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.

Malathy N | Computer Science | Best Researcher Award

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Dr. Malathy N | Computer Science | Best Researcher Award

Associate Professor | Mepco Schlenk Engineering College | India

Dr. N. Malathy is an esteemed academician and researcher currently serving as an Associate Professor in the Department of Information Technology at Mepco Schlenk Engineering College. With over 12 years of experience in teaching and research, she has made significant contributions to the fields of Mobile Computing, IoT, Networks, Fog Computing, and Machine Learning. She holds a Ph.D. in Fog Computing from Anna University (2024) and has published 24 research papers. Her expertise extends to international certifications in AI, cloud computing, and cybersecurity, and she is an active mentor and reviewer in her domain.

Profile

Google Scholar

ORCID

Scopus

Strengths for the Awards✨

  • Research Excellence 📚

    • 24 research publications, including 5 SCI and 11 Scopus-indexed papers.
    • Notable contributions to Fog Computing, IoT, Machine Learning, and Distributed Computing.
    • Recent high-impact publications, including studies on Federated Learning, Intrusion Detection, and Green Computing.

  • Innovation & Intellectual Property 🏅

    • One granted patent and four published patents demonstrate innovative contributions to applied research.
    • Published two book chapters, contributing to academic literature.

  • Recognized Expertise & Certifications 🎓

    • International certifications from NVIDIA (Deep Learning), Infosys (Generative AI), and Checkpoint (Cybersecurity).
    • Oracle certification in PL/SQL Database Programming and EMC Cloud Infrastructure & Services certification.
    • Top 1%-5% rankings in multiple NPTEL courses, showing a commitment to continuous learning.

  • Professional Engagement & Recognition 🌍

    • Reviewer for 44 research papers, indicating active involvement in the research community.
    • Awarded Best Paper at an International Conference (ICSTA 2022).
    • Guest lectures (9) and faculty development programs (FDPs) conducted, demonstrating leadership in research dissemination.
    • Member of ISTE and CSI, indicating professional affiliation.

🎓 Education

  • Ph.D. in Fog Computing, Anna University, 2024
  • M.E. in Computer & Communication, SSN College of Engineering, Anna University, 2012
  • B.E. in Computer Science & Engineering, Francis Xavier Engineering College, Anna University, 2010

👩‍🏫 Experience

  • Associate Professor, MEPCO Schlenk Engineering College (2024–Present)
  • Assistant Professor (Sl. Grade), MEPCO Schlenk Engineering College (2023–2024)
  • Assistant Professor (Sr. Grade), MEPCO Schlenk Engineering College (2017–2023)
  • Assistant Professor, MEPCO Schlenk Engineering College (2012–2017)

🔬 Research Interests On Computer Science

Dr. Malathy’s research spans multiple cutting-edge areas, including:

  • Distributed Computing: Efficient task scheduling, multi-objective optimization for fog computing
  • IoT: Smart systems development, security research, intrusion detection
  • Fog Computing: Resource allocation, task scheduling, privacy-preserving methodologies
  • Machine Learning: Federated learning for security, optimization algorithms, AI applications

🏆 Awards & Achievements

  • Best Paper Award, ICSTA 2022, Ramco Institute of Technology
  • Top 1% & 5% Ranker in NPTEL Courses on Cloud Computing, Big Data, and HCI
  • International Certifications:
    • NVIDIA Deep Learning (2023)
    • Checkpoint Certified Security Administrator R81 (2024)
    • Generative AI Certifications (Infosys, 2024)
    • Oracle Certification in Database Programming (2019)
  • Top Performing Mentor, NPTEL (2025)

📚 Publications

Dr. Malathy has authored several impactful research papers in reputed journals:

  • Multi‐objective task scheduling in fog computing using improved gaining sharing knowledge based algorithm

    • Authors: M. Navaneetha Krishnan, R. Thiyagarajan
    • Year: 2022
    • Citations: 12

  • VAGR—Void aware in geographic routing for wireless sensor networks

    • Authors: A. Revathi, N. Malathy
    • Year: 2016
    • Citations: 8

  • Entropy‐based complex proportional assessment for efficient task scheduling in fog computing

    • Authors: N. K. Malathy, T. Revathi
    • Year: 2023
    • Citations: 7

  • Opposition‐based improved memetic algorithm for placement of concurrent Internet of Things applications in fog computing

    • Authors: N. Malathy, T. Revathi
    • Year: 2024
    • Citations: 3

  • Pedestrian safety system with crash prediction

    • Authors: M. K. V. S. Ms. N. Malathy, Dr. S. Kavi Priya
    • Year: 2022
    • Citations: 3*

  • Smart trash bin level monitoring system

    • Authors: M. S. A. Ms. N. Malathy, Miss. D. Kaviyaadharshani
    • Year: 2022
    • Citations: 3*

  • Pedwarn-enhancement of pedestrian safety using mobile application

    • Authors: N. Malathy, S. Sabarish Nandha, B. Praveen, K. Pravin Kumar
    • Year: 2020
    • Citations: 2

  • Topology control for depth adjustment using geographic routing in underwater wireless sensor networks

    • Authors: A. Revathi, N. Malathy
    • Year: 2016
    • Citations: 1

  • Energy Efficient Workflow Scheduling for Fog-enhanced IOT Based Healthcare Application

    • Authors: N. Malathy, M. Kartheeswari, M. Yogalakshmi
    • Year: Not mentioned
    • Citations: 1

📌 Conclusion

Dr. N. Malathy continues to make remarkable strides in academia, research, and technological innovation. Her expertise in Distributed Computing, IoT, Fog Computing, and Machine Learning is evident from her numerous publications, patents, and academic contributions. Through mentoring, research, and professional engagements, she actively bridges theoretical advancements with real-world applications, positioning herself as a leader in her field.