3SCity-E2C Collaboration:

Ask him about “Fog/Edge Computing” and “Database Management”

Meet Dr Souvik Sengupta, a highly skilled and accomplished young computer scientist with a strong educational background in the field of Computer Science. Souvik holds a Bachelor's degree in Computer Science and Engineering from West Bengal University of Technology and a Master's degree in Distributed and Mobile Computing from Jadavpur University, one of India's premier universities. Souvik is a recipient of multiple European fellowships, including the Erasmus Mundus student exchange scholarship for pursuing the final year of a Master's degree at a prestigious university in Hungary, and the FP7 scholarship from the Ministry of Science and Innovation in Spain. Souvik is currently working as a Senior Lead Researcher in IONOS SE's Digital Ecosystems Solutions group. Prior to joining IONOS, Souvik worked as a Chief Research Engineer and Administrator at iExec Blockchain Tech in Lyon, France. Before iExec he was working as a Research Engineer at Fundacio - i2CAT - a Primer Digital and 5G research lab in Catalunya. Back on 2017, Souvik joined the CRAAX Lab UPC as a researcher for pursuing the PhD. He worked in various Spanish national and European projects, including one Govt of India, MHRD-funded project, one FP7 project, and almost 7 EU H2020 projects, and coordinated a few Horizon Europe proposals. Souvik has a broad range of experience in various domains such as Distributed Computing, Big Data, Cloud Infrastructure, Edge-Cloud Infrastructure, 5G Computation segment, Blockchain, Machine Learning and Federated Machine Learning etc. Currently, Souvik's research focus is on Privacy-preserving computation framework over the Cloud- Edge infrastructure. Souvik is well-versed in a variety of programming languages, including, Java, JavaScript and Python, and is experienced in software development, advanced machine learning, and distributed systems.

His current research interest includes Fog/Edge computing, Cloud Computing, IoT, Database Management, Machine Learning

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