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Ranked Top in Yorkshire for Student Satisfaction
The Complete University Guide 2027 – Student Satisfaction Subject League table, released June 2026
A Placement year is a fantastic opportunity to enhance your professional development while gaining valuable industry experience.
From September 2027, we will offer placement years across our undergraduate Computer Science degree programmes, giving you the chance to build employer-ready skills, apply your learning in practice, explore different career paths, and earn while you learn through paid placement opportunities.
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Experience matters. That's why we embed professional work placements within the majority of our standard undergraduate degrees.
Careers+Placements will work with you to find a placement or help you to arrange your own, whether that's in Leeds, another part of the UK or even abroad. You will be able to take part in a series of workshops, events and live ‘employer challenges’ to boost your confidence and prepare you for your placement.
During your placement, you could have an opportunity to gain degree-relevant work experience, build your knowledge of career sectors and secure valuable employer references and industry contacts. This experience will help you to shape your career decisions and find the right path for you.
Our established links with companies in the Leeds city region means a wide range of business sectors where you can undertake your placement. Previous placement providers include Sky, Infinity Works, Aire Logic and TwentySix Digital.
To find out how we can help you make your career ambitions a reality, visit:
Our Computer Science team are on hand to answer your questions, whether you want to know about the modules you'll be studying, where you can complete your professional placement or the types of assessments you'll do, they are here to help.
A variety of assessment methods are used, matched to the learning outcomes for your programme, allowing you to apply and demonstrate the full range of knowledge and skills that you have developed.
For more details on specific assessment methods for this course contact hello@leedstrinity.ac.uk
Your time on campus, learning through in-person teaching, is at the heart of your academic experience and the way we deliver our programmes. This is supported and further enhanced by additional engagement activities and opportunities provided online and through digital teaching materials. This blended approach seeks to ensure a positive learning and teaching student experience.
Your programme of study has been carefully designed around a three-phase model of delivery:
Preparation, Live and Post teaching and learning and the digital materials used will vary by course, but will be designed to help you structure your learning, take a full and active part in your course, and apply and test your developing knowledge and skills.
At Leeds Trinity we aim to provide an excellent student experience and provide you with the tools and support to help you achieve your academic, personal and professional potential.
Our Learning, Teaching and Assessment Strategy delivers excellence by providing the framework for:
We have a strong reputation for developing student employability, supporting your development towards graduate employment, with relevant skills embedded throughout your programme of study.
We endeavour to develop curiosity, confidence, courage, ambition and aspiration in all students through the key themes in our Learning and Teaching Strategy:
To help you achieve your potential we emphasise learning as a collaborative process, with a range of student-led and real-world activities. This approach ensures that you fully engage in shaping your own learning, developing your critical thinking and reflective skills so that you can identify your own strengths and weaknesses, and use the extensive learning support system we offer to shape your own development.
We believe the secret to great learning and teaching is simple: it is about creating an inclusive learning experience that allows all students to thrive through:
Providing you with the opportunity to develop the professional skills and experience you need to launch your career is at the heart of everything we do at Leeds Trinity University.
There is increasing demand for graduates with relevant computer science and AI knowledge. Opportunities for careers in AI continue to grow across a variety of sectors, including the tech sector, but increasingly within other areas such as medicine and healthcare, e-commerce, finance, the energy industry, sustainable and green design, the automotive sector, aerospace, defence and government.
This degree aims to prepare you for specialist computer science roles, including algorithm developer, research scientist, big data engineer, machine learning engineer, business intelligence developer/consultant, software engineer, NLP engineer and robotics engineer. Alternatively, the degree provides a solid foundation for postgraduate study or academic research.
After you graduate, Careers and Placements will help you as you pursue your chosen career through our mentoring scheme, support with CV and interview preparation and access to graduate employability events.
To find out how we can help you make your career ambitions a reality, visit:
Senior Lecturer
Dr. Aliyu Lawal Aliyu has a PhD in Computer Science and a Master’s in Telecommunication with extensive expertise in Computer Networks, Cybersecurity, and Software Development. He is a certified Cisco professional and member of IEEE. He completed several Cisco certifications, this strengthens his technical foundation in network infrastructure and security. Dr. Aliyu Lawal Aliyu is always in the pursuit of excellence and merit. This trait gives him the drive to excel in his early education and formative years. Passionate about continuous learning, he actively explores emerging technologies and advancements in the IT industry especially the transition to 4th Industrial Revolution. Outside of academics and research, he enjoys playing tennis, chess, and monopoly, as well as maintaining an active lifestyle by regularly going to the gym.
