Dr . Raghavendra M Devadas - Computer science - Best Researcher Award
GITAM School of Technology | India
Author Profile
Early Academic Pursuits
He embarked on his academic journey with a solid foundation in computer science and engineering. He completed his Bachelor of Engineering (BE) in Information Science and Engineering from B.V. Bhoomaraddi College of Engineering, Hubli, Karnataka, in 2005. Building upon this, he pursued his Master of Technology (MTech) in Computer Science and Engineering from Bapuji College of Engineering, Davangere, Karnataka, graduating in 2012. His academic pursuits culminated in a Ph.D. in Computer Science from Visvesvaraya Technological University, Belagavi, Karnataka, with a research focus on "An Adaptive Requirements Prioritization Technique for Large Scale Software Projects," completing his doctoral journey in July 2023.
Professional Endeavors
he has a rich tapestry of professional experiences, honing his expertise and contributing significantly to academia. He commenced his career as a Lecturer at SKSVMACET, Laxmeshwar, and subsequently served as a Lecturer at PESITM, Shimoga. His journey then led him to Tata Consultancy Services, Chennai, where he worked as a Software Consultant (Mainframes Platform). He transitioned back to academia and served as a Senior Assistant Professor at MITE, Moodabidri, before joining the Computer Science department at School of Engineering, Presidency University, Bengaluru, as an Assistant Professor. Currently, he holds the position of Assistant Professor in the Computer Science & Engineering department at GITAM School of Technology, GITAM University, Bengaluru.
Contributions and Research Focus in Computer science
His research interests span various domains within computer science, with a primary focus on artificial intelligence, machine learning, and software engineering. His doctoral research on adaptive requirements prioritization techniques underscores his commitment to addressing real-world challenges in large-scale software projects. Additionally, he has made significant contributions to areas such as stochastic calculus-guided reinforcement learning, Bayesian neural networks, and fuzzy logic-based approaches in software engineering. His research output includes publications in esteemed journals and conferences, showcasing his dedication to advancing knowledge in his field.
Accolades and Recognition
His contributions to academia have garnered recognition and accolades. He has been acknowledged with patents for innovative inventions, including a "Driver Drowsiness Detecting Device based on AI" and a "Smart Bottle for Monitoring Employee Efficiency." Furthermore, he has received grants for his research endeavors and has been honored with awards such as the "Best Research Poster Competition" at the International Conference of Industrial Engineering and Operations Management in Dubai. His editorial roles in esteemed publications and his role as a peer reviewer for reputed journals reflect his standing in the academic community.
Impact and Influence
His impact extends beyond his research contributions to his role as an educator and mentor. His experience in teaching diverse groups of students and his ability to handle challenging situations have shaped the educational journeys of numerous individuals. Through his guidance and mentorship, he has empowered students to realize their full potential and excel in their academic pursuits. His lectures, seminars, and sessions on cutting-edge topics like big data analytics have equipped students with the knowledge and skills needed for success in the 21st century.
Legacy and Future Contributions
He continues his academic journey, his legacy is marked by his dedication to excellence in research, teaching, and mentorship. His ongoing projects, including edited books on sustainable agriculture applications and transformative education, underscore his commitment to advancing knowledge and fostering innovation. Through his continued research endeavors, impactful publications, and academic leadership roles, he aims to contribute meaningfully to the field of computer science and inspire the next generation of researchers and educators.
Citations
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- Interdependency Aware Qubit and Brownboost Rank Requirement Learning for Large Scale Software Requirement Prioritization
- PUGH Decision Trapezoidal Fuzzy and Gradient Reinforce Deep Learning for Large Scale Requirement Prioritization
- Multi aspects based requirements prioritization for large scale software using deep neural lagrange multiplier
- CARDIAC ARRHYTHMIA CLASSIFICATION USING SVM, KNN AND NAIVE BAYES ALGORITHMS
- Identifying Factors in Congenital Heart Disease Transition using Fuzzy DEMATEL