Dr. Satvik Vats
Assistant Professor
RESEARCH AREA
Big data, Deep Learning, Machine Learning, Digital Health, Smart Agriculture (Hybrid Approach of Machine learning Techniques such as supervised and unsupervised learning with integration of Big Data analytics and deep learning concepts.
EDUCATION
AWARDS/HONORS
Dr. Satvik Vats is an Assistant Professor in the Department of Computer Science and Engineering at Graphic Era Hill University, Dehradun. He earned his Ph.D. in Computer Science and Engineering from Birla Institute of Technology, Mesra-Ranchi, Jharkhand, India. With a remarkable research portfolio, Dr. Vats has authored multiple research papers in internationally renowned journals and conferences, including SCI, SCIE, ESCI, SCOPUS, and Web of Science indexed sources. His scholarly contributions extend to 13 patents and three published books, along with two book chapters in esteemed international publications.
He is awarded the “Young Scholar Award” at the International Conference on Network and Cryptology 2020, organized by the School of Computer and Systems Sciences, Jawahar Lal Nehru University (JNU), New Delhi. Dr. Vats has organised multiple conferences of international reputes. He is initiated conferences series such as AutoCom and CyberCom in Graphic Era Hill University, Dehradun, Uttarakhand. Dr. Vats has Worked as AI researcher on iDoc-X model (Research Project), which is a seamlessly integrated software of iDoc.ai (an initiative of Teleglobal Consulting LTD, UK) that identifies different diseases on Chest X-Ray. In addition to this, He Designed a platform-independent model for Big Data Analytics based on three different MASTERS_NODES on the HADOOP platform, which uses different data analytics tools to share a common infrastructure to provide data independence and resource sharing environment. He is reviewer and editorial member of various journals of international repute such as IEEE Access, SN Computer Science, JDMSC (Taylor & Francis), MDPI (Sensors), MDPI (Journal of Clinical Medicine), MDPI (Applied Sciences). Currently, he is working on a “Hybrid Approach of Machine learning Techniques such as recommender systems and supervised and unsupervised learning with integration of Big Data analytics and deep learning concepts.
RESEARCH DETAILS
ORCID ID: 0000-0002-9422-4915
Scopus ID: 57193131437
Vidwan ID: 400132
Web of Science ID: AAU-6249-2020
Google Scholar ID: https://scholar.google.com/citations?hl=en&authuser=1&user=LpBnm-4AAAAJ
Research Gate ID: https://www.researchgate.net/profile/Satvik-Vats
The application process at Graphic Era is strictly based on the Merit of the qualifying examination with the entire Admission Process available for completion online