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 

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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

 

 

Gurami Tsitsiashvili | Statistics | Differential Equations Pioneer Award

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Prof. Dr. Gurami Tsitsiashvili | Statistics | Differential Equations Pioneer Award

Chief Researcher at Institute of Applied Mathematics Far Eastern Branch of the Russian Academy of Sciences, Russia

Dr. Gurami Shalvovich Tsitsiashvili is a distinguished mathematician specializing in applied mathematics, stochastic models, and stability analysis. With over 50 years of research experience at the Institute of Applied Mathematics, Far Eastern Branch of the Russian Academy of Sciences, he has made significant contributions to the mathematical modeling of complex systems. His research focuses on queueing theory, Markov chains, decomposition methods, and the construction of Lyapunov functions for stability analysis—key areas closely linked to differential equations. He has authored more than 180 publications, including influential monographs, and has served as a professor since 1992, mentoring generations of mathematicians. His interdisciplinary work extends to applications in heat transfer, epidemic modeling, and biorhythm analysis. While his contributions to applied differential equations are profound, a stronger focus on fundamental theoretical advancements in differential equations would further enhance his recognition. His expertise, leadership, and research impact make him a strong candidate for the Differential Equations Pioneer Award.

Professional Profile 

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Education

Dr. Gurami Shalvovich Tsitsiashvili holds a strong academic foundation in mathematics and physics. He earned his Master of Science (M.Sc.) degree from the prestigious Moscow Physico-Technical Institute in 1972. He further pursued advanced studies at the Far Eastern Branch of the USSR Academy of Sciences, obtaining his Ph.D. in Mathematics and Physics in 1976. His doctoral research focused on stability analysis, laying the groundwork for his expertise in stochastic systems. In 1993, he achieved a Doctor of Science (Dr. Sci.) degree with a thesis on decomposition analysis of complex systems, a significant milestone in his academic career. His extensive education in applied mathematics, theoretical physics, and system analysis has equipped him with the necessary skills to tackle complex mathematical problems, particularly in differential equations, queueing theory, and stochastic modeling. His academic journey has positioned him as a leading researcher in the field, contributing extensively to mathematical sciences.

Professional Experience

Dr. Tsitsiashvili has dedicated his career to the Institute of Applied Mathematics, Far Eastern Branch of the Russian Academy of Sciences, where he has worked since 1972. Beginning as a junior researcher, he progressed through various roles, becoming a senior researcher in 1976 and later heading a research laboratory in 1981. His leadership skills and scientific expertise led to his appointment as Vice-Head of the institute on science from 2003 to 2013. Since then, he has continued as the head of a research laboratory and a principal scientific researcher. In addition to his work at the institute, he has been a professor at Far Eastern Technical University since 1992 and at Far Eastern Federal University since 1996, where he has mentored numerous students. His long-standing academic and research career has significantly contributed to applied mathematics, particularly in stability analysis, stochastic processes, and decomposition methods.

Research Interest

Dr. Tsitsiashvili’s research interests span applied mathematics, stochastic processes, and complex system modeling. His primary focus is on queueing theory, Markov chains, stability analysis, and decomposition methods, all of which have strong applications in differential equations. He has extensively studied the stability of multi-channel queueing systems, Lyapunov function construction, and cooperative effects in stochastic models. His interdisciplinary approach extends to applications in heat transfer, epidemic modeling, and biorhythm analysis. His work in mathematical physics, particularly in transforming epidemic models into random walk problems, showcases his ability to bridge theoretical mathematics with real-world applications. Additionally, his studies on decomposition effects in stochastic systems provide valuable insights into system optimization. While his expertise in applied differential equations is substantial, a deeper engagement in fundamental theoretical developments in the field could further solidify his impact. His contributions continue to shape mathematical modeling and its applications across various scientific domains.

