Her scholarly contributions focus on areas such as hashtag recommendation, popularity prediction, misinformation detection, sarcasm detection, multilingual NLP, and social media analytics. Through her research, she explores how advanced machine learning and deep learning techniques can be leveraged to address real-world challenges in digital environments. Her work has been published in leading journals and presented at premier international venues including ACL, AAAI ICWSM, ICASSP, and IEEE forums.
Dr. Bansal has built an impressive publication record across several high-impact journals and conferences, contributing to advancements in computational social science, multimodal learning, graph neural networks, and large language models. Her research spans applications ranging from disaster-event information systems and social media recommendation engines to sentiment analysis, stance detection, and multimodal content understanding. She has also contributed to emerging interdisciplinary areas such as AI-driven neuromarketing and consumer engagement.
In addition to her research, Dr. Bansal has extensive teaching and mentoring experience. She has taught courses in Artificial Intelligence, Machine Learning, Advanced Algorithms, and Natural Language Processing, and has mentored numerous undergraduate and postgraduate students. She actively contributes to the research community through reviewing for leading international journals and conferences. At MICA, her interests include applying AI and NLP to business, social media management, information systems, and analytics-driven decision-making.