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.

Yinfeng Yang | Computer Science and Artificial Intelligence | Best Researcher Award

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Assist. Prof. Dr. Yinfeng Yang | Computer Science and Artificial Intelligence | Best Researcher Award

Anhui University of Chinese Medicine | China

Dr. Yinfeng Yang is a distinguished researcher specializing in artificial intelligence, bioinformatics, and traditional Chinese medicine (TCM), with a strong emphasis on AI-enabled drug discovery and biomedical big data analysis. Her work integrates multi-omics analytics, computational modeling, and machine learning to uncover disease biomarkers, elucidate therapeutic mechanisms, and accelerate the discovery of bioactive compounds from natural medicines. Dr. Yinfeng Yang has made significant contributions to AI-assisted drug discovery (AIDD), advancing methodologies in molecular docking, molecular dynamics simulations, high-throughput virtual screening, and quantitative structure–activity relationship modeling. She has authored 44 Scopus-indexed publications, accumulating 5,663 citations across 5,524 documents, supported by a Scopus h-index of 18, underscoring her impact in computational biology and integrative medicine research. Her studies, published in leading journals such as Journal of Advanced Research, Phytomedicine, ACS Omega, Drug Discovery Today, and Current Medicinal Chemistry, span diverse topics including cancer prognosis modeling, multi-scale mechanisms of herbal medicine, ADMET prediction frameworks, and the therapeutic potential of Ginkgo biloba in oncology and neurological disorders. Dr. Yinfeng Yang has led and contributed to numerous scientific research projects focused on TCM modernization, biomedical intelligence, and compound drug discovery. She also plays an active role in scholarly publishing as an editorial board member for journals such as PLOS ONE and Journal of Hebei Medical University, and serves as a recognized reviewer for more than 30 international journals, including Nature Communications, Phytomedicine, ACS Omega, and Journal of Ethnopharmacology. Her research excellence continues to advance innovation in AI-driven precision medicine and the global understanding of natural-product-based therapeutics.

Profiles: Scopus | Google Scholar | ORCID

Featured Publications

  • Fan, N., Chen, J., Wang, J., Chen, Z. S., & Yang, Y. (2025). Bridging data and drug development: Machine learning approaches for next-generation ADMET prediction. Drug Discovery Today, Article 104487.

  • Han, Z., Liu, Q., Yang, J., Wang, X., Song, W., Wang, J., & Yang, Y. (2025). Exploration of the mechanism of Ginkgo biloba leaves targeted angiogenesis against gastric cancer. ACS Omega, 10(35), 40460–40476.

  • Li, H., Fu, S., Shen, P., Zhang, X., Yang, Y., & Guo, J. (2025). Mitochondrial pathways in rheumatoid arthritis: Therapeutic roles of traditional Chinese medicine and natural products. Phytomedicine, Article 157106.

  • Yang, P., Wang, X., Yang, J., Yan, B., Sheng, H., Li, Y., Yang, Y., & Wang, J. (2025). AI-driven multiscale study on the mechanism of Polygonati Rhizoma in regulating immune function in STAD. ACS Omega, 10(19), 19770–19796.

  • Zhang, H., Xu, Q., Kan, H., Yang, Y., & Cai, Y. (2025). Exploration of the clinicopathological and prognostic significance of BRCA1 in gastric cancer. Discover Oncology, 16(1), 381.

Mehnaz Tabassum | Computer Science and Artificial Intelligence | Women Researcher Award

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Dr. Mehnaz Tabassum | Computer Science and Artificial Intelligence | Women Researcher Award

University of Sydney | Australia

Dr. Mehnaz Tabassum is an accomplished researcher in Computational Neurosurgery and Health Innovation, with core expertise in medical image analysis, artificial intelligence, and brain tumor diagnostics. Her research integrates deep learning, radiomics, and neuroimaging to enhance the precision of tumor segmentation, classification, and recurrence prediction in neuro-oncology. Her scholarly contributions include 14 Scopus-indexed publications, with a total of 87 citations and an h-index of 4 (Scopus metrics). She has published in prestigious journals such as Cancers, European Radiology, and Neuro-Oncology Advances, and has presented her findings at leading international conferences including IEEE EMBC and IEEE ISBI. Dr. Mehnaz Tabassum’s recent research explores cross-modality medical image synthesis, MRI-to-PET generation using diffusion and GAN-based models, and meta transfer learning for brain tumor segmentation. Her innovative work advances computational solutions for precision medicine and AI-assisted neuroimaging. She has received multiple distinctions, including the Pro-Vice Chancellor’s Research Excellence Scholarship and the Henry Sutton Postgraduate Research Scholarship, alongside a Best Paper Award for excellence in scientific contribution. Her interdisciplinary research continues to impact the fields of AI-driven diagnostics, eye-tracking in medical imaging, and computational modeling for neurosurgical innovation, reflecting her commitment to advancing data-driven healthcare and translational neuroscience.

