Biography
Abedal-Kareem Al-Banna (also known as Karim) is a Jordanian academic, entrepreneur, and researcher with expertise in computer science, artificial intelligence, and speech technologies. He splits his professional life between Jordan and the United Kingdom, where he conducts advanced research in machine learning and speech disorders.
Al-Banna's career is defined by his dedication to bridging the gap between academic research and practical industry applications, particularly in the fields of artificial intelligence, speech processing, and healthcare technology. As both an educator and entrepreneur, he exemplifies the connection between theoretical research and real-world solutions.
His work in speech disorder detection, particularly stuttering, has potential to transform clinical applications for diagnosis and therapy. Through his startups and research initiatives, he continues to advance technological solutions that can improve people's lives.
Areas of Expertise
- Artificial Intelligence & Machine Learning
- Speech Processing & Disorder Detection
- Deep Learning Architectures
- Internet of Things (IoT)
- Geographic Information Systems (GIS)
- Robotics & Automation
- Healthcare Technology
Academic Background
PhD
Loughborough University, UK
PhD in Computer Science
Research focus: "A Deep Learning Model Based on Time Interval Annotation for Disfluency Detection for People Who Stutter"
Developing advanced deep learning approaches to detect stuttering events in speech signals using novel attention-based architectures and multi-feature fusion techniques.
Current
University of Petra, Jordan
Assistant Professor
Department of Data Science & Artificial Intelligence
Faculty of Information Technology
Research Focus
Speech Disorder Detection
My primary research focuses on developing computational methods for detecting and analyzing speech disorders, particularly stuttering. This involves:
- Automatic detection of stuttering events in continuous speech
- Development of novel deep learning architectures for speech processing
- Feature engineering for improved speech disorder detection
- Creating assistive technologies for people with communication disorders
AI and Machine Learning Applications
I work on applied artificial intelligence research focusing on:
- Convolutional and recurrent neural networks for signal processing
- Attention-based models for feature selection in heterogeneous data
- Multi-feature fusion approaches for improved model performance
- Domain adaptation techniques for robust AI systems
- Internet of Things (IoT) integration with AI systems
Current Research Project
Machine Learning Based Approaches to Automatic Stuttering Event Detection
This research investigates different ML/DL and feature engineering techniques for robust Stuttering Event Detection (SED) based on acoustic features that directly detect stuttering events from speech signals. The work includes developing atrous convolutional networks, attention-based models, and investigating the impact of time-domain features on detection performance. The ultimate goal is to create technologies that can provide automatic and objective stuttering assessment tools.
Selected Publications
A Novel Attention Model Across Heterogeneous Features for Stuttering Event Detection
Expert Systems with Applications (2024)
Authors: Abedal-Kareem Al-Banna, Hui Fang, Eran Edirisinghe
This paper introduces an attention-based model for improved stuttering event detection that leverages heterogeneous features and novel attention mechanisms.
View PublicationStuttering Disfluency Detection Using Machine Learning Approaches
Journal of Information & Knowledge Management (2022)
Authors: Abedal-Kareem Al-Banna, Eran Edirisinghe, Hui Fang, Wael Hadi
This paper rigorously investigates the effective use of eight well-known machine learning classifiers on two publicly available datasets for detecting stuttering events.
View PublicationStuttering Detection Using Atrous Convolutional Neural Networks
13th International Conference on Information and Communication Systems (ICICS) (2022)
Authors: Abedal-Kareem Al-Banna, Eran Edirisinghe, Hui Fang
This paper proposes a novel approach using atrous convolutional neural networks for stuttering detection directly from speech signals.
View PublicationIdentifying the Most Significant Features for Stress Prediction of Automobile Drivers: A Comprehensive Study
Journal of Information & Knowledge Management (2024)
Authors: May Y. Al-Nashashibi, Nuha El-Khalili, Wa'el Hadi, Abedal-Kareem Al-Banna, Ghassan Issa
This study identifies and analyzes key features for predicting stress levels in automobile drivers using machine learning techniques.
View PublicationDoctoral Thesis
Machine Learning Based Approaches to Automatic Stuttering Event Detection
Loughborough University (2023)
Comprehensive research on detecting stuttering events using various machine learning and deep learning methods, with a focus on innovative architectures and feature engineering approaches.
View ThesisEntrepreneurial Ventures
Deep Brain
Founder & CEO
A startup focused on developing cutting-edge artificial intelligence applications and solutions. Deep Brain combines academic research with practical industry applications to create innovative AI-powered products and services.
TAKALAM
Co-founder & CTO
A Jordanian startup providing innovative solutions for hearing and speech disorders. TAKALAM develops technologies to assist individuals with communication challenges, leveraging AI and speech processing algorithms to create assistive tools.
Leaders in Innovation Club
Founder
An organization dedicated to fostering innovation and technology development. The club provides resources, mentorship, and networking opportunities for aspiring entrepreneurs and innovators.
Patents & Innovations
Portable Neck Treatment Device (2018)
Co-invented with Majed Naser Albanna, Ghassan F. Issa, Ghiath Mhd Kheir Eriksousi, and Tamara Aljuboori. This medical device provides innovative approaches to neck treatment and therapy.
Awards & Recognitions
Leaders in Innovation Fellowship (2020)
Royal Academy of Engineering, United Kingdom
Awarded for innovative work in technology and entrepreneurship.
Best Software Idea in Jordan (2011)
Honored by King Abdullah II of Jordan
Recognized at an event in the Dead Sea, Jordan.
University of Petra Award for Best Inventor (2019, 2022)
University of Petra
For the patent on Portable Neck Treatment Device. Recognized twice for innovation contributions.
Best Inventors and Researchers in Jordanian Universities (2019)
Awarded by the Minister of Higher Education, Jordan
Ceremony held in Amman, Jordan.
LIF Community Grant (2020)
The Higher Council For Science and Technology and The Royal Academy of Engineering
Supported research and innovation activities.
Intel Award for Best IoT Device in the MENA Region (2015)
Recognized at an event in Lebanon
For innovation in Internet of Things technology.
Competition Awards with Students (2010-2020)
Mentored students to win over 30 national and international competitions including Microsoft Imagine Cup, Intel Challenge Me, and Amazon Hackathon.
Professional Affiliations
- Member of the Leaders in Innovation Fellowship community
- Research Affiliation with Loughborough University, UK
- Faculty member at University of Petra, Jordan
Contact Information
Academic Contact
abanna@uop.edu.jo
EXT NO.: 7310
Faculty of Information Technology
University of Petra, Jordan