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CSE receives Three QRNF Academic Research Grants (ARG)
Our CSE department has just been awarded three Academic Research Grants (ARG) from the Qatar National Research Fund (QNRF) in its inaugural round. The three awarded projects are led by Prof. Amr Mohamed, Prof. Somaya Almaadeed, and Dr. Ahmed Badawy.
Here are more details about the awarded projects:
The PervasiveAeroAgents platform’s primary objectives are designed to address important challenges facing disaster scenarios, including 1) establishing the system architecture and describing coordinated multi-drone features such as sensing specifications, wireless charging, intelligent detection algorithms, and autonomous navigation. 2) Developing AI-based computer vision techniques using machine learning, to detect and identify objects and individuals among the debris, while using Reinforcement learning (RL) and online learning (OL) techniques for autonomous navigation, speeding up search and rescue operations in stochastic and highly changing environments. 3) Developing new security protocols suitable for dynamic ad hoc group communications amongst the drones to guarantee integrity and confidentiality. Finally, 4) build a comprehensive proof-of-concept using digital twin technology to demonstrate system features and insure the efficacy of the proposed sensing and AI-based techniques for group ad hoc communication.
Project abstract: Cancer, which has been identified as a significant public health issue in Qatar and worldwide, can be diagnosed early and accurately with the help of biomedical imaging. It is true that there has been a significant increase in cases of breast, thyroid, colon, prostate, lung, and stomach cancer over the past five years [1]. For instance, Qatar has one of the highest rates of female breast cancer incidence and mortality when compared to the other Middle Eastern regions. In Qatar, the latest Qatar National Cancer Registry (QNCR) report of 2020 revealed that breast cancer had the highest incidence among all types of cancers. It accounted for 37% of all cancer cases, with 218 new cases reported. Colorectal cancer ranked second among female cancers, comprising 10.7% of cases with 62 reported instances. Thyroid cancer held the third position, representing 7.2% of female cancer cases with 42 reported cases [2]. Due to a variety of factors, including lifestyle choices, environmental effects, and other factors, there are an increasing number of cases of breast cancer in Qatar and the surrounding nations. Imaging and biomedical imaging techniques, such as histology image [3], and/or positron emission mammography (PEM) for breast cancer screening [4], are frequently used by caregivers to accurately detect the spread of cancer in the human body. To locate, segment, and categorize malignant tumors, these biomedical imaging approaches rely on image processing and Artificial Intelligence (AI) [4]. Both AI and computational imaging and analytics for cancer detection layer of these imaging approaches are not sufficient to provide accurate diagnose of cancer and doctors do not understand the science behind the result. Therefore, we need a much smarter way to explain and hence link the results to the clinical data. Together with medical doctors in Qatar and UAE we aim to develop new tools and techniques for multimodal breast tumor classification based on integrative data analysis from imaging and clinical data including histopathological and OMICs. We aim to develop explainable AI tools to outline how the AI produced a certain result. AI can be used as a support system that scans image and process corresponding clinical data by extracting the areas, features, or data with a high probability of cancer to simplify a doctor’s job and provide additional hints for medical care and competence. Furthermore, this proposal aims to decipher the molecular pathogenesis of breast cancer using artificial intelligence through integration of histopathological images and OMICs data from different breast cancer subtypes. Multimodal data fusion of morphology, gene expression, and DNA mutations using IHC and OMICs technology has yet to be explored in depth. Implementing this approach using AI and Deep Learning (DL) can lead to a more accurate diagnosis of the disease and timely treatment. This will improve their overall survival and decrease the economic burden of breast cancer.
Project abstract: The Open Radio Access Network (O-RAN) is on track to completely transform the telecommunications ecosystem in the coming decade. O-RAN specifications are expected to drive 50% of RAN-based revenues by 2028 for public networks and by 2027 for enterprise and industrial cellular segments and will exceed traditional RAN by 2030. This research proposal aims to investigate and develop a reliable O-RAN framework for time-critical and high-resource-demanding healthcare applications.
CSE faculties win the best paper award at IWCMC23
A collaborative team including two CSE faculty members has received the best paper award at the International Wireless Communications and Mobile Computing Conference (IWCMC23), held in Marrakesh, Morocco, between June 19-23, 2023. The awarded paper is titled “Real-time Imitation of Autonomous MCG Node using Dual ECG Probing IoT Node Suitable for Delivery by UAV”, and co-authored by Dr. Khalid Abualsaud and Dr. Elias Yaacoub from our department.
The paper is an outcome of research project NPRP13S-0205-200270 from the Qatar National Research Fund (QNRF) led by Dr. Khalid Abualsaud. The work was done in collaboration with Prof. Tamer Khattab (Dept of Electrical Engineering at QU) with medical advice from collaborators from Al-Ahli Hospital (a partner in the project) and the New York Presbyterian Hospital.
