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QU Ranked among Top 100 Universities Worldwide in Computer Science (THE 2023)

Qatar University has been ranked among the top 100 universities worldwide in Computer Science, according to Times Higher Education (THE) World University Ranking of 2023 that was just released. This is indeed a big achievement for our department. It is surely a result of years of active and hard work in planning, teaching, and research. Congratulations to all members!

QU’s rank has jumped this year over about 25 positions in THE CS subject ranking. With a steady progress over years, here are the CS ranks of QU since 2018:

  • 2018: 251-300
  • 2019: 201-250
  • 2020: 201-250
  • 2021: 101-125
  • 2022: 101-125
  • 2023: 95

 

CSE team secured first place in Qatar Datathon 2025

A CSE team, that includes current students and graduates, won the first place in the Qatar Datathon 2025, organized by the National Planning Council (NPC) in collaboration with Microsoft in Qatar. The team included Sidi Chaikh (Computer Science Student / UI/UX / Frontend Developer), Mohaned Massoud (Computer Science Student / Frontend Developer), Osama Hardan (Computer Science Student / Data Scientist / AI/ML Engineer), Ahmed Ashraf (AI Software Architect), and Youssef Aly (Cybersecurity Researcher).

The Datathon was a highly competitive event in which 35 teams participated, working on real-world challenges using data-driven solutions. Participants were provided with datasets and tasked with developing innovative insights to address critical issues related to national planning and development. The event aimed to encourage the use of data science and AI to drive impactful solutions for urban planning, resource optimization, and economic development.

Their winning project, Insighty, is a data analytics platform designed to provide policymakers and organizations with intelligent insights from large datasets. It leverages machine learning and advanced visualization techniques to simplify complex data, enabling better decision-making in urban planning, resource allocation, and economic development. The platform aims to bridge the gap between raw data and actionable strategies, making data more accessible and impactful.

We are proud of you!

CSE students/graduates secured first place in Qatar Datathon 2025

CSE Students Secure 2nd Place at CMU-Q Lifelines Hackathon 2025

CSE students from Qatar University has secured Second Place at the Lifelines Hackathon 2025, a three-week competition organized by students of Carnegie Mellon University in Qatar (CMU-Q) and sponsored by the Qatar Research, Development, and Innovation Council (QRDI). The team included Fatima Ahmed (Computer Science), Shada Ibrahim (Industrial Engineering, Minor in Computer Science), Ranya Merabet (Pharmacy), and Hala Subeh (Industrial Engineering, Minor in Computer Science).

The event started on 9th January 2025, and saw 63 teams from across Qatar that came together to develop cutting-edge solutions aimed at improving crisis management and emergency response.

Their proposed project, SalamTECH, is an advanced three-component system designed to streamline the triage process and enhance emergency communication. It integrates an AI-powered SOS alert system to assess patients in real-time, a live tracking feature for paramedics to optimize response efforts, and instant data access for emergency department staff to ensure seamless coordination. By enabling real-time data sharing, SalamTECH accelerates response times, minimizes miscommunication, and improves the accuracy of patient care, making it a game-changer in crisis management.

We are proud of you!

Team RXCoders celebrating their 2nd place in the Hackathon competition held by CMU-Q

 

 

Join our CSE Graduate Programs!

Applications for Fall 2025 MSc and Ph.D. programs are now open until March 12. Join us!

The Computer Science and Engineering (CSE) Department at Qatar University offers a range of graduate programs, including the Master of Science (MSc) in Computing, Ph.D. in Computer Science, and Ph.D. in Computer Engineering. Our programs are designed to be diverse and inclusive, with a multicultural student body guided by highly qualified and experienced faculty from various disciplines and research fields. Key research areas include artificial intelligence (AI) and applied machine learning, cybersecurity, robotics and computer vision, as well as networks and the Internet of Things, among others.

Equipped with cutting-edge lab facilities and resources, the CSE department provides students with the tools they need to excel in their academic and research endeavors. Our alumni and graduates have secured prominent positions in leading industries and academic institutions in Qatar and across the globe.

Don’t miss this opportunity to advance your career! Applications for Fall 2025 MSc and Ph.D. programs are open until March 12. Apply now!

To know more information about CSE graduate programs, check our CSE department page.

To apply for graduate studies, visit QU graduate application page.

CSE faculty gives a keynote speech on AI applications in the Oil and Gas industry

Prof. Khaled Shaban participated as a keynote speaker and panelist in a workshop titled “Decarbonization and Energy Transition in the Oil and Gas Industry,” organized by the Gas Processing Center at Qatar University on Sunday, December 1, 2024. The workshop provided a vital platform to discuss the transformative role of advanced technologies in addressing the industry’s most pressing challenges.

