From tackling the spread of COVID-19 misinformation on social media to his award-winning research on fall detection and indoor localization for ambient assisted living, Nirmalya Thakur actively engages with issues of critical importance to humans and their well-being.
Residing at the intersection of various fields–including big data, HCI, machine learning, and natural language processing–Thakur’s groundbreaking research is fueled by interaction data from daily human activities.
Whether those activities are trolling social media or attempting to navigate a room, his aim is relatively consistent: to reduce challenges related to individual well-being, public health, and community engagement.
Currently, Thakur is an assistant professor in the South Dakota School of Mines and Technology’s Department of Electrical Engineering and Computer Science. He is also one of Computing’s Top 30 Early Career Professionals of 2024.
In the following Q&A, Thakur discusses
Which of the many AI emerging trends he’s most excited about
What he did after finding that the k-Nearest Neighbors (k-NN) classifier consistently outperformed all other algorithms on overall accuracy for developing fall detection systems
His keynote addresses on the gap between advanced AI research and its real-world applications
How his recent projects on the spread of COVID-19-related information on social media can support data-driven strategies to reduce conspiracy theories and other misinformation in public health communications
Why he sees his “behind the scenes” work in professional organizations and on editorial boards as a vitally important part of his contributions to the research community
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