Dr. Sakshi Indolia

Assistant Professor,

School of Technology Management & Engineering

PhD, CSE (Banasthali Vidyapith, Rajasthan), M.Tech. (Banasthali Vidyapith, Rajasthan), B.E (MDU, Rohtak)

Email ID: sakshi.indolia @nmims.edu

Subject teaching:

Artificial Intelligence,

Deep Learning,

Introduction to Augmented Reality and Virtual Reality.

Experience

• 5 Years of Teaching Experience.

Research Interest

Machine Learning, Deep Learning, Emotion Recognition.

Research Publications

List of Journals:

1. Sakshi Indolia, Swati Nigam, and Rajiv Singh, "A Framework for Facial Expression Recognition using Deep Self Attention Network,” Journal of Ambient Intelligence and Humanized Computing, Springer, vol. 14, pp. 9543–9562, 2023. https://link.springer.com/article/10.1007/s12652-023-04627-4
2. Sakshi Indolia, Swati Nigam, and Rajiv Singh, "Micro Expression Recognition Using Convolution Patch in Vision Transformer”, IEEE Access, vol. 11, pp. 100495-100507, 2023. [SCI Impact Factor=3.9] https://ieeexplore.ieee.org/document/10250810
3. Sakshi Indolia, Swati Nigam, and Rajiv Singh, "A Self Attention Based Fusion Framework for Facial Expression Recognition in Wavelet Domain”, The Visual Computer (TVCJ), [SCI Impact Factor=3.5] 

List of Conferences:

1. Sakshi Indolia, Anil Kumar Goswami, S.P. Mishra, & Pooja Asopa, "Conceptual Understanding of Convolutional Neural Network-A Deep Learning Approach”, In Procedia Computer Science, 132, 679-688, 2018.
2. Sakshi Indolia, Swati Nigam, and Rajiv Singh. "An Optimized Convolution Neural Network Framework for Facial Expression Recognition." 2021 Sixth International Conference on Image Information Processing (ICIIP),  IEEE, 2021.
3. Sakshi Indolia, Swati Nigam, and Rajiv Singh.  "Deep Feature Fusion for Facial Expression Recognition.” International Conference on Next Generation Intelligent Systems (ICNGIS 2022). IEEE, 2022.
4. Sakshi Indolia, Swati Nigam, and Rajiv Singh. "Integration of Transfer Learning and Self-Attention for Spontaneous Micro-Expression Recognition."  in Seventh International Conference on Parallel, Distributed and Grid Computing (PDGC). IEEE, 2022 

Book Chapters:

1. Sakshi Indolia, Swati Nigam, and Rajiv Singh, "Deep Learning for Emotion Recognition using Physiological Signals”, Data Fusion Techniques and Applications, Elsevier.