Narayan Vyas | Artificial Intelligence | Young Scientist Award

Mr Narayan Vyas | Artificial Intelligence | Young Scientist Award

Mr Narayan Vyas , Vivekananda Global University, India

Dr. Narayan Vyas is an Assistant Professor at Vivekananda Global University, Jaipur, specializing in Internet of Things (IoT) and application development. With a Ph.D. in Computer Science and multiple publications in peer-reviewed journals, he is recognized for his significant contributions to IoT, machine learning, and remote sensing. Dr. Vyas has a proven track record in academia and industry, including roles as a Technical Trainer and Research Consultant. His research includes developing frameworks for agricultural changes and innovations in mobile app development. He is also an active keynote speaker and workshop organizer, dedicated to advancing technological education.

Publication Profile

Orcid

Strengths for the Award

  1. Extensive Research Contributions: Narayan has a robust research profile with numerous publications in peer-reviewed international journals and conferences. His work spans diverse and cutting-edge fields, including IoT, remote sensing, machine learning, and computer vision. This breadth and depth of research indicate a high level of expertise and a significant contribution to the field.
  2. Active Engagement in Academia: As an Assistant Professor and Research Coordinator, Narayan plays a key role in shaping academic programs and mentoring students. His leadership in developing syllabi and organizing workshops demonstrates a commitment to advancing both education and research.
  3. Industry Experience and Practical Impact: His practical experience in mobile application development and work with clients worldwide show his ability to bridge the gap between academic research and real-world applications. This experience is valuable for translating theoretical research into practical solutions.
  4. Editorial and Consultancy Roles: Editing several books and working as a research consultant highlight his expertise and recognition in the field. These roles suggest a high level of respect and credibility among peers.
  5. National Recognition: Passing the NTA UGC NET & JRF on his first attempt underscores his strong foundational knowledge and commitment to research excellence.

Areas for Improvement

  1. Research Continuity and Focus: While Narayan’s work is extensive, he could benefit from focusing more deeply on a narrower set of research areas. This could lead to more impactful and cohesive contributions in specific domains.
  2. Increased Research Collaboration: Although Narayan has collaborated with others, increasing his participation in interdisciplinary research projects could further enhance his impact and visibility in diverse fields.
  3. Awards and Grants: While Narayan has significant achievements, actively seeking and obtaining prestigious awards and grants could bolster his profile and provide additional validation of his research impact.
  4. Public Engagement: Enhancing efforts to communicate research findings to a broader audience, including the general public, could improve the societal impact of his work.

Education

Dr. Narayan Vyas is pursuing a Ph.D. in Computer Science at Punjabi University, Patiala, focusing on developing an image fusion framework for agricultural detection using remote sensing data. He cleared the NTA UGC NET & JRF in Computer Science on his first attempt. Dr. Vyas holds a Masterā€™s in Computer Application from Maharshi Dayanand Saraswati University, where he achieved the first rank. He completed his Bachelor’s in Computer Applications with a specialization in IoT, where he developed a self-balancing robot as his major project.

Experience

Dr. Narayan Vyas currently serves as an Assistant Professor and Research Coordinator at Vivekananda Global University, Jaipur. Previously, he was a Technical Trainer at Chandigarh University, where he founded the Student Research Cell. His role as Principal Research Consultant at AVN Innovations Pvt. Ltd. involved leading research projects and mentoring junior researchers. As a Senior Mobile App Developer at Flexxited, he developed applications for clients globally. His experience spans from academic roles to hands-on technical work, including freelance and training positions.

Awards and Honors

Dr. Narayan Vyas has been recognized for his contributions to technology and research. He served as a Session Chair at the 1st International Conference on Artificial Intelligence for Innovations in Healthcare Industries (ICAIIHI-2023). He has reviewed papers for prestigious conferences such as IEEE NMITCON-2023 and ICDSNS-2023. He was a proctor for the IEEEXtreme 17.0 programming competition and conducted notable workshops on mobile app development and IoT at leading universities.