Prof. Shaban delivered a keynote presentation on “AI and ML: Catalysts for Digital Transformation in the Oil and Gas Industry,” highlighting how artificial intelligence and machine learning are revolutionizing operations by driving efficiency, sustainability, and innovation. The presentation offered valuable insights into key applications, such as autonomous drilling, predictive maintenance, and supply chain optimization, along with actionable strategies to address challenges like data quality issues and resistance to change.

Prof. Khalid Shaban

Following the keynote, Prof. Shaban contributed as a panelist, engaging with industry leaders and academics to explore collaborative approaches for implementing AI/ML technologies. The discussions emphasized their potential to enhance operational agility and environmental compliance. His participation underscores a strong commitment to fostering innovation and shaping the future of energy through cutting-edge research and practical solutions.

CSE faculties awarded QU grants

Three of our faculty members (Prof. Amr Mohmed, Dr. Moutaz Saleh and Dr. Ahmed Badawy) and their research teams have just been been awarded QU internal grants (Cycle 8) in the different categories. 

Here are more details about the winning projects:

Prof. Amr Mohamed
Prof. Amr Mohamed

Project Team: Dr. Amr Mohamed

Project Title: “Next-Gen Health Systems: AI-Driven Edge Platform for Autonomous healthcare services”

Grant Category: Post-Doc grant

Project Abstract: Promoting smart and secure healthcare services is instrumental in ensuring that Qatari citizens receive efficient, timely, and high-quality healthcare, ultimately contributing to an improved quality of life. Coinciding with this vision, this project aims to adopt recent communication and Artificial Intelligence (AI) technologies, such as distributed collaborative learning, edge computing, and network function virtualization (NFV) to fulfil challenging healthcare services’ requirements. The proposed platform will integrate different, distributed AI schemes in healthcare infrastructures to enable a paradigm shift for improving efficiency of the healthcare systems in Qatar. In contrast to the literature on E-health, the adopted platform will consider context-aware, distributed AI approaches to be implemented over 6G networks. This aims to optimize medical data delivery and energy consumption while supporting intelligent healthcare services. In addition, our plan involves integrating distributed learning with resource allocation schemes over 6G networks. This aims to transmit critical health information in real-time and promptly alert the user in case of an emergency. Thus, a key aspect of this project is to develop intelligent platform and algorithms that consider: (i) all requirements of the supported healthcare services, (ii) the capabilities of the network and computing infrastructure, and (iii) the privacy and security of the acquired data. Such aspects will be thoroughly investigated and fully developed, thanks to the collaboration with Hamad Medical Corporation (HMC), which will further strengthen the scientific excellence of this project by providing the necessary datasets, use cases, and equipment if required. The developed techniques in this project will be implemented in various critical applications, such as remote surgery and emergency transmission of surveillance videos in ambient assisted living. We envision integrating these techniques with the prototypes of the remote surgery department at HMC, utilizing advanced communication over 6G networks. This integration aims to guarantee a high quality of service for delay-critical applications.

 

Dr. Moutaz Saleh

Project Team: Dr. Moutaz Saleh (Lead PI) (Department of Computer Science & Engineering, College of Engineering, Qatar University) Dr. Sumaya AlMaadeed (PI) (Department of Computer Science & Engineering, College of Engineering, Qatar University) Dr. Asma Al-Attiyah (PI) (Dean of College of Education, College of Education, Qatar University) Dr. Hanan Khalil (PI) (Department of Rehabilitation Sciences, College of Health Sciences, Qatar University) Dr. Achraf Othman (PI) (Head of Research & Innovation, Mada Center, Qatar

Project Title: “Multimodal Explainable AI for Inclusive Education in Qatar: A Novel Approach for Specific Learning Disability Diagnosis and Personalized Learning Enhancement”

