Zhiqiang Wang | Computer Science and Artificial Intelligence | Best Academic Researcher Award

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Dr. Zhiqiang Wang | Computer Science and Artificial Intelligence | Best Academic Researcher Award

North China University of Science and Technology | China

Dr. Zhiqiang Wang is a dynamic researcher specializing in intelligent control, industrial process optimization, and data-driven modeling, with a particular emphasis on complex mineral processing systems such as copper flotation. His work integrates advanced control theory, artificial intelligence, subspace identification, transfer learning, and machine vision to enhance stability, efficiency, and real-time decision-making within large-scale industrial environments. He has contributed notable innovations in intelligent optimization strategies, expert-knowledge-assisted control frameworks, flotation-foam image analysis for process evaluation, and adaptive control algorithms designed for systems with nonlinear, highly variable operating conditions. His research extends across intelligent manufacturing, big-data-driven industrial analytics, and cross-disciplinary automation technologies, advancing next-generation solutions for process monitoring, fault diagnosis, and operational optimization. He has been actively involved in major national research initiatives focusing on full-process industrial evaluation, intelligent control system development, and 5G-enabled optimization technologies for metallurgy and beneficiation. According to Scopus, Wang has authored 35 indexed publications, accumulated 403 citations from 348 citing documents, and achieved an h-index of 9, reflecting his growing academic influence in industrial automation and intelligent systems engineering. His publications in leading journals including ISA Transactions, IEEE Transactions on Instrumentation and Measurement, Canadian Journal of Chemical Engineering, and the International Journal of Control, Automation and Systems demonstrate his contributions to advancing data-driven modeling, feature engineering, and real-time operational control. Through sustained collaboration, innovative methodologies, and impactful research, Wang continues to advance the field of intelligent industrial process control and smart manufacturing technologies.

Profile: Scopus

Featured Publications

  • Wang, Z., He, D., Wang, Z., & Li, Q. (2025). Subspace identification method-based setpoints tracking control and its applications to the column cleaning process. ISA Transactions.

  • Wang, Z., He, D., Wang, Z., & Li, Q. (2023). Timeliness and stability-based operation optimization for copper flotation industrial process. IEEE Transactions on Instrumentation and Measurement.

  • Wang, Z., Peng, F., Li, Q., & He, D. (2023). State evaluation of copper flotation process based on transfer learning and a layered and blocked framework. Canadian Journal of Chemical Engineering.

  • Wang, Z., Zhang, X., & He, D. (2023). Dynamic global feature extraction and importance-correlation selection for the prediction of concentrate copper grade and recovery rate. Canadian Journal of Chemical Engineering.

  • Wang, Z., He, D., Zhang, Q., & Shi, J. (2020). Observer-based finite-time model reference adaptive state tracking control with actuator saturation. International Journal of Control, Automation and Systems.

Nafiz Fahad | Computer Science | Best Researcher Award

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Mr. Nafiz Fahad | Computer Science | Best Researcher Award

Multimedia University | Malaysia

Mr. Nafiz Fahad is an emerging AI researcher at Multimedia University, Cyberjaya, Malaysia, recognized for his growing contributions to artificial intelligence in healthcare, computer vision, and natural language processing. His research focuses extensively on explainable AI, clinical decision support systems, and data-driven healthcare intelligence. According to Scopus, he has 19 indexed publications, 122 citations, and an h-index of 6, reflecting the influence and visibility of his scholarly work within the global research community. His scientific output spans chronic disease prediction, dementia analytics, lung disease classification, hypertension ontology development, wound-image segmentation, obesity prediction, and precision public health. These studies incorporate techniques such as deep learning, transfer learning, ensemble learning, hybrid architectures, and explainable machine learning to advance diagnostic accuracy and interpretability in medical AI systems. Beyond health-focused research, Fahad has also contributed high-impact work in fake news detection, generative AI, machine learning security, student performance prediction, agricultural disease detection, vision transformers for physics data, and federated learning enhanced with homomorphic encryption. His ongoing research extends to mental health analytics, EEG decoding models, diabetic retinopathy detection, and agentic AI solutions for healthcare innovation. Fahad’s growing academic recognition includes research awards, best paper achievements, and contributions to high-impact journals and conferences. His multidisciplinary scholarship positions him as a promising young researcher advancing applied AI at the intersection of healthcare, societal well-being, and intelligent systems.