Research Focus

Dr. Narayan Vyasā€™s research focuses on integrating advanced technologies like IoT, machine learning, and remote sensing to solve complex problems in agriculture, healthcare, and environmental monitoring. His work includes developing frameworks for detecting agricultural changes, improving mobile app development methodologies, and enhancing remote sensing data analysis. He is passionate about applying these technologies to real-world problems and advancing the academic understanding of their applications.

Publication Top Notes

“Applying Machine Learning Techniques to Bioinformatics” šŸ“š

“Innovations in Machine Learning and IoT for Water Management” šŸ’§

“Quantum Innovations at the Nexus of Biomedical Intelligence” šŸ§¬

“AI-Driven Alzheimerā€™s Disease Detection and Prediction” šŸ§ 

“Secure Energy Optimization: Leveraging IoT and AI for Enhanced Efficiency” āš”

“Internet of Medicine for Smart Healthcare” šŸ„

“Multimodal Data Fusion for Bioinformatics” šŸŒ

“Elevating IoT Sensor Data Management and Security Through Blockchain Solutions” šŸ”’

“A Machine Learning Framework for Accurate Prediction of Parkinson’s Disease from Speech Data” šŸ—£ļø

“Advancing Precision Agriculture: Leveraging YOLOv8 for Robust Deep Learning Enabled Crop Diseases Detection” šŸŒ¾

Conclusion

Narayan Vyas is a compelling candidate for the Research for Young Scientist Award due to his significant contributions to research, his active role in academia, and his practical experience. His extensive publication record and leadership in academia reflect a high level of expertise and dedication. Addressing the areas for improvement, such as focusing research efforts and seeking additional recognition, could further strengthen his candidacy. Overall, his achievements and ongoing contributions make him a strong contender for this award.

 

 

Parijata Majumdar | Artificial Intelligence | Women Researcher Award

Dr. Parijata Majumdar | Artificial Intelligence | Women Researcher Award

Dr at Techno College of Engineering Agartala India

Dr. Parijata Majumdar is an accomplished academic and researcher in Computer Science and Engineering, currently serving as Associate Professor at Techno College of Engineering Agartala (TCEA). She holds a Ph.D. from NIT Agartala, specializing in AI for Precision Agriculture. With expertise in Machine Learning, Optimization Techniques, and IoT, her research focuses on applications in Precision Agriculture, Image Processing, and Blockchain. Dr. Majumdar has authored numerous SCI and SCOPUS indexed publications, holds multiple patents, and has received several awards and recognitions for her contributions to research and development. She actively participates as a reviewer and speaker in international conferences and journals.

profile:

Scopus

Scholar

 

šŸŽ“ Educational Qualification Details:

Madhyamik (Secondary Education): Board: Tripura Board of Secondary Education Year: 2010 Percentage: 70.29% Division: First Class. Diploma in Computer Science: Institution: Womenā€™s Polytechnic, Hapania Affiliated: Tripura University Year: 2013 CGPA: 8.27 (A Grade). B.E. in Computer Science and Engineering: Institution: TIT, Narsingarh Affiliated: Tripura University Year: 2016 CGPA: 7.92 (B Grade). M.Tech. in Computer Science and Engineering: Institution: Tripura University Year: 2018 CGPA: 8.97 (Gold Medalist). Ph.D. in Computer Science and Engineering: Institution: NIT Agartala Year: 2023 (October) Thesis: “Design and Development of AI Approaches for Precision Agriculture Applications” Supervisor: Dr. Diptendu Bhattacharya, Associate Professor, NIT Agartala

šŸ“š MOOCs/SWAYAM/FDP/Online Courses:

Computational Intelligence (AICTE Training And Learning, NIT Agartala), Joy of Computing using Python (NPTEL, IIT Madras), Internet of Things and Sensor Networks (TEQIP-III, Tripura Institute of Technology), Recent Trends and Research Opportunities in Engineering and Technology (TCEA), Contrast Enhancement in Poor Visibility (Global Initiative of Academic Networks, Tripura University), Image and Video Forensics (Global Initiative of Academic Networks, Tripura University), Entrepreneurship Skills Development Using Open Access Resources (TEQIP-II, Tripura Institute of Technology), Security aspects of IoT based Eco System (AICTE Training And Learning, ATAL Academy)

šŸ‘©ā€šŸ« Working Experience Profile:

Assistant Professor (Regular): Techno College of Engineering Agartala (TCEA) since February 2018., Associate Professor: Techno College of Engineering Agartala (TCEA) since November 2023.

