Murtadha Hssayeni

Research Scientist, University of Technology, Iraq - Florida Atlantic University, USA.

Research Expertise

Signal Processing
Artificial Intelligence
Deep learning
Information Systems and Management
Information Systems
Computer Science Applications
Instrumentation
Atomic and Molecular Physics, and Optics
Biochemistry
Analytical Chemistry
Electrical and Electronic Engineering
Health Informatics
Biomedical Engineering
Biophysics
Hardware and Architecture
Computer Networks and Communications
Radiological and Ultrasound Technology
Biomaterials
Radiology, Nuclear Medicine and imaging
Health Information Management
Biotechnology
Neurology (clinical)
Cardiology and Cardiovascular Medicine

Legacy Map

Full View

Publications

Intracranial Hemorrhage Segmentation Using a Deep Convolutional Model
Data
2020
Distracted Driver Detection: Deep Learning vs Handcrafted Features
Electronic Imaging
2017
Wearable Sensors for Estimation of Parkinsonian Tremor Severity during Free Body Movements
Sensors
2019
Deep Learning Methods for Abnormality Detection and Segmentation in Computed Tomography and Magnetic Resonance Images
Unknown Venue
Detection of mild cognitive impairment and Alzheimer’s disease using dual-task gait assessments and machine learning
Biomedical Signal Processing and Control
2021
Automatic assessment of medication states of patients with Parkinson's disease using wearable sensors
2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
2016
Assessment of response to medication in individuals with Parkinson’s disease
Medical Engineering & Physics
2019
The forecast of COVID-19 spread risk at the county level
Journal of Big Data
2021
Multi-Modal Physiological Data Fusion for Affect Estimation Using Deep Learning
IEEE Access
2021
Ensemble deep model for continuous estimation of Unified Parkinson’s Disease Rating Scale III
BioMedical Engineering OnLine
2021
Dual-Task Gait Assessment and Machine Learning for Early-detection of Cognitive Decline
2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
2020
Dyskinesia estimation during activities of daily living using wearable motion sensors and deep recurrent networks
Scientific Reports
2021
Dyskinesia Severity Estimation in Patients with Parkinson’s Disease Using Wearable Sensors and A Deep LSTM Network
2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
2020
Multilevel Features for Sensor-Based Assessment of Motor Fluctuation in Parkinson's Disease Subjects
IEEE Journal of Biomedical and Health Informatics
2020
Symptom-based, Dual-channel LSTM Network for The Estimation of Unified Parkinson's Disease Rating Scale III
2019 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI)
2019
Activity Recognition in Parkinson's Patients from Motion Data Using a CNN Model Trained by Healthy Subjects
2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
2022
Tensor Decomposition of Functional Near-Infrared Spectroscopy (fNIRS) Signals for Pattern Discovery of Cognitive Response in Infants
2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
2020
Activity-independent detection of mediation states in individuals with Parkinson’s disease using wearable sensors (P2.8-004)
Neurology
2019
Dyskinesia Estimation of Imbalanced Data Using a Deep-Learning Model
2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
2022
Using Conditional Generative Adversarial Networks to Boost the Performance of Machine Learning in Microbiome Datasets
Proceedings of the 1st International Conference on Deep Learning Theory and Applications
2020
Continuous Parkinsonian Tremor Estimation Using Motion Data
2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP)
2019
A NON-INVASIVE, AFFORDABLE AND ACCURATE DEVICE FOR ASSESSMENT OF LEFT VENTRICULAR SYSTOLIC DYSFUNCTION
Journal of the American College of Cardiology
2023
Exploring the feasibility of tensor decomposition for analysis of fNIRS signals: a comparative study with grand averaging method
Frontiers in Neuroscience
2023
ECG Fiducial Point Localization Using a Deep Learning Model
2022 21st IEEE International Conference on Machine Learning and Applications (ICMLA)
2022
Multidimensional Analysis of Functional Near-Infrared Spectroscopy (fNIRS) Signal using Tucker Decomposition
2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC)
2022
Interconnectivity of Deep Learning Models in AI-Driven Design Systems
Design Computation Input/Output 2022
2022
The Forecast of COVID-19 Spread Risk at The County Level
Unknown Venue
2021
Hybrid Feature Extraction for Detection of Degree of Motor Fluctuation Severity in Parkinson’s Disease Patients
Entropy
2019
Deep Learning for Medication Assessment of Individuals with Parkinson’s Disease Using Wearable Sensors
2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
2018
Parkinson's disease medication state management using data fusion of wearable sensors
2017 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI)
2017

Education

Florida Atlantic University

Ph.D., Computer Engineering

Boca Raton, Florida, United States of America

Rochester Institute of Technology

M.Sc., Computer Engineering

Rochester, New York, United States of America

Experience

Florida Atlantic University

Research Assistant / August, 2018 — Present

University of Technology- Iraq

2013 — Present

Join Murtadha on NotedSource!
Join Now

At NotedSource, we believe that professors, post-docs, scientists and other researchers have deep, untapped knowledge and expertise that can be leveraged to drive innovation within companies. NotedSource is committed to bridging the gap between academia and industry by providing a platform for collaboration with industry and networking with other researchers.

For industry, NotedSource identifies the right academic experts in 24 hours to help organizations build and grow. With a platform of thousands of knowledgeable PhDs, scientists, and industry experts, NotedSource makes connecting and collaborating easy.

For academic researchers such as professors, post-docs, and Ph.D.s, NotedSource provides tools to discover and connect to your colleagues with messaging and news feeds, in addition to the opportunity to be paid for your collaboration with vetted partners.

Expert Institutions
NotedSource has experts from Stanford University
Expert institutions using NotedSource include Oxfort University
Experts from McGill have used NotedSource to share their expertise
University of Chicago experts have used NotedSource
MIT researchers have used NotedSource
Proudly trusted by
Microsoft uses NotedSource for academic partnerships
Johnson & Johnson academic research projects on NotedSource
ProQuest (Clarivate) uses NotedSource as their industry academia platform
Slamom consulting engages academics for research collaboration on NotedSource
Omnicom and OMG find academics on notedsource
Unilever research project have used NotedSource to engage academic experts

Connect with researchers and scientists like Murtadha Hssayeni on NotedSource to help your company with innovation, research, R&D, L&D, and more.