Education
Ph.D., University of Cincinnati
Brief Bio
Dr. Nirmalya Thakur is an Assistant Professor at the Department of Electrical Engineering and Computer Science. Prior to joining South Dakota Mines, he worked as an Assistant Teaching Professor of Computer Science at Emory University for two years. His research interests include Big Data, Data Analysis, Human-Computer Interaction, Machine Learning, and Natural Language Processing. He has published over 50 peer-reviewed papers in leading conferences and journals. He completed his PhD at the University of Cincinnati, where he received numerous accolades, including the Dean's Fellowship, the Distinguished Thesis Award, the Interdisciplinary Research Fellowship, the Risk Management Awareness Award, and the Engineer of the Month Award. He has been featured on the cover page of Millennium Magazine, in the American Scientist Magazine, on Yahoo News, on Business Insider, and on multiple other news outlets for his contributions to the field of Computer Science. To learn more about his work, please visit his personal site.
Research Expertise
Dr. Thakur's research spans Big Data, Data Analysis, Human-Computer Interaction, Machine Learning, and Natural Language Processing, and he has published over 50 peer-reviewed papers at leading conferences and in journals. His work leverages interaction data from people's everyday activities, both in smart home environments and on digital platforms such as social media, to address critical societal challenges. His research in AI-powered infoveillance and social media analytics focuses on developing computational frameworks that reveal how public sentiment, misinformation, and anxiety related to global health crises merge and evolve on social media platforms. Using multilingual sentiment analysis, topic modeling, anxiety detection, and toxicity analysis, these frameworks capture the dynamics of online discourse across linguistic and cultural boundaries. The findings demonstrate that misinformation, conspiracy theories, and emotionally charged content on social media shape public perceptions, trust, and behavior, and that these responses can shift rapidly in response to policy changes, emerging variants, or health interventions. To further advance technologies that improve the quality of life for older adults, he also develops assistive solutions that support healthy aging and independent living. His projects in this area include human activity recognition, user-specific activity recommendation, indoor location detection, fall detection, and cognitive impairment detection from user interactions. In summary, Dr. Thakur’s research leverages data from everyday interactions in physical and digital settings to deliver solutions that address pressing societal needs and improve individual and community well-being, advancing knowledge and innovation across multiple disciplines.
Teaching
Dr. Thakur has experience teaching a wide range of courses in Computer Science, such as Data Mining, Deep Learning, Machine Learning Applications, Introduction to Artificial Intelligence, Analysis of Algorithms, Data Structures and Algorithms, Foundations of Computer Science, Introduction to Computer Science I, Artificial Intelligence and Computational Decision Making, and Programming for ECE.