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Dr. Gayathri Parasa

Assistant Professor (Sr. Gr), Department of Computer Science Engineering, School of Computing, Amaravati

Qualification: Ph. D., M.Tech., B.Tech
p_gayathri@av.amrita.edu
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Research Interest: Machine Learning, Deep Learning, Image Processing

Bio

Dr. Gayathri Parasa is an Assistant Professor (Sr. Gr) in the Department of Computer Science and Engineering, School of Computing Amaravati. She received her Ph.D. from Annamalai University. She has over a decade of teaching and research experience. Her research interests include Artificial Intelligence (AI) with expertise in Machine Learning and Deep Learning, Data and Text Mining, Image Processing, Computer Vision, Computer Networks and Medical Image Analysis.

Publications

Conference Paper

Year : 2026

Pandemic Shockwaves and Sectoral Economic Resilience: Evidence from the Indian Economy

Cite this Research Publication : Rachna Rathore, Sandeep Gehlot, V Sumalatha, Revathi S, Gayathri Parasa, R Chinnaiyan, Pandemic Shockwaves and Sectoral Economic Resilience: Evidence from the Indian Economy, 2026 2nd International Conference on Cognitive Computing in Engineering, Communications, Sciences and Biomedical Health Informatics (IC3ECSBHI), IEEE, 2026, https://doi.org/10.1109/ic3ecsbhi67834.2026.11468864

Publisher : IEEE

Year : 2026

BioVisionNet: Deep Morphological Learning for Biomedical Image Segmentation

Cite this Research Publication : S. Siva Shankar, Gayathri Parasa, K Kiran, Praveen Mittal, Minu Balakrishnan, Veeraswamy Ammisetty, Rasmi A, BioVisionNet: Deep Morphological Learning for Biomedical Image Segmentation, 2026 International Conference on ICT and Photonics (ICTP), IEEE, 2026, https://doi.org/10.1109/ictp67998.2026.11485193

Publisher : IEEE

Year : 2026

A Hybrid LSTM-Based Model for Stock Price Prediction Using Sentiment Analysis and Volatility Features

Cite this Research Publication : Ajay Adapa, Venkata Bhargava Adithya Kothamasu, Raghunadhreddy Sure, Lokesh Reddy Gundlakunta, Gayatri Parasa, A Hybrid LSTM-Based Model for Stock Price Prediction Using Sentiment Analysis and Volatility Features, 2026 IEEE 18th International Conference on Computational Intelligence and Communication Networks (CICN), IEEE, 2026, https://doi.org/10.1109/cicn70047.2026.11594077

Publisher : IEEE

Year : 2026

A Comprehensive Survey on Food Image Recognition and Calorie Estimation Systems: Techniques, Datasets, Challenges, and Future Directions

Cite this Research Publication : Gayathri Parasa, Ganga Singh Chauhan, M Radha Krishna, Jayapal Lande, M Nisha, Vikas Nair, A Comprehensive Survey on Food Image Recognition and Calorie Estimation Systems: Techniques, Datasets, Challenges, and Future Directions, 2026 1st International Conference on AI, Data Science, Cyber Security and Smart Manufacturing for Sustainable Development (ICADCS), IEEE, 2026, https://doi.org/10.1109/icadcs70036.2026.11583455

Publisher : IEEE

Journal Article

Year : 2026

Lightweight Convolutional Neural Network based Resource-Aware Energy-Efficient Detector within Edge–Fog-enabled Industrial IoT systems

Cite this Research Publication : Ashwin. M and Phani Kumar Solleti and Sarangam Kodati and T. Ravi and Gayathri Parasa and Mangalapalli Vamsikrishna and D. Vetrithangam, Lightweight Convolutional Neural Network based Resource-Aware Energy-Efficient Detector within Edge–Fog-enabled Industrial IoT systems, International Journal for Global Academic \& Scientific Research, [publisher], 2026, https://api.semanticscholar.org/CorpusID:286742546

Year : 2025

Multi-Agent AI Systems for Decentralized Decision-Making

Cite this Research Publication : Manisha Bhende, Shripad Joshi, C. Gouri Sainath, Surendarkumar S, Moghal Yaseen Pasha, Gayatri Parasa, Multi-Agent AI Systems for Decentralized Decision-Making, 2025 Global Conference on Information Technology and Communication Networks (GITCON), IEEE, 2025, https://doi.org/10.1109/gitcon65266.2025.11377018

Publisher : IEEE

Year : 2025

Recommendation learning management system for autism using deep convolutional neural networks and gene expression programming

Cite this Research Publication : Tholkapiyan. M, D. Krishna Madhuri, R. Sundar, Gayatri Parasa, Vivek Duraivelu, N. Krishnaveni, Recommendation learning management system for autism using deep convolutional neural networks and gene expression programming, Edelweiss Applied Science and Technology, Learning Gate, 2025, https://doi.org/10.55214/25768484.v9i2.4625

Publisher : Learning Gate

Year : 2023

A novel optimization based deep learning with artificial intelligence approach to detect intrusion attack in network system

Cite this Research Publication : S. Siva Shankar, Bui Thanh Hung, Prasun Chakrabarti, Tulika Chakrabarti, Gayatri Parasa, A novel optimization based deep learning with artificial intelligence approach to detect intrusion attack in network system, Education and Information Technologies, Springer Science and Business Media LLC, 2023, https://doi.org/10.1007/s10639-023-11885-4

Publisher : Springer Science and Business Media LLC

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