Publication:šŸ“

  • Title: IoT for promoting agriculture 4.0: a review from the perspective of weather monitoring, yield prediction, security of WSN protocols, and hardware cost analysis
    Authors: P. Majumdar, S. Mitra, D. Bhattacharya
    Journal: Journal of Biosystems Engineering
    Year: 2021
    Volume: 46
    Issue: 4
    Pages: 440-461
    Citations: 21

 

  • Title: Application of green IoT in agriculture 4.0 and beyond: Requirements, challenges and research trends in the era of 5G, LPWANs and Internet of UAV Things
    Authors: P. Majumdar, D. Bhattacharya, S. Mitra, B. Bhushan
    Journal: Wireless Personal Communications
    Year: 2023
    Volume: 131
    Issue: 3
    Pages: 1767-1816
    Citations: 13

 

  • Title: IoT and machine learningā€based approaches for real-time environment parameters monitoring in agriculture: an empirical review
    Authors: P. Majumdar, S. Mitra
    Book Chapter: Agricultural Informatics: Automation Using the IoT and Machine Learning
    Year: 2021
    Pages: 89-115
    Citations: 9

 

  • Title: Detection of Inflammation from temperature profile using Arthritis knee joint Datasets
    Authors: P. Majumdar, K. Das, N. Nath, M.K. Bhowmik
    Conference: 2018 IEEE International Conference on Healthcare Informatics (ICHI)
    Year: 2018
    Pages: 409-411
    Citations: 7

 

  • Title: Prediction of evapotranspiration and soil moisture in different rice growth stages through improved salp swarm based feature optimization and ensembled machine learning algorithm
    Authors: P. Majumdar, D. Bhattacharya, S. Mitra
    Journal: Theoretical and Applied Climatology
    Year: 2023
    Volume: 153
    Issue: 1
    Pages: 649-673
    Citations: 4

 

  • Title: Demand prediction of rice growth stage-wise irrigation water requirement and fertilizer using Bayesian genetic algorithm and random forest for yield enhancement
    Authors: P. Majumdar, D. Bhattacharya, S. Mitra, R. Solgi, D. Oliva, B. Bhusan
    Journal: Paddy and Water Environment
    Year: 2023
    Volume: 21
    Issue: 2
    Pages: 275-293
    Citations: 4

 

  • Title: Honey badger algorithm using lens opposition based learning and local search algorithm
    Authors: P. Majumdar, S. Mitra, D. Bhattacharya
    Journal: Evolving Systems
    Year: 2024
    Volume: 15
    Issue: 2
    Pages: 335-360
    Citations: 2

 

Alireza Nazemi | Neural network | Best Researcher Award

Prof. Alireza Nazemi | Neural network | Best Researcher Award

Prof at Shahrood University of Technology, Iran

Dr. Alireza Nazemi is a Professor of Applied Mathematics at Shahrood University of Technology, specializing in control and optimization. He holds a Ph.D. in Applied Mathematics from Ferdowsi University of Mashhad. His research interests include optimal control, nonlinear and convex optimization, portfolio optimization, and neural network theory. Dr. Nazemi has published extensively, with recent works addressing neural network applications in optimization and control. He teaches courses such as Optimal Control, Nonlinear Optimization, and Neural Networks & Optimization. Dr. Nazemi is dedicated to advancing mathematical methods to solve complex engineering and financial problems.

profile:

Scopus

Scholar

 

