Madanjit Singh | Education Technology | Best Paper Award

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Dr. Madanjit Singh | Education Technology | Best Paper Award

Assistant Professor at Guru Nanak Dev University, India.

Dr. Madanjit Singh is a dedicated academician and researcher specializing in Educational Technology and Computer Science. With extensive teaching experience at Guru Nanak Dev University, he has mentored students in programming and software development, fostering innovation in learning approaches. His commitment to education is reflected in his research on optimizing digital learning platforms. Dr. Singh’s technical expertise spans multiple programming languages, databases, and operating systems, making significant contributions to academia and practical applications in computer science education.

Publication Profile

Scopus

Google scholar

Educational Details

Dr. Madanjit Singh is currently pursuing a Ph.D. in Educational Technology at Guru Nanak Dev University, Amritsar. He holds a Master of Computer Applications (MCA) from Guru Nanak Dev University Regional Campus, Gurdaspur, where he achieved a CGPA of 9.46. He completed his Bachelor of Computer Applications (BCA) with 83.90% from Swami Satyanand College of Management and Technology, Amritsar. His early education includes Senior Secondary (Non-Medical Stream) from Khalsa Senior Secondary School, Amritsar, under the Punjab School Education Board, and Matriculation from DD High School, Amritsar. Additionally, he underwent six months of industrial training in J2SE & J2EE at VMM Education, Amritsar, where he worked on projects related to Ciphered Mail. He has also qualified for UGC NET (November 2017) and GATE (2018).

Professional Experience

Dr. Singh has been actively involved in academia, working as an Assistant Professor at Guru Nanak Dev University (GNDU) Main Campus, Amritsar. He has been associated with GNDU since 2015, initially in a full-time capacity and later as a part-time faculty member across multiple academic sessions. His responsibilities have included delivering lectures, assisting students with project-based learning in programming languages such as Java, PHP, .NET, and VB.NET, and guiding students in website and application development. Additionally, he has played a crucial role in administrative tasks, student evaluations, and implementing innovative teaching methodologies to enhance learning experiences.

Research Interest

Dr. Singh’s research focuses on Educational Technology, with an emphasis on data structures, algorithm design, and operating systems. His work explores the integration of technology in education, aiming to enhance learning methodologies through digital platforms and programming innovations. His expertise in various programming languages and database systems contributes to his research on optimizing educational tools and interactive learning systems.

Author Metrics & Impact

Dr. Singh’s research contributions are reflected in his academic pursuits and teaching methodologies. While specific publication details are not provided, his work in Educational Technology and Computer Science is anticipated to impact the field through ongoing research and teaching innovations. His engagement in guiding students in software projects and programming advancements underscores his influence in the academic community.

Top Noted Publication

  • Sustainable Development Goal for Quality Education (SDG 4): A study on SDG 4 to extract the pattern of association among the indicators of SDG 4 employing a genetic algorithm

    • Authors: M. Saini, E. Sengupta, M. Singh, H. Singh, J. Singh
    • Journal: Education and Information Technologies, Vol. 28 (2), pp. 2031-2069 (2023)
    • Citations: 138
    • Summary: This study investigates the relationships among the indicators of SDG 4 (Quality Education) using a genetic algorithm. The research provides insights into how various factors influence education quality and suggests data-driven strategies for improving global education policies.

  • Indian government E-learning initiatives in response to COVID-19 crisis: A case study on online learning in Indian higher education system

    • Authors: M. Singh, S.O. Adebayo, M. Saini, J. Singh
    • Journal: Education and Information Technologies, Vol. 26 (6), pp. 7569-7607 (2021)
    • Citations: 124
    • Summary: This paper examines India’s e-learning initiatives launched in response to the COVID-19 pandemic. It assesses the effectiveness of online learning platforms in higher education and explores the challenges faced by students and educators in adapting to digital education.

  • Analysing the tweets to examine the behavioural response of Indian citizens over the approval of national education policy 2020

    • Authors: M. Saini, M. Singh, M. Kaur, M. Kaur
    • Journal: International Journal of Educational Development, Vol. 82, Article 102356 (2021)
    • Citations: 23
    • Summary: This study employs sentiment analysis on Twitter data to evaluate public reactions to India’s National Education Policy (NEP) 2020. The findings highlight key themes in public discourse, including concerns, support, and criticisms of the policy.

  • A Facial and Vocal Expression Based Comprehensive Framework for Real-Time Student Stress Monitoring in an IoT-Fog-Cloud Environment

    • Authors: M. Singh, S. Bharti, H. Kaur, V. Arora, M. Saini, M. Kaur, J. Singh
    • Journal: IEEE Access, Vol. 10, pp. 63177-63188 (2022)
    • Citations: 19
    • Summary: This paper introduces a novel IoT-fog-cloud-based framework that uses facial and vocal expressions to monitor student stress levels in real time. The study explores how AI-driven systems can enhance student well-being in educational environments.

  • Artificial intelligence inspired multilanguage framework for note-taking and qualitative content-based analysis of lectures

    • Authors: M. Saini, V. Arora, M. Singh, J. Singh, S.O. Adebayo
    • Journal: Education and Information Technologies, Vol. 28 (1), pp. 1141-1163
    • Summary: This research proposes an AI-powered framework that facilitates multilingual note-taking and qualitative content analysis for lectures. The system aims to improve accessibility and comprehension for students in diverse educational settings.

Conclusion

Dr. Madanjit Singh is a highly suitable candidate for a Best Researcher Award in Educational Technology. His research contributions, strong citation record, AI-driven innovations, and dedication to digital education position him as a leading academic in the field. Strengthening global collaborations and industry partnerships could further enhance his eligibility for prestigious international research awards.