The work consists of building a testbed that uses electrocardiography (ECG) signals to generate magnetocardiography (MCG)-like signals, which can be used for various heart disease detection, including arrhythmia. A working prototype is built with weight and dimensions suitable to be carried by drones, for delivery to remote areas lacking medical infrastructure, e.g., in disaster recovery scenarios.”
CSE Faculty Awarded QJRC Grant
Dr. Mohammed Al-Sada, assistant professor at our department, and his team has been awarded a Qatar-Japan Research Collaboration (QJRC) cycle2 grant for the project titled: “A Versatile Telexistence System with Implicitly Assistive Telemanipulation Capabilities”.
QJRC, funded by Marubeni, brings together Qatar University and Japanese Universities to collaborate on research topics of mutual interest and develop high-quality, high-impact outcomes and prototypes that benefit both parties. QJRC paves the way for sustainable cooperation and helps, in a concerted manner, to fulfill the knowledge-based economy aspiration of Qatar.
The project’s team includes:
– LPI: Mohammed Al-Sada, Qatar University, Doha, Qatar.
– LPI: Prof. Tetsuya Ogata, Waseda University, Tokyo, Japan.
– PI: Prof. Tatsuo Nakajima, Waseda University, Tokyo, Japan
– PI: Dr. Osama Halabi, Qatar University, Doha, Qatar.
– PI: Dr. Faisal Al-Jaber, Qatar University, Doha, Qatar.
– PI: Dr. Sarada Prasad Dakua, Hamad Medical Corporation, Doha, Qatar
– PI: Dr. Pin-Chu Yang, Waseda University, Tokyo, Japan
– PI: Mr. Abdulla Iskandar, Waseda University, Tokyo, Japan
– PI: Mr. Naoki Hashimoto, Waseda University, Tokyo, Japan.
– Consultant: Dr. Yamen Saraiji, Sony AI, Tokyo, Japan.
Here is the project’s abstract:
In recent years, Qatar has faced pressing challenges in knowledge exchange and collaboration with the world across industrial and educational sectors. In response to such challenges, we fabricated a wearable telexistence system that can be used for knowledge transfer and remote collaboration tasks as part of QJRC-1. This proposal builds upon our system by addressing its key limitations through two main objectives. First, we propose a novel robot formfactor that enables the wearable robot to dock into a mobile robotic platform, that we called the Yorishiro system. This system provides stability, power, and enables using the robot in three Modes: i) Wearable Telexistence Mode: the robot is a fully worn system. ii) Augmented-Wearability Mode: the robot is worn by a surrogate user while attached to the Yorishiro System. iii) Mobile Telexistence Mode: the robot is completely independent from surrogate users and is a fully mobile system. Therefore, the Yorishiro system significantly increases the reliability and stability of the robotic system, and extending its usage and deployment domains for industrial and medical contexts.
The second objective is concerned with increasing the efficiency and accuracy of telemanipulation task by developing an implicitly assistive telemanipulation system for telexistence (ATX). Our ATX system mainly focusing on helping the robot operator to grasp tools with consideration to their affordances through deep learning based detection and motion generation method. ATX implicitly assists users by compensating operational errors during telemanipulation, thereby maintaining embodiment over the robot that is necessary to telexistence. The contributions of these objectives are significant, as we explore efficient novel formfactors for telexistence systems, and integrate assistive methods to ensure operational efficiency of the robot. To the best of our knowledge, these objectives have not been explored in any previous research, and advance the state of the art in telexistence systems.
CSE teams win four medals at International Invention Fair in the Middle East
Three inventions from Computer Science and Engineering (CSE) department won advanced awards in the 13th IIFME –International Invention Fair of the Middle East hosted in Kuwait. Dr. Khalid Abualsaud and his team have received a golden medal, while Prof. Sumaya Al-Maadeed and her team have received another golden medal and two bronze medals.
The fair was organized from the 12th to 15th of February 2023 by Kuwait Science Club under the Patronage of His Highness, the Emir of Kuwait, Sheikh Sabah Al-Ahmad Al-Jaber Al-Sabah, and in collaboration the International Federation of Inventors’ Associations (IFIA), World Intellectual Property Organization (WIPO), UNESCO, and the International Exhibition of Inventions of Geneva. This unique convention in the Middle East was received with great importance locally, regionally, and internationally. It highlighted the inventions, innovations, and creativity of youths and universities.
