Sangeetha S K B
Manipal University, SRM Institute of Science and Technology, RMK College of Engineering and Technology
0000-0002-6927-6916
About
My recent research interests lie in design, analysis, and implementation of machine learning algorithms. I am
particularly interested in machine learning tools for analysing the overall behaviour of classification methods in
image processing. My primary research goal is to formalize and explicitly address all constraints and important
challenges of image processing, including statistical efficiency and computational efficiency. Analysis of algorithms
beyond the worst case and more generally identifying interesting and realistic models of computation that provide
a better alternative to traditional worst-case models in a broad range of optimization problems.
Employment
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Manipal University Associate Professor2025 - Present
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SRM Institute of Science and Technology Assistant Professor(Sr.G)2020 - 2025
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RMK College of Engineering and Technology Assistant Professor2019 - 2020
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Rajalakshmi Engineering College Assistant Professor2017 - 2019
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Velammal Engineering College Assistant Professor2010 - 2017
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Karunya University Assistant Professor2009 - 2009
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Sri Subramanya College of Engineering and Technology Lecturer2005 - 2007
Education
Education history is unavailable.
Projects & Funding
Projects & funding information is unavailable.
Publications (25)
- An Empirical Analysis of Transformer-Based and Convolutional Neural Network Approaches for Early Detection and Diagnosis of Cancer Using Multimodal Imaging and Genomic Data Save
- Dynamic AI-Enhanced Therapeutic Framework for Precision Medicine Using Multi-Modal Data and Patient-Centric Reinforcement Learning Save
- Exploring Hybrid Techniques for Enhanced Pitch Estimation in Speech Processing Save
- Advancements in urban scene segmentation using deep learning and generative adversarial networks for accurate satellite image analysis Save
- An Empirical Analysis of Multimodal Affective Computing Approaches for Advancing Emotional Intelligence in Artificial Intelligence for Healthcare Save
- Secure Healthcare Access Control System (SHACS) for Anomaly Detection and Enhanced Security in Cloud-Based Healthcare Applications Save
- Decoding Emotions Using Deep Learning Approach to EEG-Based Emotion Recognition Save
- Effect of Urbanization Through Land Coverage Classification Save
- A Deep Learning Approach to Detect Microsleep Using Various Forms of EEG Signal Save
- A proficient video recommendation framework using hybrid fuzzy C means clustering and Kullback-Leibler divergence algorithms Save