Profiles: Scopus | Google Scholar | ORCID | ResearchGate | Staff Page

Featured Publications

  • Tabassum, M., Suman, A. A., Suero Molina, E., Pan, E., Di Ieva, A., & Liu, S. (2023). Radiomics and machine learning in brain tumors and their habitat: A systematic review. Cancers, 15(8), Article 2034. https://doi.org/10.3390/cancers15082034

  • Ghose, P., Alavi, M., Tabassum, M., Ashraf Uddin, M., Biswas, M., Mahbub, K., … & Hassan, M. (2022). Detecting COVID-19 infection status from chest X-ray and CT scan via single transfer learning-driven approach. Frontiers in Genetics, 13, 980338. https://doi.org/10.3389/fgene.2022.980338

  • Moradizeyveh, S., Tabassum, M., Liu, S., Newport, R. A., Beheshti, A., & Di Ieva, A. (2024). When eye-tracking meets machine learning: A systematic review on applications in medical image analysis. arXiv preprint arXiv:2403.07834. https://arxiv.org/abs/2403.07834

  • Tabassum, M., Suman, A. A., Russo, C., Di Ieva, A., & Liu, S. (2023). A deep learning framework for skull stripping in brain MRI. Neurocomputing (Under review).

  • Afrin, F., Al-Amin, M., & Tabassum, M. (2015). Comparative performance of using PCA with K-means and fuzzy C means clustering for customer segmentation. International Journal of Scientific and Technology Research, 4(8), 70–74.

Singanamalla Vijayakumar | Computer Science and Artificial Intelligence | Excellence in Innovation Award

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Dr. Singanamalla Vijayakumar | Computer Science and Artificial Intelligence | Excellence in Innovation Award

Associate Professor | GRIET | India

Dr. S. Vijayakumar is a distinguished academician and researcher in the domain of Computer Science and Engineering with over 11 years of robust teaching and research experience. He has consistently demonstrated innovation and leadership across reputed institutions including VIT University, Galgotias University, and Jain University. His work in image processing, soft computing, and big data analytics stands at the confluence of academic excellence and real-world relevance. Passionate about societal problem-solving through research, Dr. Vijayakumar is a visionary aiming to integrate research, education, and innovation to foster impactful developments in emerging technologies.

Author Profile👤

Google Scholar

Scopus

Strengths for the Awards✨

Dr. S. Vijayakumar exemplifies a strong candidate for the Excellence in Innovation Award through his interdisciplinary research, significant publication track record, and a demonstrated ability to transform research into practical innovation. With over 11.5 years of academic and research experience, he has extensively contributed to image processing, soft computing, big data stream analytics, and real-time computing, with an emphasis on Synthetic Aperture RADAR (SAR) image despeckling and satellite image analysis.

Some standout strengths include:

  • Rich publication portfolio: He has published in numerous SCI, Scopus, and Springer journals with impact factors ranging from 1.0 to over 5.2, especially on topics like SAR image noise reduction, oil spill detection, and energy-efficient WSN protocols.

  • Patents and Innovation: He has filed patents like “Predicting Micro-Enterprise Failures Using Machine Learning Techniques” and is actively pursuing more with international relevance.

  • Global Collaborations: Notable engagement with international scholars and editorial boards, reflecting his global reach and thought leadership.

  • Research-Driven Teaching: Integrates research into pedagogy, mentoring students through project-based and ABET-aligned learning models.

  • Forward-looking Research Agenda: A visionary plan focusing on high-impact publications, product development, patent filings, and collaborations with research-focused institutions like ISRO and NASA.

  • Multi-domain Expertise: From image analysis to AI-IoT integration, his cross-disciplinary approach fosters innovation beyond conventional boundaries.

🎓 Education

Dr. Vijayakumar holds a Ph.D. in Computer Science and Engineering from VIT University, Vellore (2014–2018), where he specialized in soft computing techniques for speckle noise removal in SAR images. He earned his M.Tech. and B.Tech. in Computer Science and Engineering from Jawaharlal Nehru Technological University, Anantapur (2011–2013 and 2007–2011, respectively). His educational foundation is characterized by a consistent focus on computational intelligence, real-time systems, and data-driven innovation.

