Ridam Hazra
Full Stack | AI | Chatbots | Cloud
Full Stack | AI | Chatbots | Cloud
I am a passionate Software Engineer with a strong academic foundation from NIT Durgapur. I currently work at Willis Towers Watson, contributing to impactful solutions in the Health, Wealth & Career domain as a Full Stack Developer. I thrive in collaborative environments where I can leverage data-driven insights to solve complex problems and drive innovation. As I advance my career, I seek opportunities to lead transformative projects at the intersection of software engineering and artificial intelligence, while contributing to open-source initiatives and the developer community.
Willis Towers Watson (WTW)
Java | Angular | Oracle DB | Kibana | Docker
National Institute of Technology Durgapur
CGPA - 9.14/10
QuizInc NIT Durgapur
Fest coordinator of Quizzitch Cup 2020-23
National Institute of Technology Durgapur
NLP | Dialogflow | Rasa | Chatbot
Microsoft India
Ethical Hacking | Cyber Security | Machine Learning
The Sparks Foundation, Singapore
Graduate Rotational Internship Progarm (GRIP)
Artificial Intelligence Institute, University of South Carolina, USA
ChatBot Development: Randomised Control Trial
In collaboration with Indian Institute of Technology Roorkee
Jadavpur Vidyapith, Kolkata, West Bengal
Score - 84% (A+)
KTPP High School, Kolaghat, West Bengal
Score - 92.43% (AA)
Published In: Nova Science Publishers, 2023
Authors: Ridam Hazra, Arpan Kesh, P. K. Guha Thakurta
Abstract: This publication discusses the development of a chatbot assistant designed to support farmers in improving their livelihoods. The chatbot provides information on agricultural practices, market trends, and weather forecasts, thereby enhancing decision-making processes for farmers.
Read MorePublished In: IEEE Access, 2022
Authors: Karam Kumar Sahoo, Ridam Hazra, Muhammad Fazal Ijaz, Seongki Kim, Pawan Kumar Singh, Mufti Mahmud
Abstract: This paper presents MIC_FuzzyNET, a novel fuzzy integral based ensemble method for the automatic classification of musical instruments from audio signals. The proposed method leverages fuzzy logic to enhance classification accuracy by integrating multiple classifiers.
Read More