Amit Sharma
Southern Federal University, Chitkara University, Punjab Technical University, Jaypee University of Information Technology
About
I've completed my Ph.D. in Computer Science at Jaypee University of Information Technology, India. I am grateful to be supported by the Ministry of Human Resource Development with Research Fellowship for pursuing my Ph.D. I am currently workinig as an Assistant Professor in Computer Science Department at Chitkara University. I want to do research-oriented work. My work will cover both theoretical and practical view of any field, on which I will work. My major area of work are Application of Wireless Sensor Networks, Internet of Things, Algorithms, Image Processing, Machine Learning.
Employment
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Southern Federal University Senior Researcher2022 - 2024
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Chitkara University Assistant Professor2021 - 2026
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Jaypee University of Information Technology Teaching Assistant2017 - 2020
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Jaypee University of Information Technology Project Associate2016 - 2018
Education
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Punjab Technical University B.Tech2007 - 2011
Projects & Funding
Projects & funding information is unavailable.
Publications (38)
- UAV‐based framework for effective data analysis of forest fire detection using 5G networks: An effective approach towards smart cities solutions Save
- Synergistic Integration of 5G-Enabled Cloud Native Infrastructures With Advanced Technologies for Urban Safety Enhancement Save
- AI and UAVs in Smart Transportation of Urgent Organ Transplant and Usage for Organ Donor and Donee Save
- IoT and AI-Based Smart Healthcare Monitoring System Save
- Real-Time Organ Status Tracking System for Digital Healthcare Save
- Smart Implementation of IoT and UAVs-Based Transportation of Blood Samples for Digital Healthcare Save
- Smart Management Based on Deep Data Analysis for Digital Healthcare Save
- An IoT and Blockchain-based approach for the smart water management system in agriculture Save
- Graph Neural Network-Based Anomaly Detection in Blockchain Network Save
- Internet of Medical Things (IoMT) Application for Detection of Replication Attacks Using Deep Graph Neural Network Save