Jay Kachhadia | Data Science | Data Science Award

Published on by Technology Scientists

Mr. Jay Kachhadia | Data Science | Data Science Award

Syracuse University | United States

Mr. Jay Kachhadia is a data science professional whose research lies at the intersection of machine learning, natural language processing (NLP), and computational social science. His scholarly work focuses on applying advanced deep learning models—particularly transformer-based architectures such as BERT—to analyze and classify political and social media discourse. He has authored one peer-reviewed conference publication, PoliBERT: Classifying Political Social Media Messages with BERT (SBP-BRIMS 2020), which has received 33 citations, reflecting sustained academic relevance and impact within the field. With an h-index of 1 and an i10-index of 1, his work demonstrates focused contributions with measurable scholarly influence. The publication resulted from interdisciplinary collaboration with researchers in social and behavioral modeling, highlighting his ability to bridge data science with social science research. Beyond academia, his research has broader societal impact by enabling scalable, data-driven analysis of political communication, misinformation, and public opinion, contributing to more informed policy analysis and civic discourse at a global level.

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Featured Publication

Muhammad Firoz Mridha | Machine Learning | Best Researcher Award

Published on by Technology Scientists

Prof. Dr. Muhammad Firoz Mridha | Machine Learning | Best Researcher Award

Professor | American International University | Bangladesh

Prof. Dr. Muhammad Firoz Mridha, a researcher at the American International University–Bangladesh (AIUB), has established a strong scholarly profile in computer science with notable contributions to machine learning, data analytics, cybersecurity, IoT, and applied artificial intelligence. With 319 publications, over 4,629 citations, and an h-index of 33, his work demonstrates sustained academic productivity and global research impact. His studies often address practical and emerging challenges—such as intelligent decision-support systems, secure digital infrastructures, and data-driven solutions for healthcare and smart environments—positioning his contributions at the intersection of theoretical advancement and real-world application. Collaboration is a defining feature of his career, reflected in partnerships with 575 co-authors, enabling multidisciplinary knowledge exchange and strengthening international research networks. His work has supported technological development, digital inclusion, and innovation-oriented problem-solving, particularly in contexts where data-centric technologies can improve societal outcomes.

Profiles: Scopus | ORCID | Google Scholar

Featured Publications

1. Mridha, M. F., Keya, A. J., Hamid, M. A., Monowar, M. M., & Rahman, M. S. (2021). A comprehensive review on fake news detection with deep learning. IEEE Access, 9, 156151–156170.

Cited by: 297

2. Mridha, M. F., Das, S. C., Kabir, M. M., Lima, A. A., Islam, M. R., & Watanobe, Y. (2021). Brain–computer interface: Advancement and challenges. Sensors, 21(17), 5746.

Cited by: 296

3. Jim, J. R., Talukder, M. A. R., Malakar, P., Kabir, M. M., Nur, K., & Mridha, M. F. (2024). Recent advancements and challenges of NLP-based sentiment analysis: A state-of-the-art review. Natural Language Processing Journal, 6, 100059.

Cited by: 271

4. Rayed, M. E., Islam, S. M. S., Niha, S. I., Jim, J. R., Kabir, M. M., & Mridha, M. F. (2024). Deep learning for medical image segmentation: State-of-the-art advancements and challenges. Informatics in Medicine Unlocked, 47, 101504.

Cited by: 227

5. Mridha, M. F., Lima, A. A., Nur, K., Das, S. C., Hasan, M., & Kabir, M. M. (2021). A survey of automatic text summarization: Progress, process and challenges. IEEE Access, 9, 156043–156070.

Cited by: 197

Prof. Dr. Muhammad Firoz Mridha’s research advances data-driven intelligence and secure digital systems, contributing to global technological innovation and societal problem-solving. His work supports scalable, real-world applications—particularly in developing regions—promoting inclusive, ethical, and sustainable digital transformation.