💼 Experience

With more than 11 years and 3 months of academic and research experience, Dr. Vijayakumar has served as an Associate Professor at Gokaraju Rangaraju Institute of Engineering and Technology since February 2024. His professional journey includes significant leadership roles such as Head of the CSE (Cyber Security) Department at the Institute of Aeronautical Engineering and various teaching roles at Jain Deemed University, Galgotias University, and VIT Vellore. He has also been an integral contributor to institutional accreditations like NAAC, NBA, and ABET.

🔬 Research Interests On Computer Science and Artificial Intelligence

Dr. Vijayakumar’s research interests lie in the domains of Image Processing, Soft Computing, Computer Vision, Big Data Stream Computing, IoT, Real-Time Data Analytics, and Fog Computing. His ongoing projects focus on developing efficient computational models for satellite image analysis, urban monitoring, and societal problem-solving. He envisions multi-university research collaborations and high-impact patents derived from his research.

🏅 Awards

Dr. Vijayakumar has received several prestigious recognitions for his contributions, including:

  • Research Award by VIT University (2014–2018)

  • Best Researcher Award at the 2nd International Research Awards on Science, Health and Engineering (2020)

  • Best Researcher Award at the 8th International Scientist Awards on Engineering, Science and Medicine (2020)

  • Outstanding Scientist Award at the 11th International Scientist Awards on Engineering, Science, and Medicine (2020)
    These accolades reflect his consistent commitment to innovation, quality research, and academic leadership.

📚 Publications

  • Internet of Things–based pharmaceutics data analysis
    Authors: P. Dhingra, N. Gayathri, S.R. Kumar, V. Singanamalla, C. Ramesh, …
    Published in: Emergence of Pharmaceutical Industry Growth with Industrial IoT Approach, pp. 85–131
    Year: 2020
    Citations: 40

  • Reliable and energy‐efficient emergency transmission in wireless sensor networks
    Authors: V. Singanamalla, R. Patan, M.S. Khan, S. Kallam
    Published in: Internet Technology Letters, 2(2), e91
    Year: 2019
    Citations: 20

  • Emergence of Pharmaceutical Industry Growth with Industrial IoT Approach
    Authors: V.E. Balas, V.K. Solanki, R. Kumar
    Published by: Academic Press
    Year: 2019
    Citations: 15

  • Web semantics for textual and visual information retrieval
    Authors: A. Singh, N. Dey, A.S. Ashour, V. Santhi
    Published by: IGI Global
    Year: 2017
    Citations: 9

  • Neuro-fuzzy approach for speckle noise reduction in SAR images
    Authors: V. Singanamalla, S. Vaithyanathan
    Published in: International Conference on Recent Trends in Image Processing and Pattern Recognition
    Year: 2016
    Citations: 5

  • Computational Techniques of Oil Spill Detection in Synthetic Aperture Radar Data: Review Cases
    Author: S. Vijayakumar
    Published in: Recent Oil Spill Challenges That Require More Attention
    Year: 2023
    Citations: 3

  • Recent Trends in Image Processing and Pattern Recognition: First International Conference, RTIP2R 2016, Bidar, India, December 16–17, 2016, Revised Selected Papers
    Editors/Contributors: K.C. Santosh, M. Hangarge, V. Bevilacqua, A. Negi
    Published by: Springer
    Year: 2017
    Citations: 2

  • Semantic web-based framework for scientific workflows in e-science
    Authors: S. Vijayakumar, N. Dasari, B. Bhushan, R. Reddy
    Published in: Web Semantics for Textual and Visual Information Retrieval, pp. 187–202
    Year: 2017
    Citations: 1

  • Role of social networking sites in enhancing teaching environment
    Authors: S. Vijayakumar, V.R. Thakare, S.B. Bhushan, V. Santhi
    Published in: Web Semantics for Textual and Visual Information Retrieval, pp. 227–243
    Year: 2017
    Citations: 1

🔚 Conclusion

Dr. S. Vijayakumar exemplifies the spirit of the Excellence in Innovation Award through his unwavering dedication to technological advancement, interdisciplinary research, and impactful teaching. His research has not only added value to academia but also translated into real-world applications such as coastal monitoring and emergency communication. With a strong portfolio of international publications, research leadership, and innovation-driven initiatives, he continues to inspire the next generation of engineers and researchers. His nomination for this award is a testament to his remarkable journey and futuristic vision.