Snigdha Agrawal completed her Ph.D. in Computer Science and Technology from Jawaharlal Nehru University, Delhi, India, in 2024. Her Ph.D. thesis was titled “Computer-Aided Diagnosis of Spinocerebellar Ataxia Using Machine Learning.” She earned her M.Tech. in Computer Science and Technology from Jawaharlal Nehru University, Delhi, in 2017, and her B.Tech. from BVCOE, New Delhi (GGSIPU), in 2015. She has been a recipient of the GATE, UGC NET, UGC JRF, and UGC SRF awards.

Since March 2025, she has been working as an Assistant Professor in the Department of Computer Science and Engineering at Delhi Technological University (DTU), Delhi, India. Prior to joining DTU, she served as an Assistant Professor in the Department of CSE & IT at Jaypee Institute of Information Technology, Noida. She has also worked as a visiting faculty member in the Department of Information Technology at DTU, Delhi. During her Ph.D., she collaborated with the Department of Neurology and the Department of NMR and MRI at the All-India Institute of Medical Sciences (AIIMS), New Delhi, for data collection related to her research. She was awarded the UGC-JRF and UGC-SRF fellowships during her Ph.D., along with a university fellowship during her M.Tech. at JNU.

Her research interests include Machine Learning, Image Processing, Neuroimaging, Computer Vision, Pattern Recognition, and Evolutionary Computing.

Courses Taught

• Programming with C, C++, Java
• Object Oriented Programming
• Fundamentals of Computer Vision
• Data Structures
• Discrete Structures
• Compiler Design
• Analysis and Design of Algorithms

Journal Publications

• S. Agrawal, R. K. Agrawal, B. Rana, S. S. Kumaran, and A. K. Srivastava “Sequential Multi-Stage Quantum Whale Optimization Algorithm for Biomarker Identification in Neurodegenerative Disorders and its Diagnosis”, (Communicated).
• S. Agrawal, R. K. Agrawal, B. Rana, S. S. Kumaran, and A. K. Srivastava “Identification of Atrophic Brain Regions in Neurodegenerative Disorders using Composite Kernel-based Support Vector Machine and 3D-Discrete Wavelet Transform”, (Communicated-Under Review).
• S. Agrawal, R. K. Agrawal, S. S. Kumaran, B. Rana, and A. K. Srivastava, “Integration of graph network with kernel SVM and logistic regression for identification of biomarkers in SCA12 and its diagnosis”, vol. 34, no. 4, 2024, Cerebral Cortex, Oxford Academic, doi: 10.1093/cercor/bhae132.
• S. Agrawal, R. K. Agrawal, S. S. Kumaran, A. K. Srivastava, and M. K. Narang, “Fusion of 3D feature extraction techniques to enhance classification of spinocerebellar ataxia type 12”, vol. 16, no. 1, pp. 91–103, Jan. 2024, International Journal of Information Technology, Springer Nature, doi: 10.1007/s41870-023-01579-y.
• S. Agrawal, S. S. Kumaran, A. K. Srivastava, R. K. Agrawal, and M. K. Narang, “Study of 2D Feature Extraction Techniques for Classification of Spinocerebellar Ataxia Type 12 (SCA12)”, vol. 290, pp. 670–674, 2022, Studies in Health Technology and Informatics, IOS Press, doi: 10.3233/SHTI220162.
• S. Agrawal, M. Narang, Pankaj, A. Srivastava, S. Kumaran, and R. Agrawal, “ROI based Machine Learning Classification Model for Spinocerebellar Ataxia type 12”, 2020, vol 1, pp. S8–S8, Movement Disorders, Wiley, doi: 10.1002/mds.28268.
• S. Agrawal, P. Gupta, V. Jain, and A. Jain, “Detection and Implementation of Web-based Attacks using Attribute Length Method,” vol. 120, no. 3, pp. 25–29, Jun. 2015, International Journal of Computer Applications, Foundation of Computer Science Inc., doi: 10.5120/21209-3901.
• P. Gupta, S. Agrawal, and N. Thakur, “Apparel Recommender System Based on Feature Selection and Self Organized Map”, vol 2, no. 3, pp. 96-100, Mar. 2015, International Journal of Engineering Research & Management, Eclat Research Publication Jaipur.

Conference Publications

• D. Lohani, B. Rana, S. S. Kumaran, A. K. Srivastava, S. Agrawal, Pankaj “Integrating Tensor-Based Morphometry with Machine Learning for Diagnosis of SCA12”, in 2025 International Society for Magnetic Resonance in Medicine (ISMRM) Indian Chapter, Feb. 2025, 82.
• D. Lohani, B. Rana, S. S. Kumaran, A. K. Srivastava, S. Agrawal, Pankaj “Spinocerebellar Ataxia Type 12 classification through Structural MRI: Insights from Regional Brain Volume and Cortical Thickness Analysis”, in 2024 IEEE International Conference on Computer Vision and Machine Intelligence (CVMI), Oct. 2024, pp. 1–6. doi: 10.1109/CVMI61877.2024.10781980.
• Pankaj, S. Kumaran, S. Agrawal, A. Srivastava, and R. Agrawal, “Structural and resting state network alterations in Spinocerebellar Ataxia Type 2 in comparison with healthy controls” in 2020 International Society for Magnetic Resonance in Medicine (ISMRM), 2020, 1547.