Nan Zhang | Data Science | Best Researcher Award

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Assist. Prof. Dr. Nan Zhang | Data Science | Best Researcher Award

Department Head at Wuxi Institute of Technology, China

Dr. Nan Zhang 🎓, currently serving as the Head of Department at Wuxi Institute of Technology 🏫, is an accomplished researcher with a Ph.D. in Pattern Recognition and Intelligent Systems from Nanjing University of Science and Technology 🧠. Her expertise spans across pattern recognition, computer vision, and machine learning 🤖. With 9 high-impact journal publications 📚, 18 patents 🔬, and two published books 📘, she has made notable contributions to both theoretical research and applied innovation. Dr. Zhang’s work includes advanced AI applications in medical thermal imaging and exercise prescription optimization for Type 2 diabetes patients 💡💊. Her involvement in 8 research projects and 3 industry collaborations reflects strong academic-industry synergy 🤝. Dr. Zhang exemplifies innovation, leadership, and a commitment to real-world impact, making her a valuable asset to the global research community 🌏.

Professional Profile 

ORCID Profile

🎓 Education

Dr. Nan Zhang earned her Ph.D. in Pattern Recognition and Intelligence System from the esteemed Nanjing University of Science and Technology 🏛️ in 2013. Her academic journey reflects a strong foundation in mathematics, computing, and system intelligence 📐💻. With a passion for innovation and analytical precision, she focused her doctoral research on advanced feature extraction and intelligent algorithm design 🧠. Her educational background has provided her with a solid base to explore diverse AI applications, especially in computer vision and medical technology 💊. This scholarly pursuit laid the groundwork for her prolific career as a researcher, educator, and innovator, enabling her to bridge the gap between theory and real-world applications 🌐.

👩‍🏫 Professional Experience

Currently the Department Head and Associate Professor at the School of Control Engineering, Wuxi Institute of Technology 🏫, Dr. Nan Zhang brings over a decade of academic excellence and research leadership. She has successfully led 8 major research projects and collaborated on 3 industry consultancy initiatives 🧪🤝. Her dual expertise in academic rigor and industrial relevance enables her to train students and researchers to tackle real-world challenges. Under her leadership, the department has expanded its focus on AI integration and technological innovation 🌟. She also contributes actively as a mentor, curriculum designer, and academic reviewer, emphasizing both theory and its practical implementation 💼📘.

🔍 Research Interest

Dr. Zhang’s primary research interests revolve around Pattern Recognition, Computer Vision, and Machine Learning 🤖. Her work focuses on developing algorithms that enable intelligent systems to perceive, interpret, and act on complex data, especially in dynamic environments. Recently, she has explored deep learning applications in medical thermal imaging for diagnostic improvements 🩻 and adaptive exercise prescriptions for diabetic patients 🏃‍♀️💉. Her research bridges the gap between AI theory and practical healthcare technology, aiming to make intelligent systems more precise and accessible. She is passionate about advancing human-centric AI that not only predicts but enhances decision-making across health and industrial sectors 🧬🧑‍⚕️.

🏅 Awards and Honors

With a track record of excellence, Dr. Nan Zhang has been recognized through multiple patents (18 total) 🧾 and journal publications (9 indexed in SCI/Scopus) 📚. Her books (ISBN: 978-7-121-45435-6, 978-620-2-30759-8) showcase her thought leadership in emerging technologies. While not explicitly listed, her portfolio and credentials reflect eligibility for prestigious honors like the Best Researcher Award 🌟. Her contributions in AI-enhanced diagnostics and intelligent system modeling highlight her impact in both academic and applied domains 🧠🔬. These recognitions affirm her continued commitment to innovative, responsible, and impactful science on both national and global platforms 🌍🏆.

🛠️ Research Skills

Dr. Zhang excels in AI algorithm design, feature extraction, deep learning, and image analysis 🔧🧠. She is proficient in various programming and analytical tools used in computer vision and pattern recognition, such as Python, MATLAB, and TensorFlow 💻📊. Her strength lies in bridging theoretical models with functional systems, particularly in biomedical imaging and intelligent diagnostics 🔬🖥️. In addition, she brings expertise in scientific writing, patent drafting, and industry collaboration, enabling her to work effectively across multidisciplinary teams. Her ability to lead and innovate in both solo and collaborative research settings reflects her technical depth and strategic foresight 🔍🌐.

