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I received a PhD in Computer Science from Carleton University in 2010 and a Master of Science and Information System Science from Carleton University in 2003. Prior to joining Laurier, I was a full-time analyst/developer at the Canada Federal Goverment for 10 years, a partial professor at Algonquin College for three years and an instructor at Carleton University.
At Canada Federal Goverment, I worked as a:
My research interest spans multiple computer science fields. These include software engineering, mobile and smart TV apps, semantic web, software fault-tolerance, natural language processing (NLP) and text mining, peer-to-peer systems, distributed computing, and business intelligence(BI).
Below are summaries of the three prime projects that I am currently working on and the research areas that I am interested in:
Industry grant: $7,500.00 - HH Angus & Associates. Research area: Machine Learning and Computer Vision.
Startup research fund: $50,000.00, Wilfrid Laurier University
Research fund (LTA): $10,000.00, Wilfrid Laurier Univeristy
I have research opportunities for undergraduate and gradate students interested in mobile applications, NLP and text mining. I am willing to supervise undergrad/graduate students in the area of software engineering, mobile application, NLP, machine learning, and image procesisng.
Algonquin College, Faculty of Information and Communication Technology
Create an app architecture with a user interface structured around a modular design, leveraging the principles of inheritance and subclassing. This approach enhances code organization, promotes reusability, and facilitates the management of distinct components within the app.
Engineer a comprehensive application designed to automate the testing process for assignments. This tool aims to streamline and optimize the evaluation of assignments by employing automated testing procedures, ensuring efficiency and accuracy in the grading process.
Design an environmentally conscious application that incorporates machine learning capabilities on mobile devices. This green app focuses on leveraging machine learning algorithms to enhance energy efficiency, optimize resource usage, and contribute to a more sustainable and eco-friendly mobile technology landscape.
Create a sophisticated app architecture tailored for the presentation and analysis of data. The architecture provides users with an intuitive and interactive ability to visualize and interpret data, fostering a seamless experience for data-driven decision-making.
Build a robust application for File Input/Output (I/O) operations specifically optimized for Android devices. This app ensures efficient and secure handling of files, offering users a seamless experience in managing, accessing, and organizing data on their Android devices.
Engineer an application with the capability to monitor, report, and control the resources, including storage space and CPU usage, consumed by other installed apps on mobile devices. This tool empowers users to manage and optimize their device's performance by efficiently allocating resources.
The goal of this project is to develop a state-of-the-art live-streaming Android application that leverages URL streaming technology. This app will enhance user convenience and flexibility by consolidating preferred radio stations, TV stations, or local media files and transforming Android devices into a portable entertainment hub.
In this innovative project, we aim to develop two cutting-edge educational chatbots, leveraging the power of on-device machine learning technology. These chatbots will serve distinct roles, with one specifically designed as a Student Advising Tool and the other as a Classroom Teaching Assistant.
Using on-device machine learning, the chatbot will provide personalized guidance and support to students navigating their academic journeys. the chatbot will assist in course selection, offer insights into academic pathways, and provide real-time information on educational resources. The on-device machine learning capabilities ensure that the chatbot can adapt and refine its recommendations based on individual student needs and academic progress.
Book Title
Android for Java Programmers
Authors
Abdul-Rahman Mawlood-Yunis
DOI
https://doi.org/10.1007/978-3-030-87459-9
Publisher
Springer Cham
Softcover ISBN
978-3-030-87458-2
Published: 25 June 2022
eBook ISBN
978-3-030-87459-9
Published: 24 June 2022
Edition Number
1
Number of Pages
XXIV, 640
https://www.springer.com/us/book/9783030874582
For information on our certificate in Computer Science program visit this link:
https://wlu.ca/programs/?filter=faculty-of-sciencehttps://bohr.wlu.ca/ccs.htm
Contact Info:
Office hours: By appointment.
Languages spoken: English, Kurdish, Arabic, Farsi