Amit Sharma
From
Institute of Computer Technology, Southern Federal University - RU
In residence at
PRISME Laboratory / University of Orléans, INSA CVL - FR
Host scientist
Frédéric Ros
BIOGRAPHY
Amit Sharma is a distinguished researcher specializing in Machine Learning, Deep Learning, the Internet of Things (IoT), and Wireless Sensor Networks (WSNs). He is currently a Senior Researcher under the JUNON programme at the PRISME Laboratory, University of Orléans, in collaboration with INSA Centre Val de Loire, France. His current research, supported by LE STUDIUM, focuses on the integration of heterogeneous data and algorithms to develop intelligent interfaces for digital twins, aiming to advance digital engineering and smart systems.
Previously, Amit Sharma served as a Senior Researcher at Southern Federal University, Russia, where he worked on applying Graph Neural Networks to address challenges in healthcare and sustainable smart cities. His notable projects also include the development of a Forest Fire Detection System using IoT-enabled WSNs and predictive AI models for disease diagnosis.
His research interests and competencies include graph neural networks, machine learning, artificial intelligence, big data, cloud computing, data science, and technologies such as wireless sensor networks and the Internet of Things. Dr. Amit has published multiple papers in reputed journals and conferences and contributed to the advancement of scientific knowledge and innovation in these domains. Dr. Amit is also passionate about sharing insights and expertise with the next generation of computer science students, designing and delivering engaging lectures and labs, supervising student projects, and collaborating with other faculty and researchers on interdisciplinary topics. His goal is to apply skills and knowledge to real-world problems, such as environment monitoring, smart cities, UAV communications, and sustainable development, and to explore new challenges and opportunities in the field.
Research projects:
- Winner of the competitive selection of the postdoc program of the Southern Federal University, project N PD/22-02-KT “Theory and applications of graph neural networks, soft machine learning algorithms” (2022-2024).
- Research Associate in a project “Early Forest Fire Detection System using WSN and IOT for HP Mountains” sponsored by H.P. State Council for Science Technology and Environment, Shimla under grant of HP Specific Research and Development Projects 2016-17.
PROJECT
Integration of heterogeneous data and algorythms, and development of intelligent interfaces for digital twins
The JUNON ARD CVL programme aims to build digital twins and to design digital services to improve the monitoring and understanding of the environment for a better management of natural resources (soil, water, atmosphere). The ambition is to place environmental and digital research at the heart of the regional innovation strategy and to bring useful data and services to multiple socio-economic partners.
The project aims to integrate heteregenous data in the planned architecture and algorythms in the prototypes developed for the various digital twins focusing on software design pertaining to architecture, user interface (HMI), and communication protocols. The development of the machine learning protocol stands at the heart of creation of the digital twins. The project plans the creation of intelligent interfaces enabling non-expert users to manipulate or use the various digital twins in a very user-friendly way.
The overall objective is that the digital twins can efficiently interact with the central components of the system, abstracting the implementation details while ensuring smooth communication and cooperation among different parts of the architecture.