Profiles: Scopus | Google Scholar | LinkedIn

Featured Publications

1. Ahmed, Z., Shanto, S. S., Rime, M. H. K., Morol, M. K., Fahad, N., Hossen, M. J., … (2024). The generative AI landscape in education: Mapping the terrain of opportunities, challenges and student perception. IEEE Access.

2. Mahamud, E., Fahad, N., Assaduzzaman, M., Zain, S. M., Goh, K. O. M., & Morol, M. K. (2024). An explainable artificial intelligence model for multiple lung diseases classification from chest X-ray images using fine-tuned transfer learning. Decision Analytics Journal, 12, 100499.

3. Ahmed, R., Fahad, N., Miah, M. S. U., Hossen, M. J., Morol, M. K., Mahmud, M., … (2024). A novel integrated logistic regression model enhanced with recursive feature elimination and explainable artificial intelligence for dementia prediction. Healthcare Analytics, 6, 100362.

4. Fahad, N., Goh, K. M., Hossen, M. I., Shopnil, K. M. S., Mitu, I. J., Alif, M. A. H., & Tee, C. (2023). Stand up against bad intended news: An approach to detect fake news using machine learning. Emerging Science Journal, 7(4), 1247–1259.

5. Hossain, M. N., Fahad, N., Ahmed, R., Sen, A., Al Huda, M. S., & Hossen, M. I. (2024). Preventing student’s mental health problems with the help of data mining. International Journal of Computing, 23(1), 101–108.

Umaeswari P | Computer Science | Best Researcher Award

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Dr. Umaeswari P | Computer Science | Best Researcher Award

R.M.K. Engineering College | India

Dr. P. Umaeswari is an accomplished academician and researcher in the field of Computer Science and Engineering with over 18 years of professional experience. Currently serving as an Associate Professor at R.M.K. Engineering College, Chennai, she has made significant contributions to advanced computing and interdisciplinary research. With a strong academic foundation and a deep commitment to educational excellence, she continuously strives to align academic innovation with societal needs.

Professional profile👤

Google Scholar

ORCID

Scopus

Strengths for the Awards✨

Dr. P. Umaeswari is a distinguished academician and researcher with over 18 years of rich teaching and research experience in Computer Science and Engineering. Her remarkable trajectory across various reputed institutions highlights her dedication to advancing technical education and research excellence.

She has published 30+ impactful international journal papers, including prestigious outlets like Springer, IEEE Xplore, Elsevier, and UGC CARE journals, demonstrating interdisciplinary depth in IoT, Cloud Computing, Machine Learning, Cybersecurity, and Bioinformatics. Her work on biosensors, privacy in wearable IoT devices, smart agriculture, and AI-based security systems shows a strong alignment with current technological challenges and innovations.

In addition to research papers, Dr. Umaeswari has authored six academic books on topics ranging from Artificial Intelligence to Network Security, enhancing curriculum resources and bridging the academic-industry gap. Furthermore, her professional memberships in organizations such as ISTE, Indian Academic Researchers Association, and Knowledge Research Academy reinforce her credibility and active engagement with the research community.

🎓 Education

Dr. Umaeswari holds a Ph.D. in Computer Science and Engineering from St. Peter’s University (2019), preceded by an M.E. in the same field from the same institution (2011). She also earned an M.Phil. in Computer Science (2009) and an M.C.A. in Computer Applications (2006) from Alagappa University. Her academic journey began with a B.Sc. in Computer Science (2000) from Bhaktavatsalam Memorial College for Women under Madras University. Her consistent pursuit of excellence is evident in her academic accolades and grades.

