Mr RAJDEEP DAS, IEM, India
Rajdeep Das is a talented B.Tech (CSBS) student at the Institute of Engineering and Management, with an impressive 8.94 CGPA. He has participated in notable projects, including “iDetect: An Automated Anomaly Detection System for IIoT Data” and “Cure-Net: A Deep Learning Framework for Parkinson’s Disease Detection.” Rajdeep has been granted a fellowship at the 33rd Asian Test Symposium (2024) and serves as a reviewer for the Journal of Computer Science. His research interests span Industrial IoT, cybersecurity, and machine learning. He has earned several NPTEL certifications and recognition for his contributions to the tech community. 🖥️📡🎓🔍
Publication Profile
google scholar
Academic Excellence
Rajdeep Das is a highly qualified individual with a B.Tech in Computer Science and Engineering, achieving an impressive CGPA, and a diploma in Computer Science and Technology. His academic journey reflects his commitment to excellence, consistently demonstrating outstanding performance throughout his studies. Rajdeep’s dedication to learning and skill development has been pivotal in shaping his expertise in the field. With a strong foundation in computer science, he continues to excel and make significant strides in his career. 💻🎓📚🚀
Professional Experience
Rajdeep Das is a fellow at the 33rd Asian Test Symposium 2024 in India (Nov-Dec) 🌏. He serves as a reviewer for Science Publications (Dubai) and Springer Nature (SN Computer Science Journal) 📚. Rajdeep is also a program committee member for the 13th International Conference on Advanced Computer Science (Toronto) and the Malaysia-Japan Visionaries Conference 🖥️. As a guest reviewer for IEEE conferences (Malaysia & India) ⚡, he contributes to key events like the IEEE International Conference on Information and Communication Technology and Smart Computing for Industry 5.0 🔧. Rajdeep is also an active researcher at IIEST, Shibpur, working on communications, intelligent systems, and IoT security 🔒.
Research Experience
Rajdeep Das is involved in multiple cutting-edge research projects, including “iDetect: An Automated Anomaly Detection System for IIoT Data” (accepted for COMSYS 2024), collaborating with Dr. Indrajit Banerjee, Pradeep Kumar, and others. He is also working on “IntegR Scan Tool: A Robust File Integrity Verification Solution” (accepted for AISC 2024), alongside a team from IEM. Other notable projects include “Athena: A Forecasting Strategy for DDoS Attack Prevention” (accepted for ICIS 2024) and “Cure-Net: A Deep Learning Framework for Parkinson’s Detection” (submitted to AIIoT 2025). His ongoing work includes “Lazarus AI: LLM Security Scanner Tool.” 💻🧠📊
Certifications and Accomplishments
Rajdeep’s impressive array of certifications in IoT, cybersecurity, AI, and cloud computing reflects his continuous dedication to expanding his expertise in cutting-edge technologies. His commitment to learning is further highlighted by his multiple accolades, including recognition in the NPTEL STAR categories. Additionally, Rajdeep’s status as a guest speaker at prestigious events showcases his leadership within the research community. His work continues to inspire and contribute to the advancement of emerging technologies, solidifying his place as a thought leader in his field. 🌐💡📚🏆🔒🤖☁️
Research Focus
Rajdeep Das’ research focuses on the application of Internet of Things (IoT) technologies in enhancing real-time monitoring, anomaly detection, and security across various sectors. His work spans industrial IoT for power grid systems, fall detection, space agriculture, and secure communication systems. Key contributions include developing systems for real-time anomaly detection in power grids, secure IoT-enabled fall detection, and adaptive monitoring for space agriculture. Additionally, he has worked on tools for intrusion detection and dataset generation in industrial IoT environments. His interdisciplinary research combines AI, IoT, and security to address modern technological challenges. 🌐⚡🛠️🚀📡
Publication Top Notes
GridSense-ADS: An Industrial IoT Approach for Real-time Anomaly Detection in Power Grid Systems
Accelerated Safety: Revitalizing ADXL345 for Enhanced IoT-enabled Fall Detection
Revolutionizing Real-Time Communication: A Practical Implementation of MQTT in a Secure and Scalable Custom Chat Application
AstroPlant Sentinel: Next-Gen Space AgricultureMonitoring and ADS
IoTForge Pro: A Security Testbed for Generating Intrusion Dataset for Industrial IoT
Vyoma-ADS: An AI-Driven Tool for Adaptive Monitoring and Anomaly Detection for Space Agriculture