Awards and Honors

Dr. Tsitsiashvili’s contributions to applied mathematics and stochastic modeling have earned him widespread recognition. While specific awards and honors are not explicitly listed in his curriculum vitae, his longstanding leadership roles and extensive publication record underscore his influence in the field. His appointment as the head of a research laboratory and Vice-Head of the Institute of Applied Mathematics reflects the recognition of his expertise and contributions by his peers. His role as a professor at Far Eastern Technical University and Far Eastern Federal University further highlights his standing in the academic community. With over 180 publications, including several monographs, he has made significant contributions to mathematical research, particularly in stability analysis and decomposition methods. His recognition is also evident through his extensive collaborations with researchers worldwide. While he has achieved remarkable academic and professional milestones, additional international accolades would further enhance his global impact in the field of differential equations and applied mathematics.

Conclusion

Dr. Tsitsiashvili is a highly accomplished mathematician whose research has significantly advanced applied mathematics, particularly in stochastic modeling, stability analysis, and decomposition methods. His extensive professional experience at the Institute of Applied Mathematics and his academic contributions as a professor demonstrate his dedication to the field. His work on queueing theory, Markov chains, and cooperative effects in stochastic models has influenced various scientific domains, including physics, biology, and engineering. While his research has strong connections to differential equations, a greater focus on fundamental theoretical advancements in this area could further strengthen his case for the Differential Equations Pioneer Award. His leadership, extensive publication record, and interdisciplinary research make him a strong candidate for recognition. His contributions have not only advanced mathematical theory but also provided practical applications in real-world problems, cementing his legacy as a distinguished researcher in applied mathematics.

Publications Top Noted

  • Title: Assessment of the Effect of Regional Climate Conditions on the Abundance of the Pink Salmon, Oncorhynchus gorbuscha (Walbaum, 1792) (Salmonidae), in the Sea of Japan in 1980–2023
    Authors: T.A. Shatilina, G.S. Tsitsiashvili, M.A. Osipova, T.V. Radchenkova
    Year: 2024
    Source: Russian Journal of Marine Biology

  • Title: Determination of Stability and Reliability of Shortest Paths in a Graph through Lists of Labels in Dijkstra’s Algorithm
    Authors: G.S. Tsitsiashvili
    Year: 2024
    Source: Reliability: Theory and Applications

  • Title: Networks Based on Graphs of Transient Intensities and Product Theorems in Their Modelling
    Authors: G.S. Tsitsiashvili
    Year: 2024
    Source: Computation

  • Title: Algorithms for Approximating a Function Based on Inaccurate Observations
    Authors: G.S. Tsitsiashvili, M.A. Osipova
    Year: 2024
    Source: Reliability: Theory and Applications

  • Title: Limit Cycles of Length Two in the Rikker Model and Their Application in Fishing
    Authors: G.S. Tsitsiashvili, T.A. Shatilina, M.A. Osipova, T.V. Radchenkova
    Year: 2024
    Citations: 1
    Source: Reliability: Theory and Applications

  • Title: Controlled Queuing Systems with a Stationary Uniform Distribution
    Authors: G.S. Tsitsiashvili, Y.N. Kharchenko
    Year: 2024
    Source: Vestnik Tomskogo Gosudarstvennogo Universiteta – Upravlenie, Vychislitel’naya Tekhnika i Informatika

  • Title: Graph Algorithms for Calculating the Distribution of the Amur Tiger Tracks in Primorsky Krai
    Authors: G.S. Tsitsiashvili, V. Bocharnikov, S.M. Krasnopeyev, M.A. Osipova
    Year: 2024
    Source: Theoretical and Applied Ecology

  • Title: Statistical Evaluation of Input Flow Intensity in the Presence of an Interfering Parameter
    Authors: G.S. Tsitsiashvili
    Year: 2024
    Source: Conference Paper (No source information available)

  • Title: Formation of Large Anomalies in the Thermal Conditions of Waters on the Western and Eastern Shelf of the Sakhalin Island
    Authors: T.A. Shatilina, V.V. Moroz, G.S. Tsitsiashvili, T.V. Radchenkova
    Year: 2024
    Source: Physical Oceanography

  • Title: Fast Method for Estimating the Parameters of Partial Differential Equations from Inaccurate Observations
    Authors: G.S. Tsitsiashvili, A.I. Gudimenko, M.A. Osipova
    Year: 2023
    Source: Mathematics (Open Access)