💼 Professional Experience

Dr. Umaeswari’s career spans across various esteemed institutions. She is currently an Associate Professor at R.M.K. Engineering College (2022–present). Her earlier roles include Assistant Professorships at S.A. College of Arts & Science, Mar Gregorios College, and Ponnusamy Nadar College, among others. With 18 years and 3 months of teaching experience, her roles have encompassed teaching, mentoring, and research. Her long-standing service in both engineering and arts and science colleges highlights her interdisciplinary flexibility and dedication.

🔬 Research Interests On Computer Science

Dr. Umaeswari’s research interests encompass Machine Learning, IoT, Cloud Computing, Cybersecurity, Bioinformatics, and Smart Systems. Her work aims at integrating theoretical computing concepts with real-world applications such as biosensors, smart agriculture, and secure cloud frameworks. Her multi-domain approach empowers interdisciplinary collaboration and innovation.

🏆 Awards

Dr. Umaeswari has been honored with numerous accolades including the Research Excellence Award (2024) from SIDVI Foundation, the Inspiring Research Associate Award (2023) from Madras Journal Series Pvt Ltd, and two Best Faculty Awards (2022 & 2023) from prominent academic bodies. These recognitions validate her impact in academia and innovation.

📚 Publications

Dr. Umaeswari has contributed to over 30 international journals and numerous conferences. Her recent impactful works include:

  • Machine Learning Based Predicting the Assisted Living Care Needs
    P. Umaeswari, S.B.G.T. Babu, G.A. Sankaru, G.N.R. Prasad, B.V.S. Thrinath, …
    2022 — 📑 48 citations

  • Development of Programmed Autonomous Electric Heavy Vehicle: An Application of IoT
    P.N. Reddy, P. Umaeswari, L. Natrayan, A. Choudhary
    2023 — 📑 19 citations

  • Statistical Computing and Analysis of Apple Peel Biocarbon and Beta Vulgaris Cellulosic Fiber Vinyl-Based EMI Shielding Composite
    P. Umaeswari, G. Lokesh, A.S.A. Nisha, I.J. Solomon
    2025 — 📑 6 citations

  • IoT-Enabled Energy Conservation in Residential Buildings: Machine Learning Models for Analyzing Annual Solar Power Consumption
    P. Umaeswari, R. Sonia, T.R. Saravanan, N. Poyyamozhi
    2024 — 📑 6 citations

  • Development of Innovative Algorithm for Sound Detection Based on FFT and Goertzel Algorithms
    P. Umaeswari, B.V. Jyothi, G.R.G. King, T. Patil, R. Gukendran
    2024 — 📑 3 citations

  • Internet of Things (IoT) for Remote Earthquake and Fire Detection Monitoring: Linking Safety
    P. Umaeswari, M. Muktasandhu, M. Vignesh, R. Ramyamaranan, …
    2024 — 📑 2 citations

  • Digital Twin-Driven Intrusion Detection for IoT and Cyber-Physical System
    S.K. Ramamoorthy, L. Sindhu, K. Valarmathi, C. Gobinath, P. Umaeswari
    2024 — 📑 1 citation

  • Strategic Management Accounting Practices Between Developed and Emerging Economies Using Machine Learning
    M.S. Almahairah, V.K. Saroha, A. Asokan, P. Umaeswari, J.A. Khan, …
    2022 — 📑 1 citation

  • Local Train Ticketing System Using Web Services
    R. Sheeja, P. Umaeswari, C. Bibin, R. Nishanth, S.H. Chandana
    2022 — 📑 1 citation

  • Multilevel Security System for Big Data Cloud Using SDBS Algorithm
    P. Umaeswari, B. Shanthini, S. Senthil Kumar
    2020 — 📑 1 citation

📝 Conclusion

Dr. P. Umaeswari stands out as a passionate educator, prolific researcher, and visionary thinker. With numerous accolades, interdisciplinary research, impactful publications, and two decades of academic service, she embodies the ideal candidate for a prestigious award. Her scholarly impact and dedication to continuous improvement ensure that she will continue to elevate the fields of Computer Science and Engineering.