To promote scientific research, innovation, and the integration of academic knowledge with practical applications, the Faculty of Information Technology is pleased to announce that several faculty and student research projects have been officially approved for implementation at the university level during the 2026–2027 academic year.

The approved projects cover a wide range of emerging research areas, including Artificial Intelligence (AI), Computer Vision, Large Language Models (LLMs), Reinforcement Learning, Data Privacy and Security, Intelligent Optimization, and next-generation Metaheuristic Algorithms. These topics reflect current technological trends and address real-world challenges in education, logistics, e-commerce, transportation, environmental monitoring, and intelligent decision-making.

Faculty Research Projects

1. Developing an Image Captioning Model Based on Transformer Architecture and Vision–Language Models

Principal Investigator: MSc. Dinh Thi Man

This project aims to develop an image captioning framework following the encoder–decoder paradigm by leveraging Transformer architectures and state-of-the-art vision–language models such as CLIP, BLIP, and BLIP-2. The study focuses on designing a structured prompt generation mechanism using object information and visual relationships, as well as a selective fusion strategy that effectively combines visual and semantic features to improve caption quality. The proposed model will be evaluated on benchmark datasets to validate its effectiveness.

2. Research and Development of an Image Captioning Model Using Deep Learning Integrated with Large Language Models in Higher Education Environments

Principal Investigator: Dr. Nguyen Thi Dinh

This project focuses on investigating image captioning approaches that integrate deep learning techniques with Large Language Models (LLMs). In addition to reviewing and analyzing existing studies, the research team will construct and standardize a dedicated image dataset, Data-iHUIT, collected from the Industrial University of Ho Chi Minh City environment. The project is expected to contribute an effective image captioning solution tailored to higher education applications in Vietnam.

Student Research Projects

The 2026–2027 academic year marks a strong commitment by students to innovative research with practical applications across various domains, including education, logistics, e-commerce, transportation, environmental monitoring, cybersecurity, and recommender systems.

1. Developing the CARO Algorithm to Mitigate Membership Inference Attacks on Random Forest Models

Student: Hoang Ngoc Kien
Supervisor: MSc. Tran Thi Bich Van

This project investigates privacy-preserving machine learning by developing the Chaotic Artificial Rabbit Optimization (CARO) algorithm to optimize Random Forest structures and hyperparameters. The proposed approach aims to reduce vulnerability to Membership Inference Attacks while maintaining predictive performance.

2. Developing a Truck Loading Optimization Solution for Space Utilization and Transportation Cost Reduction Using the Genetic Starfish Optimization Algorithm

Student: Luu Hoan Kim
Supervisor: MSc. Nguyen Thi Huyen Trang

The project addresses the three-dimensional truck loading problem under practical constraints such as weight distribution, stacking limitations, and unloading sequences. A Genetic Starfish Optimization algorithm is proposed to maximize space utilization, reduce transportation costs, and minimize the number of vehicles required. A web-based 3D visualization platform will be developed to support practical deployment.

3. Developing a Multi-Objective Student Scheduling Application Using Snake Optimization with Parasitic Mechanism (SOPM)

Student: Nguyen Thi My Duyen
Supervisor: MSc. Nguyen Thi Thuy Trang

This project proposes SOPM, a novel optimization algorithm that combines Snake Optimizer with the parasitic reproduction mechanism of the Cuckoo Catfish. The solution aims to automatically generate efficient student schedules that balance academic performance, personal well-being, and quality of life while minimizing scheduling conflicts.

4. Developing an Intelligent Learning Path Optimization System for Students Using the HOSM Algorithm

Student: Cao Minh Luan
Supervisor: MSc. Nguyen The Huu

The project focuses on personalizing learning pathways based on student capabilities, learning objectives, and curriculum constraints. The proposed Harris Hawks Optimization with Sailfish Mechanism (HOSM) algorithm seeks to identify optimal learning trajectories that help students achieve desired competencies efficiently.

5. Applying the RAPO Algorithm to Time-Dependent Vehicle Routing Optimization

Student: Huynh Thanh Minh Tam
Supervisor: MSc. Dinh Nguyen Trong Nghia

This research investigates the Time-Dependent Vehicle Routing Problem (TDVRP) and proposes the RAPO algorithm to optimize travel distance, delivery time, and operational costs while considering dynamic traffic conditions. A visualization system will also be developed to simulate delivery routes and evaluate algorithm performance.

6. Developing an E-Commerce Packaging Optimization Solution Using the Starfish Fourier Transform Algorithm

Student: Tran Gia Bao
Supervisors: MSc. Dinh Nguyen Trong Nghia, MSc. Tran Dinh Toan

The project aims to solve order packaging optimization problems in e-commerce by proposing the Starfish Fourier Transform algorithm. The solution focuses on maximizing packaging space utilization, reducing the number of containers used, and lowering shipping costs.

7. Real-Time Optimization of Fresh Agricultural Product Transportation Routes Under Dynamic Traffic Conditions Using Chaotic Pufferfish Optimization (CPO)

Student: Nguyen Le Quyen
Supervisors: MSc. Dinh Nguyen Trong Nghia, MSc. Nguyen Thi Thuy Trang

This study addresses the challenge of transporting fresh agricultural products in dynamic traffic environments. The proposed Chaotic Pufferfish Optimization algorithm is designed to minimize transportation time and reduce product deterioration while adapting effectively to real-time traffic data.

8. Optimizing Air Quality Monitoring Station Placement Using a Multi-Layer Halo Enhanced Artificial Rabbits Optimization Algorithm

Student: Phan Hoai Bao Khang
Supervisor: MSc. Phan Thi Ngoc Mai

The project develops a mathematical model for air pollution dispersion in urban environments and proposes HARO (Halo-Enhanced Artificial Rabbits Optimization) to determine optimal monitoring station locations. The objective is to maximize monitoring coverage while minimizing deployment costs.

9. Reinforcement Learning-Based Optimization of Long-Term User Engagement in Generative Recommender Systems

Student: Dang Nguyen Hoai
Supervisor: MSc. Bui Cong Danh

This project explores the integration of Generative AI and Reinforcement Learning to enhance long-term user engagement in recommender systems. The proposed framework aims to balance the exploitation of existing user preferences with the exploration of emerging interests, enabling adaptive and sustainable recommendation strategies.

Promoting Innovation and Applied Research

The research projects approved for the 2026–2027 academic year demonstrate the Faculty of Information Technology’s commitment to fostering innovation, strengthening research capacity, and aligning academic activities with real-world technological developments.

By focusing on cutting-edge fields such as Artificial Intelligence, Computer Vision, Large Language Models, Reinforcement Learning, and Metaheuristic Optimization, these projects are expected to generate meaningful scientific contributions and practical solutions while providing valuable research opportunities for both faculty members and students.

The Faculty of Information Technology congratulates all project leaders and student researchers and looks forward to the successful implementation and impactful outcomes of these research initiatives.