Dr. Nitin Agarwal, an Indian American professor at the University of Arkansas at Little Rock has earned international recognition with an AI research paper at the 39th Annual Conference on Neural Information Processing Systems (NeurIPS).
As one of the world’s most selective AI conferences, the acceptance process is highly competitive, drawing thousands of submissions from top universities, research labs, and technology companies across the globe, according to a university release.
The paper was co-authored by Agarwal, director of the Collaboratorium for social media and Online Behavioral Studies (COSMOS) Research Center, Maulden-Entergy Chair, and Donaghey Distinguished Professor of Information Science at UA Little Rock, along with collaborators from the University of Arkansas, Fayetteville, and the University of Florida.
COSMOS is an interdisciplinary research center that studies online behavior and develops data analytics tools to better understand online communities and emerging cognitive threats in online information environments.
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“NeurIPS is where many of the most influential advances in AI are first introduced,” said Agarwal, whose research on cognitive security has been recognized by the U.S. Department of War, NATO, the Five Eyes intelligence alliance (consisting of Australia, Canada, New Zealand, the United Kingdom, and the United States), the World Health Organization, and other organizations.
Agarwal and his team’s paper introduces MANGO: Multimodal Attention-based Normalizing Flow Approach to Fusion Learning, a new framework designed to improve how AI systems learn from and combine multiple types of information, including images, text, and other data sources.
The research centers on multimodal AI, a type of artificial intelligence that learns from multiple forms of information — such as text, images, or audio — simultaneously.
While people naturally combine different sources of information to understand the world around them, AI systems often struggle to do so effectively because the data doesn’t always match up in obvious ways. MANGO is designed to help AI better understand and combine different types of data.
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Unlike many existing AI models that simply merge information together, MANGO identifies which sources are most relevant and how they relate to one another, allowing AI systems to make more accurate and reliable decisions.
“The real world is inherently multimodal, so if we want AI to better understand people and complex environments, it needs to learn from multiple sources simultaneously rather than treating each independently,” Agarwal said.
Research like this helps AI evolve to provide more context-aware analysis, enabling systems to make more informed and trustworthy decisions. As AI becomes increasingly integrated into daily life and industry, MANGO could improve applications across various fields from healthcare to self-driving vehicles.
The technology could also strengthen security by analyzing social media to identify coordinated influence campaigns or emerging cognitive threats through the combined analysis of text, images, videos, and patterns of online behavior.
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“Ultimately, research like this helps build AI systems that are more reliable, more explainable, and better suited for solving complex real-world problems,” Agarwal said.
Looking ahead, Agarwal and his collaborators plan to expand MANGO to work with additional data types, larger AI foundation models, and real-time decision-making environments while continuing to improve the transparency and reliability of AI systems.
Their goal is to develop AI systems that not only achieve high performance, but also operate reliably in complex applications where accuracy and trust are essential.
Agarwal obtained his PhD from Arizona State University with outstanding dissertation recognition. He was recognized as one of ‘The New Influentials: 20 In Their 20s’ by Arkansas Business.
He was recognized with the University-wide Faculty Excellence Award in Research and Creative Endeavors by UALR in 2015 and 2021. Agarwal received the Social Media Educator of the Year Award at the 21st International Education and Technology Conference.