Faculty at School of Engineering

Nazil Perveen

Nazil Perveen

Assistant Professor


Contact Information

Dr. Nazil Perveen is currently working as an Assistant Professor in the Department of Computer Science and Engineering, Shiv Nadar Institution of Eminence, Delhi-NCR, India. Before this, she was a Postdoctoral Fellow at the University of Manchester, UK. She received her Ph.D. from IIT Hyderabad in Applied Machine Learning.

Her research interests include computer vision and machine learning applications to understand and explore, but are not limited to, emotion recognition, healthcare, human cognitive level recognition, and human behavior.

She is currently teaching CSD361 – Introduction to Machine Learning (Monsoon 2026). Previously, she taught CSD204 – Operating Systems (Spring 2026), CSD101 – Introduction to Computing and Programming (Summer 2025), and CCC634 – A Gentle Introduction to Python (Monsoon 2025).

For more information, please visit her personal website.

  • Ph.D., Indian Institute of Technology Hyderabad (IIT-H), Telangana (2020)
  • M.Tech, National Institute of Technology Raipur (NIT Raipur), Chhattisgarh (2012)
  • B.E., Institute of Technology-GGU Central University (IT-GGU), Chhattisgarh (2009)

  • Assistant Professor, Shiv Nadar Institution of Eminence, India (April 2025–Present)
  • Postdoctoral Fellow, University of Manchester, Manchester, UK (November 2021–November 2022)
  • Distinguished Researcher (Honorary Position), Target India, Bangalore, India (May 2020–November 2022)
  • Senior Engineer, Micron Technologies, Hyderabad, India (August 2021–November 2021)
  • Assistant Professor, Department of Computer Science and Engineering, Guru Ghasidas University, India (August 2012–May 2013)
  • Assistant Professor, Department of Computer Science and Engineering, Guru Ghasidas University, India (August 2013–June 2014)

Facial Expression Recognition, Emotion Recognition, AI in Healthcare, Human Cognitive Load Estimation, Facial Paralysis, Improving In-Car Cabin Experiences, etc.

  • University Gold Medalist in both B.E. and M.Tech.
  • Recipient of JASSO Scholarship.
  • Recipient of the Institute Research Excellence Award, 2017 & 2021.
  • Recipient of the Institute Certificate of Appreciation in Research, 2018.

  1. Nazil Perveen, D. Roy, and C. K. Mohan, “Facial Expression Recognition in Videos Using Dynamic Kernels,” IEEE Transactions on Image Processing, vol. 29, pp. 8316–8325, 2020. DOI: 10.1109/TIP.2020.3011846
  2. Nazil Perveen, D. Roy, and C. K. Mohan, “Spontaneous Expression Recognition Using Universal Attribute Model,” IEEE Transactions on Image Processing, vol. 27, no. 11, pp. 5575–5584, November 2018.
  3. Y. Sravani, Nazil Perveen, C. Vishnu, and C. Krishna Mohan, “Fine-grained Action Recognition Using Dynamic Kernels,” Pattern Recognition, vol. 122, 2022, 108282. DOI: https://doi.org/10.1016/j.patcog.2021.108282
  4. Rajeshreddy Datla, Nazil Perveen, and Krishna Mohan C., “Learning Scene Vectors for Remote Sensing Image Scene Classification,” Neurocomputing, vol. 587, 2024, 127679. DOI: https://doi.org/10.1016/j.neucom.2024.127679

Nazil Perveen, C. K. Mohan, and Yen-Wei Chen, “Quantitative Assessment of Facial Paralysis Using Dynamic Kernel Modeling,” submitted to Communications in Computer and Information Science, Springer.

  • Nazil Perveen and C. K. Mohan (2020). “Configural representation of facial action units for spontaneous facial expression recognition in the wild,” In Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, ISBN 978-989-758-402-2, pages 93-102. DOI: 10.5220/0009099700930102.
  • Nazil Perveen, C. K. Mohan and Chen, Y. (2020). “Quantitative analysis of facial paralysis using GMM and dynamic kernels,” In Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP, ISBN 978-989-758-402-2, ISSN 2184-4321, pages 173-184. DOI: 10.5220/0009104801730184.
  • Nazil Perveen, D. Singh, and C. K. Mohan, “Spontaneous facial expression recognition: A part-based approach,” 2016 15th IEEE International Conference on Machine Learning and Applications (ICMLA), Anaheim, CA, 2016, pp. 819-824. DOI: 10.1109/ICMLA.2016.0147.
  • Yenduri, S., Perveen, N., Chalavadi, V. and Mohan, C. (2022). “Fine-grained Action Recognition using Attribute Vectors.” In Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP, ISBN 978-989-758-555-5; ISSN 2184-4321, pages 134-143. DOI: 10.5220/0010828700003124.

  • Curriculum Design of CSD361: Introduction to Machine Learning
  • Curriculum Design of CSD204: Operating Systems
  • Curriculum Design of CCC634: Introduction to Python
  • Lab Design of CSD361: Introduction to Machine Learning
  • Lab Design of CSD1001: Introduction to Computing
  • Lab Design of CSD204: Operating Systems

Reviewer in ICASSP, ACM IKDD, Springer Nature, Multimedia Tools and Applications, CVIP, CVMI, ICVGIP, etc.