Dr. Aliyu Lawal Aliyu is enthusiastic about technology and research with a profound passion for teaching and advancing knowledge in the field of Computer Science. With a commitment to excellence, he inspires students to explore the frontiers of technology and innovation. He values the transformative power of education and strives to cultivate a learning environment that fosters curiosity, critical thinking, and a lifelong love for knowledge.
He wears several caps in the arena of Computer Science, some days he is a Cybersecurity specialist, Computer Network Engineer, Software Developer with a passion for AI/ML innovation and other days he enjoys reading classics and reflecting on human evolution. He thrives on solving complex problems, securing systems, and building intelligent solutions. With a strong background in research, he enjoys exploring cutting-edge technologies and contributing to advancements in the field. He is deeply committed to mentoring students, sharing knowledge, and fostering the next generation of tech professionals. Whether it's developing secure networks, creating robust software, or applying AI/ML to real-world challenges, he brings curiosity, expertise, and a collaborative spirit to every project.
Cybersecurity, Web Development, Mobile App Development, Software Development (Python, JavaScript, Java, Dart), Analytical Mathematics.
Machine Learning (ML) and Artificial Intelligence (AI), Long Time Evolution (LTE) 5G/6G, Cybersecurity, Networks and Cloud Computing.
Aliyu, A. L., Aneiba, A., Patwary, M., & Bull, P. (2020). A trust management framework for software defined network (SDN) controller and network applications. Computer Networks, 181, 107421.
Aliyu, A. L., & Diockou, J. (2023, March). An Analytical Queuing Model Based on SDN for IoT Traffic in 5G. In International Conference on Advanced Information Networking and Applications (pp. 435-445). Cham: Springer International Publishing. Aliyu, A. L., Aneiba, A., Patwary, M., & Bull, P. (2020). A trust management framework for software defined network (SDN) controller and network applications. Computer Networks, 181, 107421.
Aliyu, A. L., Aneiba, A., & Patwary, M. (2019, September). Secure communication between network applications and controller in software defined network. In 2019 IEEE 18th international symposium on network computing and applications (NCA) (pp. 1-8). IEEE.
Aliyu, A. L., Bull, P., & Abdallah, A. (2017, March). Performance implication and analysis of the OpenFlow SDN protocol. In 2017 31st International Conference on Advanced Information Networking and Applications Workshops (WAINA) (pp. 391-396). IEEE.
Aliyu, A. L., Bull, P., & Abdallah, A. (2017, March). A trust management framework for network applications within an SDN environment. In 2017 31st International Conference on Advanced Information Networking and Applications Workshops (WAINA) (pp. 93-98). IEEE.
My professional career has been influenced by many mentors and icons in my life. They are David master’s programme leader, Prof. Ali Abdallah, Dr. Peter Bull, Ass. Prof Adel as all part of my research supervision . In all of them, I see them as embodiment of knowledge, intellectual acumen, professional experience, industry perspective, mentors and leaders. The bring and inspire real-world examples into the classroom and research environment, such as the challenges of integrating computer network models into scalable applications and the importance of interdisciplinary collaboration. They emphasise on practical skills like coding best practices, algorithm optimization, and ethical considerations. Additionally, I use this experience to teach students about the impact of technology on society and inspire them to think critically about how their technical skills can solve real-world problems.
The world leader and trail blazers are Prof. Nick Mckeown and Martin Cassado. They pioneered a greenfield technology in virtualising computer networks. Their little research project in Stamford University became a huge success as a start up company called Nicira which was later acquired by Vmware at about $1.1 billion. They continue to set the pace and lead research and innovation developments.
The dotcom revolution where we witnessed rapid rise of internet-based companies during the late 1990s and early 2000s. This period, often called the dot-com bubble, saw a massive surge in the stock market valuations of internet startups, driven by speculative investments and the widespread adoption of the internet. Global companies that emerge out of these eporch are Facebook, Google, Yahoo, MySpace, Twitter, Blackberry, IPhone, Craiglist, EBay and many more. The second moment is now with AI revolution and fourth industrial revolution.
Senior Lecturer in Computer Science
Dr Antesar Shabut is a Senior Lecturer in Computer Science and the Programme Leader for the BSC (Hons) Computer Science programme at Leeds Trinity University. With over a decade of teaching experience, she is also a Senior Fellow of the Higher Education Academy. Dr Shabut received her PhD degree in Cybersecurity from the University of Bradford in 2016. Prior to this, she studied her Master's degree at Sheffield Hallam University and graduated with a Bachelor of Science in Computer Science with First Class Honours.
