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