Parijata Majumdar | Artificial Intelligence | Women Researcher Award

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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

 

Tahir Cetin Akinci | Artificial Intelligence | Best Researcher Award

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Dr. Tahir Cetin Akinci | Artificial Intelligence | Best Researcher Award

šŸ‘Øā€šŸ«Profile Summary

Dr. Tahir Cetin Akinci, an accomplished scholar, holds a Bachelor’s in Electrical Engineering from Klaipeda, Lithuania, and earned his Master’s and Ph.D. in 2005 and 2010. As a Research Assistant at Marmara University and later at Istanbul Technical University, he demonstrated a commitment to electrical engineering research. Engaging globally, Dr. Akinci enriched his expertise as a visiting scholar at the University of California Riverside. His diverse research interests span electric energy systems, AI, and data analysis. Awarded the International Young Scientist Excellence and Best Researcher Awards in 2022, Dr. Akinci is recognized for impactful contributions to cutting-edge technologies.

šŸŒ Professional Profiles

 

šŸŽ“ Education:

Tahir Cetin Akinci embarked on his academic journey with a Bachelor’s degree in Electrical Engineering from Klaipeda, Lithuania, in 2000. This foundation paved the way for his pursuit of knowledge, leading to the successful completion of his Master’s and Ph.D. degrees in 2005 and 2010, respectively.

šŸ‘Øā€šŸ”¬ Research Positions:

From 2003 to 2010, Dr. Akinci dedicated his expertise as a Research Assistant in the Electrical Engineering Department at Marmara University in Istanbul, Turkey. Building on this experience, he continued his academic journey at Istanbul Technical University (ITU), where he further enriched his research portfolio.

šŸŒ Global Academic Engagement:

Dr. Akinci’s quest for knowledge and global perspective led him to assume the role of a visiting scholar at the University of California Riverside (UCR). This international exposure added a diverse dimension to his academic and research endeavors.

šŸ§  Diverse Research Interests:

Dr. Akinci’s research spans a wide spectrum of cutting-edge domains, including electric energy systems, renewable energy, artificial neural networks, deep learning, machine learning, cognitive systems, signal processing, and data analysis. His multidisciplinary approach reflects a keen interest in leveraging advanced technologies for innovative solutions.

šŸ† Recognition and Awards:

In 2022, Dr. Akinci’s impactful contributions to research were celebrated with the International Young Scientist Excellence Award and the Best Researcher Award. These accolades signify not only his dedication to advancing knowledge but also the significant impact of his work on the global stage.

šŸ’” Research Experience:

With a profound focus on Artificial Intelligence, Machine Learning, Cyber Security, and Data Analytics, Dr. Akinci’s research journey epitomizes a commitment to exploring cutting-edge technologies that reshape our understanding of various scientific and technological domains.

šŸ“šTop Noted Publication

  1. Automatic detection of brain tumors with the aid of ensemble deep learning architectures and class activation map indicators by employing magnetic resonance images
    • Published in 2022 Cited by 12

 

  1. Short-term wind speed forecasting system using deep learning for wind turbine applications
    • Published in 2020, Cited by 14

 

  1. Determination of optimum operation cases in electric arc welding machine using neural network
    • Published in 2011 Cited by 16

 

  1. Creating large language model applications utilizing langchain: A primer on developing llm apps fast
    • Published in 2023 Cited by 16

 

  1. Application of decision tree methods for wind speed estimation
    • Published in 2019 Cited by 17

 

 

 

  • Ā  Ā  Ā  Ā  Ā  Ā  Ā  Ā  Ā  Ā  Ā Published in 2020 Cited by 32