šŸŽ“ Education

B. Sc. in Applied Mathematics Sharif University of Technology, Tehran, Iran (1997-2001). M. Sc. in Applied Mathematics (Field: Control & Optimization)Ā  Hakim Sabzevari University, Sabzevar, Iran (2001-2003). Dissertation: ā€œTo solve some nonlinear programming problems by using measure theory and neural network modelsā€ Supervisor: Prof. Sohrab Effati. Ph.D. in Applied Mathematics (Field: Control & Optimization)Ā  Ferdowsi University of Mashhad, Mashhad, Iran (2005-2009). Dissertation: ā€œTo solve some optimal shape design problems with free boundaryā€ Supervisor: Prof. Mohammad Hadi Farahi Advisor: Prof. Ali Vahidian Kamyad

šŸ” Research Interests

  • Optimal Control
  • Nonlinear Optimization
  • Convex Optimization
  • Portfolio Optimization
  • Optimization of PDEā€™s
  • Neural Network Theory

Publication:šŸ“

  • Title: Neural network models and its application for solving linear and quadratic programming problems
    Authors: S. Effati, A.R. Nazemi
    Journal: Applied Mathematics and Computation
    Year: 2006
    Volume: 172
    Issue: 1
    Pages: 305-331
    Citations: 84

 

  • Title: A dynamic system model for solving convex nonlinear optimization problems
    Author: A.R. Nazemi
    Journal: Communications in Nonlinear Science and Numerical Simulation
    Year: 2012
    Volume: 17
    Issue: 4
    Pages: 1696-1705
    Citations: 73

 

  • Title: A gradient-based neural network method for solving strictly convex quadratic programming problems
    Authors: A. Nazemi, M. Nazemi
    Journal: Cognitive Computation
    Year: 2014
    Volume: 6
    Pages: 484-495
    Citations: 72

 

  • Title: Analytical solution for the Fokkerā€“Planck equation by differential transform method
    Authors: S. Hesam, A.R. Nazemi, A. Haghbin
    Journal: Scientia Iranica
    Year: 2012
    Volume: 19
    Issue: 4
    Pages: 1140-1145
    Citations: 62

 

  • Title: MĆ¼ntzā€“Legendre spectral collocation method for solving delay fractional optimal control problems
    Authors: S. Hosseinpour, A. Nazemi, E. Tohidi
    Journal: Journal of Computational and Applied Mathematics
    Year: 2019
    Volume: 351
    Pages: 344-363
    Citations: 59

 

  • Title: A neural network model for solving convex quadratic programming problems with some applications
    Author: A. Nazemi
    Journal: Engineering Applications of Artificial Intelligence
    Year: 2014
    Volume: 32
    Pages: 54-62
    Citations: 59

 

  • Title: An efficient dynamic model for solving the shortest path problem
    Authors: A. Nazemi, F. Omidi
    Journal: Transportation Research Part C: Emerging Technologies
    Year: 2013
    Volume: 26
    Pages: 1-19
    Citations: 59

 

  • Title: Application of projection neural network in solving convex programming problems
    Authors: S. Effati, A. Ghomashi, A.R. Nazemi
    Journal: Applied Mathematics and Computation
    Year: 2007
    Volume: 188
    Issue: 2
    Pages: 1103-1114
    Citations: 52

 

  • Title: A dynamical model for solving degenerate quadratic minimax problems with constraints
    Author: A.R. Nazemi
    Journal: Journal of Computational and Applied Mathematics
    Year: 2011
    Volume: 236
    Issue: 6
    Pages: 1282-1295
    Citations: 49

 

  • Title: Solving general convex nonlinear optimization problems by an efficient neurodynamic model
    Author: A. Nazemi
    Journal: Engineering Applications of Artificial Intelligence
    Year: 2013
    Volume: 26
    Issue: 2
    Pages: 685-696
    Citations: 45

 

  • Title: A capable neural network model for solving the maximum flow problem
    Authors: A. Nazemi, F. Omidi
    Journal: Journal of Computational and Applied Mathematics
    Year: 2012
    Volume: 236
    Issue: 14
    Pages: 3498-3513
    Citations: 44