Dr Shabut's academic journey commenced as a Graduate Teaching Assistant at the University of Bradford. She then transitioned to a Research Fellow position at Anglia Ruskin University, where she dedicated over three years to various scientific and pedagogical projects. Joining Leeds Trinity, Dr Shabut worked as a Lecturer, instructing students in diverse Computing subjects and quickly got promoted to a Senior Lecturer role.
Throughout her career, Dr Shabut has secured funding as both a principal investigator and co-principal investigator for several scientific and pedagogical research projects. She is deeply passionate about transforming innovative concepts into software products that serve the community and wider society.
Additionally, Dr Shabut is the co-founder of Globalizer, an app aimed at facilitating global education collaboration.
Her research interests include Artificial Intelligence, Machine Learning, Computer Education and Software Engineering.
Artificial Intelligence, Machine Learning, Mobile App Development, Software Engineering.
Artificial Intelligence, AI Ethics, Machine Learning, Computer Education and Software Engineering.
How the Globalizer App Developed at Leeds Trinity University is a Way for All Higher Education Institutions to Implement Globalization 4.0K Blair, A Shabut HETL Frontiers 2 (1), 10-12, , 2024.
Unravelling the Skills Deficit in Tech: An Educator's PerspectiveG Bengsch, A Shabut, S Harriet, J Diockou2023 15th International Conference on Software, Knowledge, Information …, , 2023
GLOBALIZER: TINDER FOR EDUCATORSK Blair, A ShabutICERI2023 Proceedings, 2774-2782, , 2023
iTB-test: An Intelligent Image-enabled Diagnostic System for In Vitro Screening of Infectious DiseasesMH Tania, MS Kaiser, AM Shabut, K Abu-Hassan, M Mahmud, ...2022 14th International Conference on Software, Knowledge, Information …, , 2022
Security scheme enhancement for voice over wireless networksF Hazzaa, AM Shabut, NHM Ali, M CirsteaJournal of Information Security and Applications 58, 102798, 7, 2021
Achievements of neural network in skin lesions classificationN Hameed, A Shabut, F Hameed, S Cirstea, A HossainState of the Art in Neural Networks and their Applications, 133-151, 4, 2021
Mobile based skin lesions classification using convolution neural networkN Hameed, A Shabut, F Hameed, S Cirstea, S Harriet, A HossainAnnals of Emerging Technologies in Computing (AETiC) 4 (2), 16, 2020
Multi-class multi-level classification algorithm for skin lesions classification using machine learning techniquesN Hameed, AM Shabut, MK Ghosh, MA HossainExpert Systems with Applications 141, 112961, 158, 2020
Intelligent image-based colourimetric tests using machine learning framework for lateral flow assaysMH Tania, KT Lwin, AM Shabut, M Najlah, J Chin, MA HossainExpert Systems with Applications 139, 112843, 29, 2020
Design and development of a benchmark for dynamic multi-objective optimisation problem in the context of deep reinforcement learningMM Hasan, K Lwin, A Shabut, MA Hossain2019 22nd International Conference on Computer and Information Technology …, ,
An intelligent mobile-enabled expert system for tuberculosis disease diagnosis in real time. AM Shabut, MH Tania, KT Lwin, BA Evans, NA Yusof, KJ Abu-Hassan, ...Expert Systems with Applications 114, 65-77
Senior Lecturer in Computer Science
Mr. Diockou is a Senior Lecturer at the School of Computing and Creative Industries at Leeds Trinity University (LTU), where he has been a faculty member since 2020. He obtained his MSc in Network Performance Engineering from Bradford University in 2015 and his BSc in Computer Networks from Middlesex University in London in 2003. His extensive background in network engineering and computer science has paved the way for a career in academia and research.
Jim began his teaching career at the University Centre at Leeds City College (UC at LCC), where he worked as a lecturer for over 10 years. During his time at UC at LCC, he played an important role in the development of several academic pathways. He designed and developed the Cybersecurity pathway and significantly contributed to the design and development of the Software Development and Game Development pathways. His innovative approach and dedication to curriculum development have had a lasting impact on the programmes at UC at LCC.
At LTU, Jim continues to demonstrate his commitment to education and student success. At undergraduate and postgraduate levels, he teaches a variety of modules, including Introduction to Software Development, Secure Development and Deployment (SDD), Computing Skills, and Responsible Computing. His expertise in these areas ensures that students receive a comprehensive and up-to-date education in computer science.
