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CSE faculties and students awarded at CENG 2024 End of Year event
The College of Engineering held its End of Year event on May 28, 2024, where several CSE faculty members and students were honored with awards.
The graduation projects competition of all engineering senior students was part of the CENG End of Year event. The competition included two categories: Best Project Design and Best Project Marketing Presentation. The first place in the Best Project Design category was awarded to the project titled “Vaultexe/OSS Zero-knowledge Self-hosting Password Manager” from the Computer Science program. This project was created by students Ahmed Abdou, Husam Snober, Mohammed Saqallah, and Walid Ben Ali, under the supervision of Dr. Moutaz Saleh.
In the Best Project Marketing Presentation category, the third place was awarded to multidisciplinary graduation project titled “Q-SAR: Drone Swarm for Disaster Management”. The team included students Ali Yasser Ali Abdolwahab , Abdalla Mostafa Shaaban , and Assem Malek Alnajjar from Computer Engineering Program. Moslem Yaser A Al- Qawasmi, and Yaman Yasser Kutmawi from Computer Science Program, Khaled Abdelrazak Khaled, Khaled J L Barakah, Omar Hakam Ahmad, and Abdullah Khalid AL Mawed from Electrical Engineering Program. The project is supervised by Prof. Amr Mohamed, Dr. Wadha Labda, and Prof. Ahmed Massoud.
The Dean’s Awards for the academic year 2023-2024 were also presented. Prof. Junaid Qadir received the Dean’s Award for Research, and Dr. Saleh Al-Hazbi was honored with the Dean’s Award for Teaching. Additionally, Dr. Mohammed Saleh and Prof. Elias Yaacoub were recognized as internal judges for the Best Prototype and Most Creative Design competition.
Lastly, Dr. Hazem Kemal was acknowledged by the College of Engineering for the completion of his tenure as a visiting professor in the CSE department.
Congratulations to all of the awarded CSE students and faculties!
CSE SDP Contest Day 2024: All Winners
The highly anticipated senior projects’ presentations took place on May 6th at the state-of-the-art new engineering building H07. These remarkable projects, the culmination of tireless efforts by talented students, were subjected to rigorous evaluation by industry examiners. After careful deliberation, outstanding projects from each program, Computer Science (CS) and Computer Engineering (CE), emerged victorious. Exceptional teams of these winners will be chosen to proudly represent our department in the upcoming college contest. We eagerly anticipate the success that awaits our representatives as they compete at the college level, confident in their abilities, to make our department proud once again.
Winning Projects in CSE-SDP23 Contests Day
CE Rank 1
Project title: Q-SAR: Drone Swarm for Disaster Management
Students: Ali Elmancy, Abdalla Ahmed, Assem Alnajjar
Supervisor: Dr. Amr Mohamed
Abstract:
- SAR operations face difficult environments.
- Drones offer faster and more effective SAR missions.
- Design a drone system to enhance SAR missions.
- Radar sensors are used for under-rubble survivor detection.
- Leverage autonomous smart drones.
- Drone assembly and sensor integration.
- Design a wireless charging stations for drones.
- Develop a backend for ground control and monitoring.
CE Rank 1 (equally-ranked)
Project title: Marathon Monitoring System
Students: Aly Okasha, Mohammad Rayyan, Ibrahim koubeisi
Supervisor: Dr. Noora Fetais
Abstract:
The challenges in marathon organization, in particular participant safety and data collection. We’ve evolved a product to track participant positions, detect cheating, identify fainting, and easily transmit data to event administrators.
CE Rank 2
Project title: NABATEQ: Plant Health Monitoring System
Deep Learning Classification Approach
Students: Amro Moursi , Mohamed Tahar, Malek Hamad, Hamad Alansi
Supervisor: Dr. Uvais Qidwai
Abstract:
This project focuses on the development and implementation of an advanced plant health monitoring system. Our approach involves addressing the critical environmental factors essential for preserving plants’ well-being, including temperature, soil moisture, water levels, humidity, as well as the presence of essential nutrients like Nitrogen, Phosphorus, and Potassium.
Central to our methodology is the utilization of computer vision technology with Artificial Intelligence to provide health ranks for the plants under monitoring. By leveraging this data-driven approach, our system aims to provide precise and timely insights into the overall health and well-being of plants, offering a valuable tool for effective plant care and management.
CE Rank 3
Students: Abeer Madyar , Kawther Ahmed, Leen Alinsari, Razan Abdelgalil
Supervisor: Dr. Mohammed AlSada
CS Rank 1
Project title: Vaultexe/OSS Zero-knowledge Self-hosting Password Manager
Students: Ahmed Ashraf, Husam Snober, Mohammed Saqallah, Walid Ben Ali
Supervisor: Dr. Moutaz Saleh
Abstract:
In this digital age, we rely on passwords to protect our online presence on the web. With so many passwords to memorize, we experience password fatigue and easily fall into the trap of reusing weak passwords across different sites. This is a serious security risk, as a single compromised password can give attackers access to many other accounts. To address this issue, we introduce Vaultexe, an open-source self-hosted zero-knowledge password manager.
