Designation: Assistant Professor

Teaching Experience: 3+Years

Industry Experience:  1+Years

Brief: Moushumi Barman is a seasoned professional with over three years of experience in academia coupled with a year of industrial exposure, where she has excelled in guiding students pursuing MCA, BCA, and BTech degrees. With a specialized focus on cutting-edge fields such as Computer Networks, IoT, Machine Learning, Deep Learning, Information Security, and Android App Development, her expertise shines through international-level courses and diverse subject teaching. Her prolific research contributions, extensively published in renowned journals and conferences, underscore her proficiency in a wide array of technologies including Python, Java, C, C++, and more, solidifying her reputation as a versatile and knowledgeable educator.

Research Publications: 

Key Publications:

1. IoT malware detection using a novel 3-Sigma Auto-Funnel Transformer approach. International Journal on Recent and Innovation Trends in Computing and Communication.

2 Comparative Analysis of Deep Learning Techniques on LOT devices.

3. Pragmatic Way of Analyzing Malware Attacks Detection in IoT Devices Using Deep Learning.

4. A Randomized Scheme for Modular Exponentiation against Power Analysis Attacks. Journal of Cyber Physical System

LinkedIn : http://www.linkedin.com/in/moushumi-barman-505837150

External Links: https://www.researchgate.net/profile/Moushumi-Barman