SATHEESH KUMAR SAMPATH

About

Dr. S. Satheesh Kumar is a Proficient academician and researcher with over 16 years of experience in the field of Computer Science. His expertise spans Data Mining, Machine Learning, Data Analytics, the Internet of Things (IoT), Computer Networks, and Big Data Technologies. He received his Ph.D. in Master of Computer Applications from Visvesvaraya Technological University (VTU), Karnataka, India. He serves as an Assistant Professor in the Department of Bachelor of Computer Applications at Presidency University, Bengaluru. He has authored and co-authored numerous research papers in reputed international journals, book chapters, and conference proceedings. In addition, he is a patent holder, with multiple innovations to his credit, including an Indian Patent granted for his research contributions. His research interests encompass a wide range of domains, including IoT, Network Security, Data Mining, Data Security, Artificial Intelligence, and Machine Learning. He is also an active reviewer for several national and international journals, contributing to the advancement of knowledge and research in emerging technologies.

Employment

• Presidency University, Bengaluru Assistant Professor
  2025 - Present
• REVA University Assistant Professor
  2019 - 2022
• Acharya Bangalore B-School ASSISTANT PROFESSOR
  2018 - 2019
• Dayananda Sagar Academy of Technology and Management ASSISTANT PROFESSOR
  2014 - 2018
• Sri Nandhanam College of Engineering and Technology ASSISTANT PROFESSOR
  2009 - 2013

Education

• Priyadarshini Engineering College MCA
  2005 - 2008

Projects & Funding

Projects & funding information is unavailable.

Publications (26)

• Edge-Driven Multimodal Fusion Framework for Real-Time EmotionAware Vehicular Networks
  Autonomous Systems in the Internet of Vehicles 2026 DOI: 10.1002/9781394311729.ch13
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• Machine Learning Model Comparative Analysis for IoMT Data Security
  Advanced Explorations in Machine Learning Computer Vision and Iot 2026
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• A Cognitive Edge-Driven Autonomous Learning System for Scalable and Secure IoV Automation
  Autonomous Systems in the Internet of Vehicles 2026 DOI: 10.1002/9781394311729.ch1
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• Securing the Future of IoMT
  2025 DOI: 10.4018/979-8-3693-6180-1.ch008
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• Adaptive error approximate data reconciliation technique for healthcare framework
  International Journal of System Assurance Engineering and Management 2024 DOI: 10.1007/s13198-022-01744-9
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• A Quantitative Approach of Purposive Sampling Techniques for Security and Privacy Issues in IoT Healthcare Applications
  2023 DOI: 10.4018/978-1-6684-6971-2.ch016
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• Deep Learning Based Hybrid Network Architecture to Diagnose IoT Sensor Signal in Healthcare System
  Journal of Machine and Computing 2023 DOI: 10.53759/7669/jmc202303011
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• Efficient key exchange protocol for industrial internet of things
  AIP Conference Proceedings 2022 DOI: 10.1063/5.0109623
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• E-Collaboration for Management Information Systems Using Deep Learning Technique
  2022 DOI: 10.4018/978-1-7998-9640-1.ch026
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• Efficient Authentication for Securing Electronic Health Records using Algebraic Structure
  2021 5th International Conference on Electrical, Electronics, Communication, Computer Technologies and Optimization Techniques (ICEECCOT) 2022 DOI: 10.1109/iceeccot52851.2021.9708050
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