Jim has also been instrumental in the design and development of the Computer Science with Game Development pathway at LTU. Additionally, he contributed to the design and development of the BA Game Design pathway within the School of Computing and Creative Industries, reflecting his interdisciplinary interests and ability to bridge the gap between computer science and creative domains of knowledge and skills.
His research interests are diverse and current, focusing on enhancing the security of drone networks through advanced intrusion detection and reliability modelling, exploring the intersection of tourism and the Metaverse, and integrating education with computer science advancements. These research areas not only contribute to the academic community but also address real-world challenges and opportunities.
Jim's publications include:
"An Analytical Queuing Model Based on SDN for IoT Traffic in 5G"
"Unravelling the Skills Deficit in Tech: An Educator's Perspective." These publications highlight his ability to address both technical and educational challenges within the field of computer science.
Outside of his professional activities, Jim likes reading about classical and medieval philosophies.
Networking: Designed, developed, and delivered courses on advanced networking principles, focusing on the design, implementation, and security of emerging network architectures such as RANET (Robotic Ad hoc Networks), VANET (Vehicular Ad hoc Networks), and MANET (Mobile Ad hoc Networks).
Computer Science: Developed comprehensive curricula in foundational and advanced computer science topics, including programming languages, data structures, algorithms, and software engineering.
Cyber Security: Delivered courses covering intrusion detection, secure network design, cryptographic protocols, and ethical hacking.
Enhancing the security of drone networks through advanced intrusion detection and reliability modelling
Tourism and the Metaverse
Education and Computer Science
Lecturer
Dr. Hua Yan received his Ph.D. from the University of Warwick in 2022. He is currently working as a Lecturer in the School of Computer Science at Leeds Trinity University, U.K. Prior to joining Leeds Trinity University, he worked as a Postdoctoral Research Associate in the Department of Engineering at Durham University, U.K., and as a Research Fellow in the School of Engineering at the University of Warwick, U.K. His research interests include intelligent communications, system modelling and performance analysis, as well as wireless power transfer.
Computer Science and wireless communications.
THz-integrated sensing, communications and powering, UAV communications and Wireless power transfer.
[1] H. Yan and Y. Chen, "Enabling 6G with Terahertz Integrated Sensing Communications and Powering," in IEEE Transactions on Vehicular Technology, 2026, doi: 10.1109/TVT.2026.3688956.
[2] H. Yan and Y. Chen, "Optimum Distance for In-Flight UAV-to-UAV Wireless Charging," in IEEE Access, vol. 13, pp. 143914-143924, 2025, doi: 10.1109/ACCESS.2025.3598733.
[3] H. Yan and Y. Chen, "Time Allocation for Sensing-Assisted Wireless Powered Terahertz Communications," in IEEE Wireless Communications Letters, vol. 14, no. 10, pp. 3364-3368, Oct. 2025, doi: 10.1109/LWC.2025.3594007.
[4] H. Yan, Y. Chen and X. Ding, "Sag Monitoring for Overhead Transmission Lines Using 5G Radio Signals," 2024 6th Global Power, Energy and Communication Conference (GPECOM), Budapest, Hungary, 2024, pp. 584-589, doi: 10.1109/GPECOM61896.2024.10582613.
[5] H. Yan, Y. Chen and S. -H. Yang, "Time Allocation and Optimization in UAV-Enabled Wireless Powered Communication Networks," in IEEE Transactions on Green Communications and Networking, vol. 6, no. 2, pp. 951-964, June 2022, doi: 10.1109/TGCN.2021.3117312.
[6] H. Yan, Y. Chen and S. -H. Yang, "New Energy Consumption Model for Rotary-Wing UAV Propulsion," in IEEE Wireless Communications Letters, vol. 10, no. 9, pp. 2009-2012, Sept. 2021, doi: 10.1109/LWC.2021.3090772.
[7] H. Yan, S. -H. Yang, Y. Chen and S. A. Fahmy, "Optimum Battery Weight for Maximizing Available Energy in UAV-Enabled Wireless Communications," in IEEE Wireless Communications Letters, vol. 10, no. 7, pp. 1410-1413, July 2021, doi: 10.1109/LWC.2021.3069078.
[8] H. Yan, Y. Chen and S. -H. Yang, "UAV-Enabled Wireless Power Transfer With Base Station Charging and UAV Power Consumption," in IEEE Transactions on Vehicular Technology, vol. 69, no. 11, pp. 12883-12896, Nov. 2020, doi: 10.1109/TVT.2020.3015246.
