of experience in ETL testing and bank reconciliations. His research interests are biomedical signal processing, machine learning and cryptography. His project explores the use of EEG signals for biometric authentication, focusing on security and privacy. By applying Fully Homomorphic Encryption (FHE), his system ensures that EEG data remains encrypted throughout processing, maintaining the confidentiality of sensitive information. Contact: Akhilesh Singh Kushwaha
Sonia Sohail is an undergraduate sophomore pursuing a BS in Computer Engineering with a minor in Mathematics. Her interests are biomedical signal processing, machine learning, and computer vision. She is currently working on applying human pose estimation methods and machine learning to quantify dyadic synchrony in parent-infant interactions. This project is co-advised by Dr. Teresa Wilcox. Contact: Sonia Sohail
Jossaya Camille is a senior at FAU High School, pursuing a Bachelor of Science in Computer Engineering. He has worked as a Precalculus Learning Assistant, assisting students with complex mathematical concepts. With research interests in AI, computer vision, and data analytics, Jossaya is currently working on a project focusing on human pose estimation for gait analysis, with applications in rehabilitation for those suffering from cognitive disorders. Contact: Jossaya Camille
Hunter Lauritano is an undergraduate student pursuing a B.S. in Electrical Engineering and a minor in Mathematics. Previously, he has engaged in consulting work in the field of Electrical Engineering, and his current research aims to leverage machine learning and computer vision techniques for 3D human pose estimation to improve gait analysis and its applications in diagnosing cognitive disorders. Contact: Hunter Lauritano
Past Students
Jasmine Chan, Ph.D. in Experimental Psychology at Florida Atlantic University (2024). Co-Advised. Dissertation: Purchase Intention After Exposure To Same Versus Different Attributes of Brand-Name Products: an fNIRS Study. Read Here.
Shelly Davidashvilly, BS Computer Science, Florida Atlantic University (2022). Project: Developing machine learning models to recognize activity data from wearable body sensors on Parkinson's patients.
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.