Deepti Mishra

Norwegian University of Science and Technology

Papers

21

Total Citations

262

H-Index

9

About

Deepti Mishra is a leading researcher at the intersection of artificial intelligence, robotics, and education, with a primary focus on human activity recognition (HAR) and human-robot interaction. Her work has made significant contributions to understanding how deep learning can analyze video data for behavior analysis and event recognition, as demonstrated in her highly cited 2022 review on HAR using benchmark video datasets (85 citations). Mishra has also pioneered the integration of social and humanoid robots—such as Pepper and NAO—into educational environments, developing frameworks that leverage these robots as teaching assistants to improve language skills, reading habits, and student engagement. Her innovative research extends to autonomous systems, including a coverage path planning approach for environmental monitoring using unmanned surface vehicles (23 citations) and a robust bacterial foraging algorithm for path planning that overcomes local minima challenges. With over 200 citations across her top publications, Mishra’s work bridges cutting-edge AI techniques with practical applications in education and environmental monitoring, establishing her as a key figure in advancing autonomous and interactive technologies for real-world impact.

Research Focus

Key Achievements

9
H-Index
21
Papers
262
Total Citations
12
Avg Citations/Paper
🏆 Most Cited Paper
A Review of Deep Learning-based Human Activity Recognition on Benchmark Video Datasets
85 citations · 2022
📈 Most Prolific Year: 2024 (7 Papers)
🤝 Key Collaborators: 31
🏛 Institutions: Norwegian University of Science and Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago