Rohini Srihari is a Professor in the Department of Computer Science and Engineering at the University at Buffalo, State University of New York, where she also serves as Associate Chair. Additionally, she holds an Adjunct Professor position in the Department of Linguistics. Her academic journey includes a PhD in Computer Science from the University at Buffalo (1992) and a B. Math degree from the University of Waterloo (Canada). Dr. Srihari's research spans multiple cutting-edge areas in artificial intelligence, with a strong focus on Natural Language Processing, Information Retrieval, and Text Mining. Her work encompasses both theoretical foundations and practical applications, particularly in Conversational AI systems, disinformation detection, and social unrest prediction. She has pioneered approaches in multilingual text mining for less commonly taught languages and developed innovative methods for social media analysis. Her recent research emphasizes AI for Social Good, addressing critical societal challenges through technology. Her publication record shows a clear evolution from foundational work in multimedia information retrieval and document analysis toward increasingly socially impactful applications. The recent publications demonstrate a strong focus on using AI to address misinformation, predict civil unrest, and develop empathetic conversational agents. Her work increasingly integrates multiple data sources and leverages state-of-the-art deep learning techniques while maintaining a focus on real-world applicability and social impact. Awards & Recognition: Bronze prize in the Alexa Prize Socialbot Grand Challenge 4 (2021) Two US patents in text mining and image analysis Extensive publication record with over 100 papers and an h-index of 40 Dr. Srihari has secured significant research funding from major agencies including the National Science Foundation (NSF), DARPA, and IARPA. She has directed multiple research projects focused on AI applications for social good, including an NSF-funded project on Purposeful Conversational Agents based on Hierarchical Knowledge Graphs. She supervises students across both Computer Science and Linguistics departments, fostering interdisciplinary research. Her research group, focused on Conversational AI for Social Good, addresses critical issues like combating disinformation and assisting the disabled through trustworthy socialbots. She also directs the Center of Excellence for Document Analysis and Recognition (CEDAR) and has led interdisciplinary student teams in major competitions. Her industry experience includes founding and directing technology startups focused on big data analytics, two of which were acquired by larger media analytics companies.





