ଗଙ୍ଗାଧର ମେହେର ବିଶ୍ୱବିଦ୍ୟାଳୟ, ସମ୍ବଲପୁର, ଓଡିଶା
Gangadhar Meher University, Sambalpur, Odisha
Assistant Professor
School of Computer Science
Ph.D. Utkal University (Ph.D. research work carried out at i)FBK Research Center, Trento, Italy, ii)Trento University, Italy, and iii)Utkal University), M.Tech. (E-Gov) Trento University Italy, M.Tech. (CS) Utkal University
Machine Learning, Soft Computing, Formal Language Design
EasyBand: A Wearable for Safety-Aware Mobility During Pandemic Outbreak
IEEE CEM
Ajaya K. Tripathy, Ambarish G. Mohapatra, Saraju P. Mohanty, Elias Kougianos, Amit M. Joshi, and Gautam Das,
WoS Indexed: Yes; Scopus Indexed: Yes; UGC Care Listed: Yes; vol: 9; pg: 57-61; Publisher: IEEE; Impact Factor: 4.5; DOI : 10.1109/MCE.2020.2992034iTour: The Future of Smart Tourism
IEEE CEM
Ajaya K. Tripathy, Pradyumna K. Tripathy, Niranjan K. Ray, Saraju P. Mohanty
WoS Indexed: Yes; Scopus Indexed: Yes; UGC Care Listed: Yes; vol: 7; pg: 32-37; Publisher: IEEE; Impact Factor: 4.5; DOI : 10.1109/MCE.2018.2797758A SVM-based classification approach for obsessive compulsive disorder by oxidative stress biomarkers
Journal of Computational Science
Abhijeet Shrivastava, Ajaya Kumar Tripathy, Pronob Kumar Dalal
WoS Indexed: Yes; Scopus Indexed: Yes; UGC Care Listed: Yes; vol: 36; pg: 101023; Publisher: Elsevier; Impact Factor: 3.1; DOI : https://doi.org/10.1016/j.jocs.2019.07.010Fuzzy QoS requirement-aware dynamic service discovery and adaptation
Applied Soft Computing
AK Tripathy, PK Tripathy
WoS Indexed: Yes; Scopus Indexed: Yes; UGC Care Listed: Yes; vol: 68; pg: 136-146; Publisher: Elsevier; Impact Factor: 8.7; DOI : https://doi.org/10.1016/j.asoc.2018.03.038A novel hybrid machine learning approach for change detection in remote sensing images
Engineering Science and Technology, an International Journal
C Pati, AK Panda, AK Tripathy, SK Pradhan, S Patnaik
WoS Indexed: Yes; Scopus Indexed: Yes; UGC Care Listed: Yes; vol: 23; pg: 973-981; Publisher: Elsevier; Impact Factor: 5.7; DOI : https://doi.org/10.1016/j.jestch.2020.01.002About
Dr. Ajaya Kumar Tripathy has been a faculty member of the School of Computer Science, Gangadhar Meher University since 2020. Prior to joining this institution, he served as a faculty member in the Computer Science and Engineering department at the Silicon Institute of Technology in Bhubaneswar, India, from 2010 to 2019. Dr. Tripathy earned his Ph.D. in computer science from Utkal University in 2015. During the years 2008 to 2010, he pursued his Ph.D. studies at Trento University in Italy, where he was affiliated with the SOA Research Unit at Fondazione Bruno Kessler (FBK) in Trento, Italy. Dr. Tripathy has gained valuable experience as a research assistant (internee) at the Machine Intelligence Unit, Indian Statistical Institute in India and the Createnet Research Center in Trento, Italy. He also attended the Research Summer School in Crete, Greece, in 2009. Additionally, Dr. Tripathy holds a Professional M.Tech. degree in e-Government from Trento University, Italy, which he obtained in 2008. He completed his M.Tech. in Computer Science at Utkal University, India, in 2007. Dr. Tripathy qualified in the national GATE (Graduate Aptitude Test in Engineering) for Computer Science in the year 2006. His research interests encompass a wide range of topics, including pattern recognition, machine learning, data mining, soft computing, and Formal Language Design. Furthermore, he has an impressive track record of publishing numerous research papers in prestigious international journals and conferences.
saraju.mohanty[at]unt.edu
Dept of CSE, University of North Texas, USA.
Research Collaboration
Machine Learning and Cyber-Physical Systems for Smart Cities
mrpatra12@gmail.com
Department of Computer Science, Berhampur University
Research Collaboration
Service Oriented Architecture and Formal Language Processing
MD (Psychiatry)Professor (Additional)
drsujita@gmail.com
King George's Medical University
Research Collaboration
Bioinformatics
Professor
University of North Texas, USA
Research Collaboration
Machine Learning and Cyber-Physical Systems for Smart Cities
Professor
CSE Dept, University of Texas at Arlington, USA
Research Collaboration
Machine Learning and Cyber-Physical Systems for Smart Cities
PhD Student
School of CS, Gangadhar Meher University
PhD Student (Active)
Bioinformatics
Dept. of Electronics & Comm. Engineering, Malaviya NIT
Research Collaboration
Machine Learning and Cyber-Physical Systems for Smart Cities
Additional Professor of Psychiatry
AIIMS Bhubaneswar
Research Collaboration
Bioinformatics
The increasing recognition of the importance of setting up monitoring for Service-Based Systems (SBS) is due to the fact that even though SBS's service composition assumptions and requirements are verified during design, they can still be violated during runtime. This is particularly true for web service-based systems, which often rely on services provided by third parties that operate independently and can change without notice, causing runtime issues. When such deviations are detected, they need to be identified and analyzed to take appropriate action. For example, a bank might suddenly refuse to transfer money to a partner hotel's account, requiring immediate investigation to understand the reason. Similarly, collecting statistical information during runtime can reveal significant insights, such as a sudden increase in customers rejecting a travel agent's offer, which may indicate the offer is less competitive compared to other businesses. Reporting such events promptly allows business analysts to take swift action. The main goal of this research is to develop a monitoring framework that is agnostic to business logic and the service composition platform. The monitoring engine should operate alongside the SBS and enable easy adaptation of the business process.
The main objective of this study revolves around creating, building, applying, and assessing innovative Machine Learning and Soft Computing methods to address a wide range of computational challenges in various research fields. These domains encompass Remote Sensing, Service-Oriented Architecture, Smart Cities, and Bioinformatics. Within these research domains, the research team has effectively tackled numerous research problems. The primary achievements of this research encompass three notable contributions: "Innovative Dynamic Service Discovery and Adaptation Considering Fuzzy Quality of Service (QoS) Requirements." "A Hybrid Machine Learning Approach for Detecting Changes in Remote Sensing Images." "Utilizing Support Vector Machines (SVM) for the Classification of Obsessive Compulsive Disorder through Oxidative Stress Biomarkers.
The Research "Cyber Physical Systems for Smart Cities" focuses on integrating digital technology into urban infrastructure to enhance city efficiency and sustainability. This research involves developing and implementing interconnected systems that use sensors, data analytics, and automation to optimize transportation, energy management, and public services. The goal is to improve traffic flow, reduce energy consumption, and enable real-time data-driven decision-making for city officials. As the Internet of Things (IoT) continues to advance, these systems become more critical for urban planning and development. Researchers strive to create innovative solutions to address the evolving needs of modern cities.