Seung-Ju kang | Statistics | Best Researcher Award

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Dr. Seung-Ju kang | Statistics | Best Researcher Award

Chonnam National University, South Korea

Dr. Seung-Ju Kang , a dedicated veterinary scholar from Chonnam National University College of Veterinary Medicine, specializes in Internal Medicine and Emergency & Critical Care Medicine . With a strong academic foundation in veterinary science and a growing passion for clinical research, Dr. Kang recently published a peer-reviewed article in an internationally recognized journal . Though early in their research journey, they exhibit a clear focus on advancing critical veterinary care and a commitment to academic excellence. Their emerging contributions reflect both potential and purpose, particularly in high-impact, life-saving animal health domains. With integrity, enthusiasm, and a strong vision for future innovation, Dr. Kang stands as a promising new voice in veterinary research, ready to make significant strides in the scientific community.

Professional Profile

Scopus Profile | ORCID Profile

Education

Dr. Seung-Ju Kang pursued both his undergraduate and postgraduate studies at the prestigious Chonnam National University College of Veterinary Medicine. He earned his Bachelor of Veterinary Medicine with a strong academic foundation in animal health sciences. Further advancing his expertise, he completed a Master’s degree specializing in Veterinary Internal Medicine and Emergency & Critical Care Medicine. His educational journey reflects dedication to a complex and life-saving field, underpinned by rigorous clinical and academic training. Focused on excellence and lifelong learning, Dr. Kang continues to deepen his knowledge through evidence-based practices, clinical exposure, and scholarly pursuits, preparing him for impactful roles in both research and practice.

Professional Experience

Though early in his professional journey, Dr. Kang has cultivated hands-on experience in high-pressure veterinary environments . As a postgraduate specializing in Emergency & Critical Care Medicine, he has actively worked in clinical settings dealing with complex, time-sensitive cases requiring advanced diagnostic and therapeutic skills. His training included exposure to a variety of animal emergencies, internal disorders, and critical interventions, enhancing both his decision-making and patient management skills. Dr. Kang’s professional experience is rooted in continuous learning, mentorship under seasoned clinicians, and evidence-informed practice. This foundational experience positions him well to bridge clinical insight with scientific inquiry—a vital quality for any veterinary researcher in today’s fast-evolving medical landscape.

Research Interest

Dr. Kang’s primary research interest lies in Veterinary Internal Medicine and Emergency & Critical Care—a dynamic and high-impact field within animal health science. His academic and clinical experiences have shaped a passion for improving outcomes in life-threatening veterinary conditions through targeted diagnostics, advanced interventions, and translational research. With a keen focus on critical care protocols, systemic disorders, and emergency responses, Dr. Kang aims to explore innovative therapeutic strategies and contribute to the growing body of veterinary medical literature. His interests also extend to improving patient monitoring systems, fluid therapy approaches, and early detection techniques using technology. As a researcher, he is committed to developing knowledge that directly enhances animal welfare and clinical practice outcomes.

Awards and Honors

Dr. Seung-Ju Kang is currently nominated for the Best Researcher Award, recognizing his early but promising entry into scholarly publication and academic research. While this marks his first formal recognition at the research level, it represents a significant milestone in his academic journey. The nomination itself reflects his emerging potential in the veterinary research community and acknowledges the quality and relevance of his first published article in a peer-reviewed international journal. Though at the beginning of his accolades, Dr. Kang’s consistent dedication, subject focus, and clinical rigor have already earned him the respect of peers and mentors alike. With time, he is poised to build a rich portfolio of honors through impactful work and innovative thinking in veterinary science.

Research Skills

Dr. Kang brings a solid set of research skills honed through his postgraduate academic training and recent publication achievement. His abilities include conducting literature reviews, data collection and analysis, and interpreting clinical findings to inform practice. With firsthand clinical exposure, he integrates scientific inquiry with real-world veterinary challenges, particularly in emergency and internal medicine. He is proficient in formulating hypotheses, navigating ethical research protocols, and preparing manuscripts for academic journals. His emerging skillset also includes experience with patient monitoring tools, case study design, and collaboration in clinical settings. As a developing researcher, Dr. Kang demonstrates the curiosity, discipline, and methodological awareness required to contribute meaningfully to veterinary medicine’s academic and clinical advancements.

Publications Top Note

Title: Non-resectable bilateral malignant granulosa cell tumor with metastasis in a dog: a case report

Authors: Young-Tak Cho, Chang-Hyeon Choi, Keon Kim, Chang-Yun Je, Jae-Beom Joo, Seung-Ju Kang, Sang-Ik Park, Woong-Bin Ro*, Chang-Min Lee*

Year: 2025

Journal: Korean Journal of Veterinary Research

Volume & Issue: Volume 65, Issue 1, Article e7

DOI: https://doi.org/10.14405/kjvr.20240066

Citation (APA Style): Cho, Y.-T., Choi, C.-H., Kim, K., Je, C.-Y., Joo, J.-B., Kang, S.-J., Park, S.-I., Ro, W.-B., & Lee, C.-M. (2025). Non-resectable bilateral malignant granulosa cell tumor with metastasis in a dog: a case report. Korean Journal of Veterinary Research, 65(1), e7. https://doi.org/10.14405/kjvr.20240066

