Computer Science Students Solve Real-life Challenges with Graduation Projects

Marking the completion of three years of learning and innovation, the Computer Science Graduation Showcase highlights 8 outstanding projects recognised with the Excellence Award in Undergraduate Research. These projects were highly praised by both industry experts and BUV lecturers: “These are the kind of products we’d expect from seasoned professionals – not fresh graduates,” as remarked by Prof. Raymond Gordon, Vice-Chancellor and President of BUV.

After three years of intensive learning and practice, our Computer Science students presented diverse solutions, including AI applications, cybersecurity, manufacturing technology, and e-commerce innovations. Each project not only demonstrates solid technological expertise but also BUV students’ ability to tackle real-world challenges with creativity and practicality. This year’s project raised the bar for graduation projects this year, leaving both industry professionals and academic observers in awe of their achievements. 

The exhibition marks an important milestone in the students’ development and offers them an opportunity to engage with industry professionals, opening doors to potential product commercialisation.

Outstanding students from the Computer Science programme with the faculty from the School of Computing & Innovative Technologies during the Graduation Showcase

Learn more about the award-winning tech creations from BUV Computer Science students in the article below.

Hoang An Khanh: Optimising the personal shopping assistance experience with Deep Learning

Hoang An Khanh brought a practical solution to the field of e-commerce at the Technology Project Exhibition with her project “Personal Shopping Assistant: Comparative Analysis and Proposed Enhancements for Deep Learning-Based Recommendation Systems.”

Instead of simply applying existing recommendation models, Khanh focused on evaluating the real-world effectiveness of each system while leveraging the power of Deep Learning to deliver solutions that suggest products more accurately and closely aligned with consumer needs.

The project is clear evidence of Khanh’s independent research ability and sharp technological mindset developed over three years at BUV. Thanks to this, Khanh was proudly awarded First Prize, voted by the attending industry representatives.

Nguyen The Vinh: Enhancing Penetration Testing process with AI-Based Payload Generation and Web Request Analysis

Nguyen The Vinh took on a bold and challenging direction with his project “Enhancing Penetration Testing process with AI-Based Payload Generation and Web Request Analysis.”, where AI automatically generates attack data and analyses web communication flows to detect vulnerabilities faster and with greater accuracy.

Thanks to its practicality and performance comparable to professional cybersecurity tools currently used in the industry, Vinh’s project captured significant attention at the Technology Project Exhibition. Not only was it highly praised by experts for its quality and real-world applicability, but Vinh also stood out as a talented student who collaborated with Dr. Ali Al-Dulaimi, Head of the School of Computer Science & Technology, to further refine his doctoral thesis research.

Hoang Minh Sang: Enhancing cybersecurity system with Generative Adversarial Networks (GAN)

His graduation project aims to develop a more optimised cybersecurity system, Hoang Minh Sang harnessed the power of Generative Adversarial Networks (GANs) – a deep learning model in machine learning that operates through two competing systems: one generating synthetic data as realistic as possible, and the other distinguishing between real and fake. By continuously training these two models in competition, a wide range of simulated cyberattacks close to real-world scenarios are generated, enabling the cybersecurity system to automatically refine its alert rules and thereby detect and respond to threats more effectively.

The project originated from the ambition to break away from today’s manual, inefficient security practices and to address the overload of inaccurate alerts. Despite facing dozens of failed experiments and the lack of existing references, he persisted and even created a new mathematical function to fundamentally solve the issue.

More than just a personal achievement, the project stands as proof of the synergy between technological passion, curiosity, and relentless research efforts—allowing Hoang Minh Sang to bring to life an innovative idea in the field of cybersecurity.

Nguyen Hoang Minh: Designing and Evaluating a Resilient Fault-Tolerant framework for Software Defined Networks (SDN)

Unlike traditional networks where hardware controls the devices, Software Defined Networking (SDN) manages infrastructure through software, enabling a highly automated, flexible, and easily managed system. Although SDN surpasses traditional models, Nguyen Hoang Minh enhanced the system with a fault detection and automatic failover mechanism at the control layer, delivering greater stability, efficiency, and reliability than conventional SDN.

The project was inspired by Minh’s curiosity about how the internet maintains connectivity during disruptions and was shaped through in-depth discussions with Dr. Hamza Mutaher, who introduced him to the SDN field and guided him throughout the process. Valuable feedback from Dr. Sasikumar Perumal, along with the experience of attending the ICCIT conference under the mentorship of Associate Professor Anchit Bijalwan, also played a crucial role in helping Minh successfully complete the project.

Pham Quoc Bao: Gamified Ethical Hacking Platform

Pham Quoc Bao developed a gamified cybersecurity learning platform to challenge the stereotype that computer science is only for experts. Featuring real-world scenarios, point-based rewards, and hints, the platform makes cybersecurity knowledge accessible, engaging, and inspiring for learners of all levels.

Built as a complete web application personally designed and developed by Bao, from interface and security to system logic, the project presents both his skills and passion. Above all, Bao is proud that how the platform not only simplifies learning but also motivates beginners to explore the world of cybersecurity.

Tran Quy Vuong: Applying Artificial Intelligence in Predictive Maintenance for the Manufacturing Industry

With his project “AI-Powered Predictive Maintenance for Manufacturing,” Tran Quy Vuong developed a Hybrid Capsule Network–Transformer (HCNTM) model capable of analyzing sensor data across both temporal and spatial dimensions. The model aims to enhance maintenance efficiency and minimize production downtime.

Under the guidance of Dr. Ali Al-Dulaimi, Head of School, Vuong overcame his initial limitations in deep learning foundations to successfully build a model with strong potential for real-world industrial applications. His project not only showcases his resilience and commitment to learning but also highlights the vital role of dedicated mentorship from experienced BUV faculty.

Bach Xuan Phong: Developing Large Language Model to Optimise Student Services 

Bach Xuan Phong developed a chatbot powered by a Large Language Model (LLM) integrated with Retrieval-Augmented Generation (RAG) to address student inquiries. In parallel, he conducted experimental testing of three Spanning Tree Protocol (STP) configurations on actual Cisco devices to evaluate network performance in real-world conditions.

Despite numerous challenges during the process, these obstacles strengthened Phong’s patience and adaptability. At the exhibition, he took pride in presenting his findings in a clear and accessible manner, ensuring both technical and non-technical audiences could engage with his work.

The project reflects both Phong’s strong academic grounding and the dedicated guidance of BUV faculty, while marking an important milestone that empowers him to confidently step into his professional journey.

Nguyen Tung Anh: AI-Assisted SIEM Optimised with Precise Threat Monitoring, Detection and Response 

Driven by a desire to create a simple, effective, and accessible security solution for businesses, Nguyen Tung Anh developed an integrated SIEM system with Telegram and OpenAI, designed to reduce alert overload and enable security teams to respond more swiftly to potential threats.

The idea was developed during his internship at ASIM Group, where Tung Anh gained hands-on experience in customising SIEM systems. The project leverages the open-source Wazuh platform, integrates Telegram for real-time notifications, and applies AI to optimize detection rules.

Although faced with technical difficulties and software limitations, Tung Anh remained resilient, proving his ability to turn knowledge into real-world solutions, reflecting the strong academic grounding he acquired at BUV.