CS Rank 2
Project title: PassGuard
Students: Youssef Aly, Essa Ahmed Kamel Abou Jabal, Mohamed-Dhia Abdaoui, Khalifa Yousuf
Supervisor: Dr. Mohammad Saleh
Abstract:
The importance of a password in today’s world cannot be overstated. Unfortunately, a large number of people falls victim to data breaches because of their reliance on weak passwords, default passwords, reused passwords. It can be explained by a simple reason: it is more convenient for the general public to use predictable passwords and reuse them.
Here comes PassGuard, an offline password manager application, whose sole purpose is to provide password security and user convenience.
CS Rank 3
Project title: ReWisely: a ChatGPT-based comprehensive revision platform for generating user-personalized study materials
Students: Amani Mamiche, Asma Bahabarah, Khadija Khedr, Taqwa Ellabad
Supervisor:Dr. Moutaz Saleh
Abstract:
Our project aims to modernize the creation of revision material by integrating AI into a comprehensive, interactive, customized, and user-friendly web application. It focuses on developing a platform capable of handling vast amounts of data and offering assistance through text summarization, flashcards, question extraction, the Feynman technique, and mind-mapping functionalities.
CSE Senior Students Participate at 11th Agricultural Technologies Conference and Exhibition
A team of CSE senior students have participated in the 11th Agricultural Technologies Conference and Exhibition. The team includes Amro Moursi , Mohamed Tahar, Malek Hamad, and Hamad Alansi, who are working under the supervision of Dr. Uvais Qidwai on their senior project titled “NABATEQ: Plant Health Monitoring System Deep Learning Classification Approach”. The students project is featured at the exhibition until 27/2/2024 as part of Qatar Expo. The event cumulates a number of innovations, products, and companies that have brought a variety of technologies to assist in making the agricultural growth more sustainable, profitable, and viable for food security initiative from Qatar Vision 2030.
The student project focusses on the use of IoT technologies for sensory measurements and utilizes custom-cloud solutions for the implementation of the whole system. Artificial Intelligence has been deployed in providing meaningful feedback to the process controllers related to the plants’ health using optical and IR images.
The group was invited as a special exhibitor by the conference organizers due to its merit and importance in the overall food security efforts.
Wishing the team all the best!
Humanitarian Drone Competition by CSE Students
The CSE department has organized an “Humanitarian Drone Competition” as part of the course project for the “Computer Engineering Practicum” course..
The motivation for this year’s project is to show solidarity with people in Gaza. Unlike typical control circuits used in the drones, the students of the course were asked to design a control circuit for the drone with only passive electronic components and basic IC to control the motors of the drones. In order to achieve this, the students had to go through phases of idea description, schematic design, breadboard prototyping, and a final soldered prototype that has to have at least three functionalities that can assist the humanitarian mission.
The winning drones were judged based on their design, number of functionalities incorporated in the design, A4 poster and a video montage of their work carried out during the project.
The winners in the competition were:
Male Students
- First place: Yusuf Siddiqui, Iheb Zouari, Mohamed Ali, Mahmoud Ali
- Second place: Mubarak AlHajri, Abdulrahman Marwan Aboumadi, Ahmed Miqdad, Deya Aldeen Abdelbaset
- Third place: Muhammad Khan, Abdullah Irhimeh, Laith Nasrallah
Female Students
- First place: Isra Ali, Yoma Mohammed, Maya Attia, Nooralhodaa Elshawadfy
- Second place: Roaa Shady, Noha Elgamal, Amna Al-Ahmed
- Third place: Aisha Al Mannai, Naema Al Abdulla, Hila Al Dosari, Fatima Al Ali
The competition was judged by our faculty members Eng. Amelle Bedair , Eng. Farah E-Qawasma and Eng. Amal Elmasri. The prizes for the winners were awarded by the HoD Prof. Amr Mohamed.
Thanks Voltaat for sponsoring the prizes worth 2,000 QAR. Thanks to Dr. Wadha Labda for her kind support as well to make the awards ceremony in the ICET’23 events. Thanks for the course coordinator Eng. Naveed Nawaz, course instructors Eng. Leila Ghastli and Eng. Tamer Eltaras, and all other faculties for making this competition a successful one.
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.
QU Team Secures 3rd Place in ICPC Programming Competition, Earns Ticket to Egypt
In an impressive showing of skills and determination, a team of students from Qatar University has secured the third spot in the highly competitive Qatar Collegiate Programming Contest (QCPC), part of the International Collegiate Programming Contest (ICPC). Often regarded as the “Programming World Cup,” ICPC challenges teams to tackle algorithmic problems and devise programming solutions. The accomplished team, composed of Aly Soliman, Mohamed Fauzan, and Omar Elshenhabi, demonstrated remarkable programming skills and problem-solving abilities, earning them their place in the regional competition. Their achievement is a testament to their hard work and dedication in the field of programming.
The national stage of the competition (QCPC), hosted at Carnegie Mellon University-Qatar, provided a platform for teams across Qatar to go for a chance to advance to the regional level. This event served as a qualifying round for the Africa and Arab Regional Competition (ACPC), scheduled to be held in Egypt’s Sharm El Sheikh end of this year.
As they prepare to represent Qatar on the regional stage, the students are poised to compete among the top talents in the region. While they secured third place nationally, Qatar University takes pride in their accomplishment, and we eagerly anticipate their performance in Egypt. We extend our best wishes to the team and their coach, Hamza Saleh , as they prepare for the next phase of the ICPC.