Associate Professor (Teaching and Learning) in Computer Science
Lesley May is Associate Professor of Teaching and Learning in Computer Science at Leeds Trinity University, where she serves as Student Success Lead for the School. Her work focuses on enhancing the student experience through inclusive practice, with a strong emphasis on belonging, engagement, and progression. She is also committed to promoting responsible and ethical approaches to computing, ensuring students understand the broader societal impact of technology.
With more than twenty years of experience in higher education, Lesley has developed expertise in curriculum design, pedagogic innovation, and the dissemination of effective teaching practices. She is committed to supporting both student achievement and staff development, fostering a collaborative culture of continuous improvement while embedding responsible computing practices within the curriculum.
Her interest in data originates from her earlier career as a Manager for Virgin Trains, where she began exploring innovative approaches to information management. This experience sparked a lasting curiosity about the power of data and its applications. She now brings this enthusiasm into her teaching, inspiring the next generation of computer scientists to engage critically, creatively, and responsibly with data.
Data Science, Visualisation, Computer Science, Information Systems and Responsible Computing.
Computer Science Education, Data Visualisation, Student Engagement and Digital Pedagogy.
May, L. and Danino, N., (2023). Enhancing Student Support and Community Engagement: The Implementation of Peer Assisted Study Sessions in Computer Science Education, Annual Research Conference (ARC), Leeds Trinity University, June 2023.
Danino, N. and May, L (2021). The PASS effect: enabling a student-led Computing community. Practical Pedagogy, University of Lincoln, UK, 13 September 2021.
May, L. and Danino, N., (2020). The PASS Effect: How Peer Assisted Study Sessions Contribute to a Computing Community. Computing Education Practice (CEP ’19), January 9, 2020, Durham, United Kingdom. ACM.
May, L., (2019). Riding The Rollercoaster: An Exploration of a Computing Student’s Journey, INTED2019 Proceedings, pp. 7106-7112.
Mitchell, N.P., May, L., and Danino, N., (2019). Students as Partners in an Immersive Agile Learning Environment, International Technology, Education and Development Conference p. 6988.
Mitchell, N.P. and May, L., (2016). Meaningful Mentoring For Computing Students at the University of Central Lancashire, Learning and Teaching Conference, University of Central Lancashire.
May, L., (2016). An Exploration of Retention and Success for First Year Computing Students at the University of Central Lancashire (UCLan), Learning and Teaching Conference, University of Central Lancashire.
May, L., (2015). An Investigation Into Retention Issues for Computing Students at UCLan, Learning and Teaching Conference, University of Central Lancashire.
Danino, N., May, L. and Mitchell, N., (2014). The Four Week Challenge: A Highly Scaffolded Introduction to Computing at University, The European First Year Experience Conference, Nottingham Trent University.
May, L., Danino, N. and Mitchell, N., (2014). Interactive Induction: Involving the Students To Minimise Initial Fears, The European First Year Experience Conference, Nottingham Trent University.
May, L., Mitchell, N. and Danino, N., (2014). Peer Assessment as a Student Engagement Strategy, The European First Year Experience Conference, Nottingham Trent University.
Mitchell, N.P., Danino, N. and May, L., (2014). Using competition and reward to influence undergraduate attitudes in computing, The European First Year Experience Conference, Nottingham Trent University.
Senior Lecturer
Yashar is a dedicated Senior Lecturer at Leeds Trinity University with a robust background in higher education, spanning over a decade. His research focuses on the applications of AI, data science, advanced signal processing and complex system modelling in neuroscience, biomedical applications, and healthcare. He has extensive experience in designing and developing programmes of studies and module specifications, as well as conducting pedagogical experimentations. Yashar has been actively involved in editorial activities, serving as an Editorial Board Member for the Journal of Learning Assessment Teaching in Higher Education. His expertise lies within the field of Automation and Advanced Systems Engineering, Computer Science, and Informatics, contributing significantly to academic publications and peer review processes.
In addition to his research, Yashar is deeply involved in curriculum development, consistently striving to innovate and enhance the academic experience. His approach includes integrating real-world applications into coursework and actively engaging in experimental pedagogies to improve teaching outcomes.
Yashar also plays a significant role in enhancing the student experience at Leeds Trinity University. He contributes to various panels and workstreams aimed at refining educational practices and fostering a dynamic learning environment.
Data Science, AI and DevOps, Cloud Computing, Software Engineering and Programming (Python, Java, MATLAB, HTML, CSS, JS), Mathematics and Front- and Back-end development.
Genetics, AI, Robotics, 3D Printing and applications of computing for good.
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