Publications Top Note 📝

  • Title: Medical image inpainting with edge and structure priors
    Authors: Qianna Wang, Yi Chen, Nan Zhang, Yanhui Gu
    Year: 2021
    DOI / Source: 10.1016/j.measurement.2021.110027
    Published in: Measurement (Elsevier)
    Citation Source: Crossref

  • Title: Robust H∞ filtering for Markovian jumping static neural networks with time-varying delays
    Authors: Aodong Zhao, Nan Zhang, Maolong Xi, Jun Sun, Meiyan Dong
    Year: 2020
    DOI / Source: 10.1177/1748302620931340
    Published in: Journal of Algorithms & Computational Technology (SAGE)
    Citation Source: Crossref

  • Title: Feature extraction based on Low-rank affinity matrix for biological recognition
    Authors: Nan Zhang, Yi Chen, Maolong Xi, Fangqin Wang, Yanwen Qu
    Year: 2018
    DOI / Source: 10.1016/j.jocs.2018.06.001
    Published in: Journal of Computational Science (Elsevier)
    Citation Source: Crossref

  • Title: Low-rank representation based discriminative projection for robust feature extraction
    Authors: Nan Zhang, Jian Yang
    Year: 2013
    DOI / Source: 10.1016/j.neucom.2012.12.012
    Published in: Neurocomputing (Elsevier)
    Citation Source: Crossref

📝 Conclusion

Dr. Nan Zhang represents a rare blend of academic brilliance, research depth, and societal relevance 🌟. Her contributions in AI-driven medical imaging, pattern recognition, and intelligent diagnostics highlight a career committed to innovation with impact 🚀. With a clear vision and versatile skillset, she continues to advance next-generation technologies that bridge health and machine intelligence 🧬🤖. As a mentor, department leader, and researcher, Dr. Zhang has cultivated a culture of excellence and curiosity, inspiring the next wave of innovators 🌱. Her dedication, accomplishments, and forward-thinking make her an ideal nominee for prestigious recognitions like the Best Researcher Award 🏅🎓.

Iliyas Khan | Statistics | Best Researcher Award

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Dr. Iliyas Khan | Statistics | Best Researcher Award

Teaching Assistance at Universiti Teknologi PETRONAS, Malaysia

Dr. Iliyas Karim Khan is a dedicated researcher specializing in machine learning, statistical modeling, forecasting, and big data analysis. He holds a Ph.D. from Universiti Teknologi PETRONAS (UTP), Malaysia, along with advanced degrees in statistics from Peshawar University, Pakistan. With a strong publication record in Q1 journals, his research focuses on optimizing clustering algorithms, particularly in K-means clustering and data science applications. His expertise extends to programming and statistical tools such as Python, SPSS, Stata, and EViews. Dr. Khan has gained extensive teaching experience, serving as a Teaching Assistant at UTP and a Subject Specialist in Pakistan. He was recognized with a Publication Recognition Achievement (2024) at UTP, underscoring his research contributions. His work is instrumental in improving data-driven decision-making and computational efficiency, making him a valuable asset in the academic and research community. His commitment to innovation and education positions him as a promising leader in his field.

Professional Profile 

Google Scholar
Scopus Profile

Education

Dr. Iliyas Karim Khan has a strong academic background in statistics and data science. He earned his Ph.D. in 2024 from Universiti Teknologi PETRONAS (UTP), Malaysia, focusing on optimizing machine learning algorithms. Prior to that, he completed an M.Phil. (2016) and M.Sc. (2014) in Statistics from Peshawar University, Pakistan, and a B.Sc. in Statistics (2012) from SBBU Sheringhal, Upper Dir, Pakistan. His foundational studies in science and engineering were completed at BISE Peshawar, along with a B.Ed. (2015) for pedagogical training. His educational journey reflects his commitment to advanced research in big data analysis, forecasting, and statistical modeling. Throughout his studies, he has demonstrated exceptional analytical skills, contributing to high-impact research in data clustering and computational efficiency. His academic achievements have positioned him as a promising researcher in the field of machine learning and statistical analytics, making significant contributions to data science methodologies.

Professional Experience

Dr. Iliyas Karim Khan has gained extensive teaching and research experience across multiple institutions. He worked as a Teaching Assistant at Universiti Teknologi PETRONAS (UTP), Malaysia, where he was actively involved in data science research and statistical analysis. In Pakistan, he served as a Subject Specialist at GHSS Bang Chitral for four years, strengthening his expertise in applied statistics and data analysis. His teaching career also includes one year at Abbottabad University of Science and Technology, where he mentored students in statistical modeling and machine learning techniques. Additionally, he completed an internship at the University of Peshawar and taught at Darban Degree College, Chitral. His experience encompasses curriculum development, student mentoring, and advanced research in statistical computing, making him an accomplished educator and researcher. His hands-on expertise in Python, SPSS, Stata, and EViews further enhances his ability to train future data scientists and statisticians.

Research Interest

Dr. Iliyas Karim Khan’s research revolves around machine learning, big data analytics, statistical modeling, and forecasting. His primary focus is on clustering algorithms, particularly enhancing the K-means clustering method for improved efficiency and accuracy. His work addresses key challenges in data science, such as non-spherical data, outlier handling, and optimal cluster selection, which have significant implications for AI-driven decision-making. Additionally, he explores computational time optimization and statistical accuracy in clustering techniques, contributing to the advancement of data-driven methodologies. His studies extend to forecasting models, applied statistical techniques, and real-world big data applications. Through numerous Q1 journal publications, he has proposed innovative solutions for refining data science models. His research is highly relevant in industries reliant on machine learning, artificial intelligence, and predictive analytics, positioning him as a key contributor to the evolution of data-centric technologies and computational intelligence.

