Research Lead
Advanced AI Research Group | 2026–Present
I am currently pursuing this research together with my team, bringing a strong academic and professional background in artificial intelligence, machine learning, and cybersecurity.
My research interests lie at the intersection of AI and cybersecurity, with a particular focus on developing advanced models for real-world problem-solving. My undergraduate thesis on “Contextual Emotion Detection in Text using Deep Learning and Big Data” reflects my deep interest in natural language processing (NLP) and deep learning–based analytics, and has led to multiple research publications.
I am particularly interested in applying AI techniques such as machine learning, neural networks, and cybersecurity to solve complex challenges in areas like text analysis, cybersecurity, and intelligent decision-making systems.
I have hands-on experience in software development and automation using Java, along with a solid foundation in data structures and algorithms. I am actively seeking research opportunities where I can contribute to innovative projects in AI, machine learning, and cybersecurity, and aim to pursue a PhD to advance my research in intelligent systems.
- Artificial Intelligence & Machine Learning: Developing advanced ML models for real-world problem-solving, including supervised classification, neural networks, and deep learning architectures applied to text, healthcare, and IoT domains.
- 💬 Natural Language Processing & Emotion Detection: Research in contextual emotion detection using deep learning and big data. Applying NLP techniques such as text mining, word embeddings, and transformer-based models to analyze human language.
- 🔒Cyber Security & AI-Driven Security: Exploring the intersection of AI and cybersecurity, including malware analysis, threat detection, and machine learning for 6G-integrated network security. Currently working on file system forensics and digital investigation techniques with Dr. Tahir Khan.
- 🏥Healthcare & Smart Systems: Applying data-driven approaches to healthcare challenges, including disease prediction, automated blood cell quantification, and near-infrared imaging techniques for vein detection.
TrustGuard-LLM ( Ongoing project )
An explainable and adversarially robust agentic LLM framework for real-time cyber-threat detection. TrustGuard-LLM combines language-model reasoning with security telemetry to flag emerging threats while keeping every decision auditable — built for environments where a black-box answer isn’t good enough.
TODO — add project stage, funding/affiliation, and links (paper, repo, demo) here. Note: file system forensics work with Dr. Tahir Khan may belong as its own project entry rather than under TrustGuard-LLM — confirm scope.
People
Leads the lab’s research at the intersection of AI and cybersecurity, with a focus on contextual emotion detection, NLP, and AI-driven security.
Currently working on file system forensics and digital investigation with Dr. Tahir Khan, alongside developing TrustGuard-LLM.
Papel Chandra
Department of Computer Science and Engineering
Western Illinois University Macomb, Illinois, USA
shantochandrapapel267@gmail.com
Komol Dev
Department of Computer Science and Engineering
Trisha Majumder
Bangladesh University of Business and Technology, Dhaka, Bangladesh
Sourav Chandra Shil
Bangladesh University of Business and Technology, Dhaka, Bangladesh
Chinmoy Ray Dipto
Bangladesh University of Business and Technology, Dhaka, Bangladesh
Prapti Roy
Bangladesh University of Business and Technology, Bangladesh