 

Swati Jitendrakmar Patel | Artificial Intelligence | Best Researcher Award

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Ms. Swati Jitendrakmar Patel | Artificial Intelligence | Best Researcher Award

Software Engineer at Skyline Software Solutions, India

Ms. Swati Patel is an accomplished Data Analyst and Software Developer with extensive expertise in data science, machine learning, and software engineering. She has contributed significantly to academic research, publishing 8 journal papers, 2 IEEE conference papers, and 5 books on topics ranging from software security to predictive analytics. With strong analytical skills and a track record of developing efficient workflows and impactful applications, she has consistently delivered data-driven solutions for business optimization and research innovation.

Publication Profile

Google Scholar

Educational Details

Ms. Swati Patel holds a Master of Science in Advanced Computing Technologies from Birkbeck, University of London (2022-2023), where her projects included Principal Component Analysis on the Pima Indians Diabetes Dataset and predicting DDoS attacks using Darknet Time-Series data. She earned a Master’s degree in Computer Science from SES’s R. C. Patel Institute of Technology (NMU, India, 2012-2014), completing her thesis on software birthmark-based theft detection of JavaScript programs. Her Bachelor’s degree in Computer Engineering was completed at PSGVPM’s D. N. Patel College of Engineering, Shahada (NMU, India, 2008-2012), where she developed an Online Voting System using ASP.NET and SQL.

Professional Experience

Swati Patel is a Data Analyst and Entrepreneur with proven expertise in designing and optimizing workflows, data visualization, and software development. She served as a Data Analyst at SSP Group PLC, UK (2023-2024), where she created interactive Power BI dashboards to analyze sales data, optimized EPOS systems for data accuracy, and reduced data processing time by 30% through SQL optimization. As an entrepreneur, she successfully led Skyline Software Solutions (2014-2022), developing over 35 applications in Java, .NET, and other technologies. She managed end-to-end project execution, providing high-quality software solutions to diverse industries.

Research Interest

Swati’s research focuses on applied machine learning, natural language processing, and predictive modeling. She is particularly interested in statistical methods for data anomaly detection, speech-based health diagnostics, and secure systems in computing environments. Her work also extends to innovative clustering techniques for theft detection in software and dimensionality reduction in large datasets.

Author Metrics

  • Publications: 2 IEEE papers, 8 journal papers, 5 books.
  • Key Topics: Data science, machine learning, NLP, secure computing systems, predictive analytics.
  • Notable Works:
    • “A Review on Statistical Analysis-Based Approaches for Data Poison Detection Using Machine Learning.”
    • “Automated Depression Assessment from Speech Signals Using Pitch and Energy Features.”
    • “Long Short-Term Memory and Gated Recurrent Unit Networks for Accurate Stock Price Prediction.”
    • Books: COVID-19 Data Analysis for the United Kingdom and Data Exploration and Machine Learning using R.

Publication Top Notes

  • Software Birthmark Based Theft Detection of JavaScript Programs Using Agglomerative Clustering and Frequent Subgraph Mining
    • Authors: S.J. Patel, T.M. Pattewar
    • Conference: 2014 International Conference on Embedded Systems (ICES)
    • Pages: 63–68
    • Citations: 9
    • Year: 2014
    • Summary: This paper presents a novel method for detecting software theft in JavaScript programs using software birthmarks. The approach employs agglomerative clustering and frequent subgraph mining to identify similarities between programs, aiding in theft detection.
  • K-Means Clustering Algorithm: Implementation and Critical Analysis
    • Author: S. Patel
    • Publisher: Scholars’ Press
    • Citations: 8
    • Year: 2019
    • Summary: This publication provides an in-depth exploration of the K-means clustering algorithm, including its implementation and a critical analysis of its efficiency and limitations in clustering diverse datasets.
  • Software Birthmark Based Theft Detection of JavaScript Programs Using Agglomerative Clustering and Improved Frequent Subgraph Mining
    • Authors: S. Patel, T. Pattewar
    • Conference: 2014 International Conference on Advances in Electronics, Computers, and Communications
    • Citations: 7
    • Year: 2014
    • Summary: This paper builds upon earlier research by introducing an improved method for frequent subgraph mining, enhancing the detection accuracy of JavaScript program theft through advanced birthmark-based techniques.
  • Software Birthmark for Theft Detection of JavaScript Programs: A Survey
    • Authors: S.J. Patel, T.M. Pattewar
    • Journal: IJAFRC (International Journal of Advanced Foundation and Research in Computers)
    • Volume: 1, Issue 2, Pages: 29–38
    • Citations: 2
    • Year: 2014
    • Summary: This survey reviews existing methods for detecting software theft in JavaScript programs, with a focus on software birthmark techniques. It outlines challenges, solutions, and future research directions.
  • Emerging Trends in Computer Technology (NCETCT)
    • Authors: S.J. Patel, T.M. Pattewar
    • Journal: IJCA (International Journal of Computer Applications)
    • Conference Issue: NCETCT, Number 1
    • Year: 2014
    • Summary: This conference paper discusses advancements in computer technology with a focus on software security. It explores the use of software birthmarks as a means of detecting and preventing intellectual property theft in programming.

Conclusion

Ms. Swati Patel is a highly qualified and deserving candidate for the Best Researcher Award. Her combination of academic excellence, impactful research, and real-world contributions to artificial intelligence and software engineering set her apart as an innovative thinker. To maximize her potential and visibility, she could focus on strengthening her citation impact, pursuing international collaborations, and contributing to higher-impact conferences. Overall, her track record reflects dedication, skill, and the ability to drive meaningful advancements in her field.