Madhuri Mishra

Madhuri Mishra

Assistant Professor

Profile Summary

Madhuri Mishra is an Assistant Professor in the School of Computer Science at UPES, Dehradun, with strong academic and industry engagement experience in teaching and student development.

She has previously served as Visiting Faculty at MNNIT Allahabad for three years and at IIIT Lucknow for one semester, handling core computer science subjects including algorithms, data structures, and theory of computation.

Her expertise spans Deep Learning, AI in Agriculture, Image Processing, Green IoT, and Computer Vision, with active involvement in research and academic leadership roles.

Work Experience

Madhuri Mishra served as Visiting Faculty at MNNIT Allahabad from 2017 to 2020 and at IIIT Lucknow in 2023.

She also worked as Placement Coordinator at IIIT Lucknow for three years, where she strengthened industry collaborations and facilitated over 700 direct industry connections for student placements.

Educational Qualification

To be updated

Research Interests

AI in Agriculture, Deep Learning, Image Processing, Green IoT, Computer Vision, Cloud Security.

Teaching Philosophy

Madhuri Mishra believes in bridging the gap between theoretical concepts and real-world applications to make learning more meaningful and industry-relevant.

Her teaching approach focuses on conceptual clarity, analytical thinking, and practical implementation to prepare students for both technical interviews and competitive examinations such as GATE.

She aims to develop students who are both academically strong and industry-ready through structured and application-oriented learning.

Courses Taught

Design and Analysis of Algorithms, Data Structures, Theory of Computation, Programming, Python, Deep Learning.

Awards and Achievements

Recognized for contributions in academic leadership, placement coordination, invited expert lectures, and research publications.

Scholarly Activities

Madhuri Mishra has contributed to research in Artificial Intelligence, computer vision, and cloud security.

Her work includes research on YOLOv8-transformer-based cattle behavior recognition, CLIP-based multimodal fake news detection, and cryptographic approaches for secure cloud data retrieval.

She actively participates in peer review activities and contributes to academic advancement through publications, expert lectures, and research collaboration.