Grant Category: High Impact Grant 

Project Abstract: Specific Learning Disability (SLD) is defined as a disorder in one or more of the basic learning processes involved in understanding or using language, spoken or written, that may manifest in significant difficulties affecting the ability to listen, speak, read, write, spell, or do mathematics. Particularly, Dyslexia which refers to difficulties in reading; Dysgraphia which refers to difficulties in writing; and Dyscalculia which refers to difficulties in math. While Qatar has focused on promoting inclusive education to support students with SLD, the development of a general system that can automatically diagnose and assist is an essential step for improving its education system. This project aims to develop expert systems that use artificial intelligence (AI) algorithms to improve diagnosis and assistance evaluation for children with SLD. The project aims to use multimodal data based on standard activities including physiological, neurological, and behavioral data, to provide accurate and personalized assessments to improve the overall quality of care and assistance outcomes. Generally, two main steps are considered: Diagnosis and Assistance Evaluation. In the diagnosis, data collection for normal and SLD is planned, and an AI expert system based on multimodal data will be implemented. This system should analyze the degree of normality and severity of disability. In the second step, based on the analysis of the diagnosis and the suggestions of the psychologist, intelligent decision-making models will be developed to generate tailored assistance plans for each individual by considering the severity of diagnostic disability, level of motor control impairment, and other related factors that contribute to the learning disability. This step is followed until a significant improvement is seen. The project utilizes advanced technologies and data analysis techniques to develop intelligent decision-making models that enhance the accuracy and efficiency of the assessment process. By integrating innovative methods, such as machine learning algorithms, computer vision, multimodal learning, explainable AI, the system can provide objective and reliable measurements for early identification of SLD in children and suggest appropriate improvement plans in an efficient and timely manner that will contribute to the advancements of the education system in Qatar.

Dr. Ahmed Badawy

 

Project Team: Dr. Ahmed Badawy(LPI), Prof. Saeed Salem 

Project Title: “Distributed Edge Learning for Secure Healthcare IoT Networks”

Grant Category: Collaborative grant

Project Abstract: Digital healthcare is a rapidly growing domain with a variety of devices incorporated to monitor, assess, and maintain a healthy lifestyle. Therefore, the Healthcare Internet of Things (HIoT) domain presents a great opportunity to enhance the quality of patient care and potentially save lives; however, comes with unique challenges related to network security and data privacy. On the other hand, Distributed Edge Learning (DEL) represents a paradigm shift in data processing by decentralizing both the learning and the model aggregation processes across multiple edge devices allowing them to collaboratively aggregate a single learning model while keeping the data local. DEL’s decentralized nature allows for faster model aggregation, deployment, and later on model updates, which are key advantages for HIoT applications, allowing for faster response time and reduced network congestion. However, given that DEL is a relatively new field, significant research gaps remain, especially in security and data privacy—crucial for healthcare data—requiring further work to ensure the reliable and secure implementation of HIoT systems.

 

Wishing continued success to all other colleagues in the upcoming cycles!

CSE Faculty Awarded QRDI Grant to Advance Food Security Innovations

Congratulation to Dr. Cagatay Catal and his team for securing a grant through Qatar Research, Development and Innovation Council (QRDI) for food security call. 

The granted project is titled “Artificial Intelligence-Empowered Aquaponics: Empowering Food Security for a Sustainable Future”.

Prof. Cagatay Catal

The Project team includes:

  • Prof. Dr. Cagatay Catal (Lead PI) (Department of Computer Science & Engineering, College of Engineering, Qatar University)
  • Prof. Dr. Nader Meskin (PI) (Department of Electrical Engineering, College of Engineering, Qatar University)
  • Prof. Dr. Ahmed Khalifa (PI) (Department of Finance and Economics, College of Business and Economics, Qatar University)
  • Assoc. Prof. Dr. Mohammed Hussain S A Alsafran (PI) (Agriculture Research Station, Qatar University)
  • Dr. Yamine Bouzembrak (PI) (Information Technology Group, Wageningen University & Research, The Netherlands)
  • Assoc. Prof. Dr. Turker Bodur (PI) (Department of Aquaculture, Faculty of Fisheries, Akdeniz University, Türkiye)

Project Abstract: The objectives of this project are to advance the efficiency, scalability, and reliability of aquaponics systems through the integration of Artificial Intelligence (AI), Machine Learning (ML), Computer Vision (CV), and Internet of Things (IoT) solutions. The project aims to address key challenges in aquaponics, including fish health monitoring, plant disease detection, and environmental monitoring. The project team, in collaboration with Wageningen University & Research in the Netherlands and Akdeniz University in Türkiye will develop Qatar’s first comprehensive research setup for aquaponics. This research setup will be deployed at the Agricultural Research Station of Qatar University. The expected outcomes of this project are two-fold. Firstly, it will result in the development of novel prediction models and innovative technologies that address the challenges in aquaponics. These models and technologies will contribute to enhanced fish health, optimized crop production, and improved overall system efficiency. Secondly, the project aims to empower sustainable food security by minimizing the environmental impact of agriculture. By reducing water usage, nutrient runoff, and pollution, AI-empowered aquaponics will offer a more sustainable alternative to traditional farming methods.

The QRDI and the Ministry of Municipality (MoM) have launched the Food Security Call to support research that aligns with Qatar’s National Food Security Strategy, fostering collaboration among experts to develop solutions for the country’s food supply challenges.