Awards and Honors

Dr. Iliyas Karim Khan’s academic excellence and research contributions have been recognized through prestigious accolades. In 2024, he received the “Publication Recognition Achievement” award from Universiti Teknologi PETRONAS (UTP), Malaysia, honoring his impactful research in machine learning and statistical analysis. His Q1 journal publications in high-impact journals demonstrate his ability to produce innovative and widely acknowledged research. Additionally, his contributions to data clustering and computational efficiency have been well-received within the academic and research communities. His work on addressing K-means clustering limitations and enhancing algorithmic efficiency has been cited extensively, highlighting its significance in data science and artificial intelligence. His growing recognition in machine learning and big data analytics marks him as a promising scholar in his field. Through his research, he continues to make valuable contributions that shape the future of data-driven decision-making and statistical computing.

Conclusion

Dr. Iliyas Karim Khan is an exceptional researcher, educator, and innovator in the field of machine learning, statistical modeling, and big data analysis. His strong academic background, extensive teaching experience, and high-impact research make him a significant contributor to computational intelligence and data science advancements. His studies on enhancing K-means clustering efficiency, outlier handling, and computational time optimization have added valuable insights to the field. Through prestigious publications and academic honors, he has demonstrated his expertise in refining statistical methodologies for real-world applications. His proficiency in Python, SPSS, Stata, and advanced statistical techniques enables him to bridge the gap between theoretical advancements and practical applications in data science. As he continues to explore new frontiers in machine learning and predictive analytics, his work is expected to have a lasting impact on data-driven industries and AI-based decision-making systems.

Publications Top Noted

  • Title: Determining the Optimal Number of Clusters by Enhanced Gap Statistic in K-Mean Algorithm
    Authors: Iliyas Karim Khan, HB Daud, NB Zainuddin, R Sokkalingam, M Farooq, ME Baig, …
    Year: 2024
    Citations: 7
    Source: Egyptian Informatics Journal, Volume 27, Article 100504

  • Title: Numerical Solution of Heat Equation Using Modified Cubic B-Spline Collocation Method
    Authors: M Iqbal, N Zainuddin, H Daud, R Kanan, R Jusoh, A Ullah, Iliyas Karim Khan
    Year: 2024
    Citations: 3
    Source: Journal of Advanced Research in Numerical Heat Transfer, Volume 20, Pages 23-35

  • Title: Numerical Solution by Kernelized Rank Order Distance (KROD) for Non-Spherical Data Conversion to Spherical Data
    Authors: Iliyas Karim Khan, HB Daud, R Sokkalingam, NB Zainuddin, A Abdussamad, …
    Year: 2024
    Citations: 2
    Source: AIP Conference Proceedings, Volume 3123 (1)

  • Title: A Modified Basis of Cubic B-Spline with Free Parameter for Linear Second Order Boundary Value Problems: Application to Engineering Problems
    Authors: M Iqbal, N Zainuddin, H Daud, R Kanan, H Soomro, R Jusoh, A Ullah, …
    Year: 2024
    Citations: 1
    Source: Journal of King Saud University-Science, Volume 36 (9), Article 103397

  • Title: Standardizing Reference Data in Gap Statistic for Selection of Optimal Number of Clusters in K-Means Algorithm
    Authors: Iliyas Karim Khan, H Daud, N Zainuddin, R Sokkalingam
    Year: 2025
    Source: Alexandria Engineering Journal, Volume 118, Pages 246-260

  • Title: A Hybrid Stacked Sparse Autoencoder (HSSAE) Model for Predicting Type 2 Diabetes
    Authors: A Abdussamad, H Daud, R Sokkalingam, M Zubair, Iliyas Karim Khan, Z Mahmood
    Year: 2025
    Source: To be published

  • Title: A Mini Review of the State-of-the-Art Development in Oil Recovery Under the Influence of Geometries in Nanoflood
    Authors: M Zafar, H Sakidin, A Hussain, M Sheremet, I Dzulkarnain, R Safdar, …
    Year: 2024
    Source: Journal of Advanced Research in Micro and Nano Engineering, Volume 26 (1), Pages 83-101

  • Title: Exploring K-Means Clustering Efficiency: Accuracy and Computational Time Across Multiple Datasets
    Authors: Iliyas Karim Khan, H Daud, N Zainuddin, R Sokkalingam, A Abdussamad, AS Azad, …
    Year: 2024
    Source: Journal of Advanced Research in Applied Sciences and Engineering Technology

  • Title: Forecasting the Southeast Asian Currencies Against the British Pound Sterling Using Probability Distributions
    Authors: Iliyas Karim Khan, Ahmad Abubakar Suleiman, Hanita Daud, Mahmod Othman, Abdullah …
    Year: 2023
    Source: Data Science Insights, Volume 1 (1), Pages 31-51

  • Title: Addressing Limitations of the K-Means Clustering Algorithm: Outliers, Non-Spherical Data, and Optimal Cluster Selection
    Authors: Iliyas Karim Khan, Abdussamad, Abdul Museeb, Inayat Agha
    Year: 2024
    Citations: 4
    Source: AIMS Mathematics, Volume 9, Pages 25070-25097