Source Links:

Conclusion

Dr. Seung-Ju Kang is a highly motivated, early-career veterinary researcher whose academic rigor, clinical focus, and sincere commitment to emergency and internal animal care set a strong foundation for future impact. With a solid educational background, real-world experience, and a growing research portfolio, he embodies the essential qualities of a next-generation veterinary scientist. His first publication marks a significant step forward, showcasing both competence and potential in contributing to high-value scientific literature. While still on the path of professional growth, his clarity of focus, work ethic, and innovative thinking point toward a promising future in research, academia, and clinical excellence. Dr. Kang is undoubtedly a rising talent in the world of veterinary medicine, ready to make lasting contributions.

 

Reanna Shah | Statistics | Best Researcher Award

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Dr. Reanna Shah | Statistics | Best Researcher Award

Medical Student at Icahn School of Medicine at Mount Sinai, United States

Dr. Reanna Shah 🎓 is an emerging medical researcher at Mount Sinai Hospital 🏥 with a focus on plastic, orthopedic, and breast surgery outcomes. With multiple abstracts accepted for prestigious conferences such as ASRM, NESPS, and Plastic Surgery The Meeting 📊🩺, her work spans topics like surgical planning, postoperative pain management, and the impact of socioeconomic factors on patient outcomes. Dr. Shah has collaborated with top surgeons including Dr. Peter Taub and Dr. Dennis Frank-Ito, contributing to innovative research using 3D reconstructions, AI comparisons 🤖, and health equity analytics. Her cross-disciplinary studies are shaping better surgical protocols, enhanced wound care, and evidence-based decision-making 💡🔬. Committed to patient-centered research and clinical advancement, Dr. Shah exemplifies the next generation of healthcare scientists with integrity, insight, and academic rigor 🌟📚.

Professional Profile 

Google Scholar
Scopus Profile

🎓 Education

Dr. Reanna Shah holds a strong academic foundation rooted in clinical sciences and surgical research. She is affiliated with Mount Sinai Hospital, New York 🏥, where her education is enhanced through rigorous medical training, surgical research immersion, and advanced mentorship. Her academic pursuits focus on reconstructive surgery, patient outcomes, and anatomical modeling 🧠. Her educational journey is marked by precision, compassion, and curiosity—qualities she continuously applies in interdisciplinary environments. Throughout her medical training, she has also undertaken courses in medical ethics, quantitative research design, and evidence-based clinical practices 📘. Under guidance from esteemed physicians like Dr. Peter Taub and Dr. Dennis Frank-Ito, she has bridged textbook knowledge with real-world impact, paving the way for a dynamic medical career fueled by analytical rigor and hands-on surgical insight. 🎓📚

🩺 Professional Experience

Dr. Shah’s professional experience is rooted in cutting-edge clinical research across multiple departments at Mount Sinai Hospital, including Plastic Surgery, Orthopedic Surgery, and Breast Surgery 🏥. She has conducted retrospective and prospective studies on DIEP flap reconstructions, intraoperative hypothermia, and spinal surgery wound outcomes. Working with renowned surgeons, she has contributed to research on the anatomical variations in infants using 3D reconstructions 🧬 and explored health disparities in breast reconstruction through Area Deprivation Index scores 📊. Her work has been consistently selected for top national conferences, showcasing her ability to translate clinical challenges into impactful research. Through collaborative roles, she has developed strong protocols, data analysis frameworks, and manuscript development skills 🖊️, solidifying her as a reliable contributor in multidisciplinary surgical innovation. Her clinical insight is complemented by technical precision and research leadership in patient-focused care.

🔬 Research Interest

Dr. Shah’s research interests lie at the intersection of surgical innovation, patient outcomes, and health equity 💡. She is particularly passionate about improving reconstructive surgical techniques, especially in breast and spinal procedures. Her studies focus on identifying predictors of complications, optimizing wound closure, and analyzing the role of intraoperative variables like hypothermia on pain management and opioid use ⚖️. She is also exploring the integration of AI in surgery-related decision-making, such as comparing ChatGPT responses to clinical guidelines 🤖. Her interest in racial and socioeconomic disparities in surgical outcomes reflects her commitment to equitable healthcare delivery. Additionally, she investigates anatomical variability using 3D reconstructions in pediatric craniofacial structures. With a drive to transform clinical problems into research solutions, Dr. Shah contributes meaningfully to enhancing the safety, quality, and personalization of modern surgical care.