Dr. Khalid Abualsaud and his team have won the golden medal on an invention resulted from the CSE Senior Design Project (SDP) 2021/2022. Other colleagues from our department as well as the Department of Electrical Engineering have contributed to improve the work. The invention was filed under QU tracking code QU2022-022 and reporting U.S. Provisional Patent Application No. 63/421, 416 filed November 1, 2022. Ref: 432743.10335 [I-AMS.FID5168591] in the United States Patent and Trademark Office (USPTO). The system aims for continuous accurate blood glucose monitoring in a non-invasive manner. The current idea is that the device continuously measures blood sugar and notifies the patient in case of a significant increase in blood sugar that exceeds the limit of normal sugar level, or in case it drops below the limit.
The team of the project consists of the following members:
Contributor(s) Name(s) | Affiliation |
|
Mazun Alshahwani, | Graduate Student, Dept. of Computer Science and Engineering, College of Engineering, Qatar University. |  |
Noora Al Bordeni, | Graduate Student, Dept. of Computer Science and Engineering, College of Engineering, Qatar University. |  |
Fatima Al-Kaabi, | Graduate Student, Dept. of Computer Science and Engineering, College of Engineering, Qatar University. |  |
Sara Al-Mohannadi, | Graduate Student, Dept. of Computer Science and Engineering, College of Engineering, Qatar University. | |
Khalid Abualsaud | Lecturer of Computer Engineering, Dept. of Computer Science and Engineering, College of Engineering, Qatar University. |  |
Muhammad E. H. Chowdhury | Assistant professor Dept. of Electrical Engineering, College of Engineering, Qatar University. |  |
Associate professor Dept. of Computer Science and Engineering, College of Engineering, Qatar University. |  | |
Nizar Zorba | Professor, Dept. of Electrical Engineering, College of Engineering, Qatar University. |  |
CSE Team Wins Best Poster Award at ISID 2023
A CSE team led by Dr. Mohammed Al-Sada and Dr. Osama Halabi has received the Best Poster Award at the 3rd International Symposium of Intelligence Design (ISID 2023). The award was given for the poster paper titled “Virtual Reality Wearable Telexistence System Deployment and Evaluation Environment“.
The project is part of a collaboration between Qatar University and Waseda University. The research team includes Ms. Fatima Al-Yafei, Ms. Eman Al-Shaer, Ms. Bushra Alarqaban, Ms. Muneera Al-Yousef, Ms. Lujan Hayajneh, Mr. Abdulla Iskandar, Prof. Tatsuo Nakajima, Dr. Osama Halabi, and Dr. Mohammed Al-Sada.
The poster work is part of a larger project that explores using a VR based environment for the deployment and evaluation of wearable robotic systems, with emphasis on human-robot interaction in various contexts of use.
CSE Team Wins Best Paper Award at BIOSIGNALS 2023
A team from our CSE department has received the Best Paper Award in the 10th International Conference on Bio-inspired Systems and Signal Processing (BIOSIGNAL2023) conference with a paper titled “Wearable Data Generation Using Time-Series Generative Adversarial Networks for Hydration Monitoring”. The team includes Farida Sabry, Dr. Wadha Labda (LP), Eng. Tamer Eltaras, Ms. Fatima Hamza, and Dr. Qutaibah Malluhi. in collaboration with Dr. Khawla Elzoubi from Community College of Qatar.
BIOSIGNAL 2023 brought together researchers and practitioners from multiple areas of expertise working at the intersection of engineering, mathematics, statistics, computer science, data science, biology and medicine, who develop and apply algorithmic tools, models and techniques to solve challenging problems in biology and medicine. A diversity of signal types can be found in this area, including video, audio, electrophysiological signals, medical imaging, and other biological sources of information. The analysis and use of the diverse types of data seem across these applications often requires cross-disciplinary expertise and collaborative efforts and this conference aims to be a high quality forum to celebrate many of these ongoing interactions and research efforts.
Paper Abstract: Collection of biosignals data from wearable devices for machine learning tasks can sometimes be expensive and time-consuming and may violate privacy policies and regulations. Successful and accurate generation of these signals can help in many wearable devices applications as well as overcoming the privacy concerns accompanied with healthcare data. Generative adversarial networks (GANs) have been used successfully in generating images in data-limited situations. Using GANs for generating other types of data has been actively researched in the last few years. In this paper, we investigate the possibility of using a time-series GAN (TimeGAN) to generate wearable devices data for a hydration monitoring task to predict the last drinking time of a user. Challenges encountered in the case of biosignals generation and state-of-the-art methods for evaluation of the generated signals are discussed. Results have shown the applicability of using TimeGAN for this task based on quantitative and visual qualitative metrics. Limitations on the quality of the generated signals were highlighted with suggesting ways for improvement.
