Computer Science and Information Technology Research Areas

Computer Science:

The Computer Science program focuses on the principles and advanced technologies that underpin modern computing systems. It provides a strong foundation in algorithms, programming, and computational theory, with emphasis on systems design, software development, and high-performance computing. Graduates are prepared for research and innovation in emerging technologies such as intelligent systems and quantum computing.

• Large Language Models (LLMs) and AI in Software Engineering
• Human–AI Collaboration and Trustworthy AI
• Cloud, Microservices, DevOps, and DevSecOps
• Low-Code / No-Code and Quantum Software Engineering
• Parallel and High-Performance Computing
• Compiler Design and Optimization
• Advanced Algorithms and Data Structures

Software Engineering:

The Software Engineering program equips students with the methodologies, tools, and practices for building reliable, scalable, and secure software systems. It combines theoretical knowledge with hands-on experience in modeling, verification, and quality assurance.

• Software Engineering and Formal Methods
• Software Quality, Reliability, and Verification
• Agile and Model-Driven Software Development
• Software Project Management and DevOps Practices

Artificial Intelligence:

The Artificial Intelligence program provides deep understanding of intelligent systems that learn, reason, and act autonomously. It covers modern AI techniques and applications across domains, preparing students to lead in both research and industry innovation.

• Machine Learning and Deep Learning
• Natural Language Processing
• Computer Vision and Autonomous Systems
• Embedded and Edge AI
• Explainable, Ethical, and Trustworthy AI
• Speech and Audio Signal Processing
• Reinforcement Learning and Decision Making
• Scalable AI Systems and Infrastructure

Data Science:

The Data Science program focuses on methods for extracting knowledge and insights from large and complex datasets. It blends machine learning, statistics, and computing to support evidence-based decision-making and predictive analytics.

• Sustainable and Green Data Science
• Data-Centric AI and Synthetic Data Generation
• Edge and Real-Time Data Analytics
• Big Data Mining and Predictive Modeling
• LLM-Based Data Automation and Workflow Optimization
• Decision Intelligence and Cognitive Systems

Cybersecurity:

The Cybersecurity program prepares experts to protect data, networks, and systems against evolving digital threats. It covers cryptography, cyber defense, ethical hacking, and AI-driven security frameworks for emerging technologies.

• Quantum-Safe and Post-Quantum Security
• Adversarial AI and Machine Learning Security
• Privacy and Data Protection
• Cyber Defense for Smart Infrastructure
• IoT Blockchain and Distributed Ledger Security
• Cloud, Edge, and Autonomous System Security
• Cyber Threat Intelligence and Digital Forensics
• AI Governance, Risk, and Compliance (AI-GRC)

Bioinformatics:

The Bioinformatics program integrates computing, biology, and data science to address challenges in genomics, proteomics, and biomedical research. It emphasizes computational modeling and AI-enhanced analysis for biological discovery and healthcare innovation.

• AI and Machine Learning for Biological Data
• High-Performance and Quantum Bioinformatics
• Genomic and Proteomic Data Analysis
• Biomedical Signal and Image Processing
• Systems Biology and Drug Discovery
• DNA and Protein Sequence Modeling