0000-0001-7137-629X About
Dr. Suneeta Mohanty has 21 years of teaching experience in Computer Science & Engineering. She earned her M.Tech degree in Computer Science & Engineering from College of Engineering & Technology which is a constituent college of BPUT, Odisha. She earned her Ph.D. from KIIT Deemed to be University, Odisha. She has been a life member of ISCA, ISTE and IET. Her research interests include Cloud Computing, Network Security, WSN, IoT. Her research contribution includes 02 co-edited books published by Springer Nature, more than 56 research publications in reputed conferences, book chapters and journals indexed in Scopus/SCI/Web of Science. As an organizing chair she has organized one International conference SCI, 2018 and has been part of different core committees of other conferences and workshops. She has eleven international patents to her credit.
Employment
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KIIT University Associate Professor2007 - Present
Education
Education history is unavailable.
Projects & Funding
Projects & funding information is unavailable.
Publications (66)
- Conversational Text Extraction with Large Language Models Using Retrieval-Augmented Systems Save
- Application of Optimized Artificial Neural Networks to Enhance Medical Data Interpolation Save
- Patient Health Surveillance System for Acute Kidney Disease Prediction Applying Machine LearningApproaches Save
- OPTIMIZING CLOUD COSTS AND CARBON FOOTPRINT IN MULTI-CLOUD ENVIRONMENTS WITH FUZZY LOGIC & MONTE CARLO SIMULATION Save
- Neutrosophic Hierarchical Clustering: A Novel Approach for Handling Uncertainty in Multi-Level Data Organization Save
- Neuromorphic computing for machine learning: An overview Save
- L-MCAT: Unpaired Multimodal Transformer with Contrastive Attention for Label-Efficient Satellite Image Classification Save
- Embedded and Cloud Computing for Ingesting Big Multimedia Data in IOT Sensor Networks Applications Save
- Convolutional Neural Network Segmentation for Satellite Imagery Data to Identify Landforms Using U-Net Architecture Save
- Convolutional Neural Network Segmentation for Satellite Imagery Data to Identify Landforms Using U-Net Architecture Save