Dr Rahul Dass has about three decades of rich experience, with nearly 25 years as a full-time journalist with leading media houses including the Hindustan Times, The Statesman, Indo-Asian News Service (IANS) and The Tribune. His research interest lies at the intersection of Artificial Intelligence and Mass Communication. He has authored three books, including one on Mobile Journalism. He is editor of a book on AI and media, law and marketing. He has co-filed six inter-disciplinary patents that push the frontiers of storytelling.
2009
- Ph.D. on “Challenges of Terrorism to Peace Process in Indian Perspective” from Chaudhary Charan Singh University, Meerut: (2009)
1997
- MA in Political Science from Delhi University: (1997)
1994
- BA (Honours) in Journalism from Delhi University: (1994)
- Dr. Rahul Dass is currently working at Mahindra University as an Associate Professor.
- Dr Rahul Dass has about three decades of rich experience, with nearly 25 years as a full-time journalist with leading media houses including the Hindustan Times, The Statesman, Indo-Asian News Service (IANS) and The Tribune.
Publications
2023
2023
- A consumer perception study on CSR reputation shaping brand image in India. Published in International Journal of Management and Enterprise Development
- The emerging role of metaverse in the buying behavior of the Indian consumer. Published in Asian and Pacific Economic Review
- Role of start-ups in poverty alleviation and entrepreneurial environment in India. Accepted for publication in International Journal of Entrepreneurship and Small Business.
2022
2022
- Book on Mobile Journalism. Published by Prabhat Prakashan
Interdisciplinary research at the intersection of Artificial Intelligence and Mass Communication.
Patents co-filed:
- AI-based tool for predicting virality of videos
- Machine based tool for predicting subterranean topics in journalism through simulation
- Artificial Intelligence enabled news push notifications on mobile devices
- Machine learning based tool to index news based on its social media readability for the purpose of newspaper page making
- Real-time splicing of audio speech to extract news-worthy component by using accelerated deep learning mode
- Deep-learning model to detect text-based fake news
