Department
Computer Science and Engineering (Artificial Intelligence and Machine Learning)
Research Areas
The faculty and researchers of the Department of Computer Science and Engineering (CSE) at Annamacharya University explore a dynamic range of advanced research areas that drive academic innovation, foster industry collaboration, and address critical technological challenges in computing and information technology.
Key Research Areas:
- Artificial Intelligence & Machine Learning: Development of robust machine learning classification algorithms, automated cyberbullying detection systems, deep learning architectures, and intelligent predictive modeling for real-world applications.
- Retrieval-Augmented Generation (RAG) & Natural Language Processing: Research and development of forensic-gated legal RAG system architectures utilizing LayoutLMv3, Tesseract OCR, InLegalBERT, FAISS, and LangChain for tamper detection and intelligent statute retrieval.
- Software Engineering & Agile Methodologies: Advanced methodologies in software development lifecycle management, quality assurance, DevOps automation, continuous integration, and modern architectural frameworks.
- Full Stack Development & Web Technologies: Modern web architectures, scalable distributed application design, robust database integration, and innovative front-end/back-end frameworks.
- Human-Computer Interaction (HCI): Investigation of user experience principles, intuitive user interface design, accessibility engineering, and interaction paradigms for complex computing systems.
- Cybersecurity & Data Privacy: Cryptographic protocols, secure software engineering, vulnerability assessment, threat intelligence, and privacy-preserving data monitoring models.
- Internet of Things (IoT) & Embedded Computing: Software-hardware co-design, sensor-based Human Activity Recognition (HAR), smart automation, and edge intelligence systems.
- Big Data Analytics & Cloud Computing: Distributed computing systems, scalable data processing pipelines, cloud infrastructure optimization, and enterprise resource management.

