0000-0001-9895-116X About
I am a researcher and educator in Computer Science & Engineering, with a specialization in Human Activity Recognition (HAR), Machine Learning (ML), Computer Vision, and Deep Learning. My expertise extends to IoT (Internet of Things), IoV (Internet of Vehicles), Edge Computing, software development, embedded systems deployment, and data analytics. I am passionate about bridging the gap between academic research and industry applications.
My research primarily focuses on developing advanced machine learning frameworks for abnormal human activity recognition using video surveillance, leveraging deep learning architectures like CNNs, RNNs, Transformers, and attention mechanisms. In addition to academic research, I have worked on industrial projects involving Data Fabric architectures, GIS-based analytics, and AI-driven solutions for the energy sector, including grid analytics, anomaly detection, and large-scale data processing.
Passionate about research, mentoring, and innovation, I thrive in collaborative environments that foster problem-solving and knowledge sharing. Whether optimizing ML workflows, enhancing data quality, or enabling intelligent analytics for smart infrastructures, I am dedicated to advancing technology and empowering the next generation of engineers and researchers.
Let’s connect and explore opportunities for collaboration in advancing intelligent computing systems.
Employment
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Galgotias University Assistant Professor2026 - Present
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Delhi Technological University Research Scholar2022 - Present
Education
Education history is unavailable.
Projects & Funding
Projects & funding information is unavailable.
Publications (7)
- Occluded skeleton-based multi-stream model using Part-Aware Spatial–Temporal Graph Convolutional Network for human activity recognition Save
- STAD-ConvBi-LSTM: Spatio-temporal attention-based deep convolutional Bi-LSTM framework for abnormal activity recognition Save
- Activity Recognition in Dynamic Environments Using Image Enhancement and Vision Transformers with DETR Save
- Threat of Adversarial Attacks within Deep Learning: Survey Save
- ConvST-LSTM-Net: convolutional spatiotemporal LSTM networks for skeleton-based human action recognition Save
- Enhancement of Steganography Using K Strange Point Clustering Save
- Privacy Preserving in TPA for Secure Cloud By Using Encryption Technique Save