🏅 Awards and Honors

While still early in her professional trajectory, Dr. Reanna Shah has earned recognition through multiple research presentations accepted at prestigious national conferences, including: American Society for Reconstructive Microsurgery (ASRM), Plastic Surgery The Meeting (PSTM), Northeastern Society of Plastic Surgeons (NESPS) 🎖️. Her selection for oral and poster presentations across competitive forums reflects the high impact and relevance of her research. Working under respected clinical researchers, her findings on surgical outcomes, patient pain management, and procedural optimization have been spotlighted by expert panels. These distinctions mark her as a rising researcher in clinical medicine. Her early honors serve as testimony to both her scientific excellence and her dedication to advancing evidence-based surgery. As her peer-reviewed publication record expands, she is well-positioned for future national research awards and leadership in surgical science. 🏆📜

🛠️ Research Skills

Dr. Shah demonstrates a robust suite of research skills, combining clinical insight with analytical precision. She is proficient in retrospective and prospective study design, statistical analysis, literature reviews, and data interpretation 📊. She has applied these skills to study surgical techniques, opioid usage trends, wound healing outcomes, and social determinants of health. Additionally, she is skilled in presenting at national forums, manuscript writing, and collaborating across specialties. Her use of 3D reconstructions, health equity indices (e.g., ADI scores), and comparative AI analysis (ChatGPT vs. clinical guidelines) highlights her technical creativity and adaptability 🔍. Dr. Shah is also experienced in electronic medical record (EMR) data mining and chart reviews, enabling her to generate insights from complex clinical datasets. Her sharp methodological discipline and curiosity-driven mindset make her an invaluable asset in translational medical research. 🔬📑.

📝Publications Top Note

  • Title: Risuteganib—a novel integrin inhibitor for the treatment of non-exudative (dry) age-related macular degeneration and diabetic macular edema
    Authors: LT Shaw, A Mackin, R Shah, S Jain, P Jain, R Nayak, SM Hariprasad
    Year: 2020
    Citations: 52
    Source: Expert Opinion on Investigational Drugs, 29(6), 547–554

  • Title: The role of normal nasal morphological variations from race and gender differences on respiratory physiology
    Authors: R Shah, DO Frank-Ito
    Year: 2022
    Citations: 31
    Source: Respiratory Physiology & Neurobiology, 297, 103823

  • Title: Analyses on the influence of normal nasal morphological variations on odorant transport to the olfactory cleft
    Authors: RM Sicard, R Shah, DO Frank-Ito
    Year: 2022
    Citations: 11
    Source: Inhalation Toxicology, 34(11-12), 350–358

  • Title: Computational analysis of olfactory airspace in patients with unilateral cleft lip nasal deformity
    Authors: R Shah, JR Marcus, DO Frank-Ito
    Year: 2021
    Citations: 9
    Source: The Cleft Palate-Craniofacial Journal, 58(10), 1242–1250

  • Title: A systematic analysis of surgical interventions for the airway in the mature unilateral cleft lip nasal deformity: a single case study
    Authors: RT Tillis, R Shah, HL Martin, AC Allori, JR Marcus, DO Frank-Ito
    Year: 2022
    Citations: 8
    Source: International Journal of Computer Assisted Radiology and Surgery, 17(1), 41–53

  • Title: Intranasal spray characteristics for best drug delivery in patients with chronic rhinosinusitis
    Authors: C Popper, H Martin, R Shah, R Sicard, K Hodges, DO Frank-Ito
    Year: 2023
    Citations: 6
    Source: The Laryngoscope, 133(5), 1036–1043

  • Title: Characterizing olfactory dysfunction in patients with unilateral cleft lip nasal deformities
    Authors: SM Russel, H Chiang, JB Finlay, R Shah, JR Marcus, DW Jang, et al.
    Year: 2023
    Citations: 5
    Source: Facial Plastic Surgery & Aesthetic Medicine, 25(6), 457–465

  • Title: Nasal airway obstruction in patients with cleft lip nasal deformity: A systematic review
    Authors: H Chiang, R Shah, C Washabaugh, DO Frank-Ito
    Year: 2024
    Citations: 3
    Source: Journal of Plastic, Reconstructive & Aesthetic Surgery, 92, 48–60

  • Title: The Impact of Depression and Anxiety Comorbidities on Acute Postoperative Pain After DIEP Flap Breast Reconstruction
    Authors: C Wang, M Tang, R Shah, J Frost, E Kim, PE Shamamian, O Oleru, et al.
    Year: 2024
    Citations: 2
    Source: Microsurgery, 44(8), e31260

  • Title: Neighborhood deprivation is associated with increased postoperative complications after implant-based breast reconstruction
    Authors: C Wang, J Frost, M Tang, R Shah, E Kim, PE Shamamian, KE Montalmant, et al.
    Year: 2024
    Citations: 1
    Source: Clinical Breast Cancer, 24(7), 604–610

  • Title: D25. Assessment of Anatomic Eligibility for Robotic-assisted DIEP Flap Harvest
    Authors: J Roth, M Godek, E Fung, R Shah, B Yu, K Montalmant, A Kagen, et al.
    Year: 2025
    Source: Plastic and Reconstructive Surgery–Global Open, 13(S2), 98

  • Title: D26. Contralateral Breast Symmetrization at Time of Unilateral DIEP Flap Breast Reconstruction Reduces Length of Reconstructive Sequence Without Compromising Outcomes
    Authors: R Shah, E Fung, K Montalmant, B Yu, C Wang, J Frost, M Tang, E Kim, et al.
    Year: 2025
    Source: Plastic and Reconstructive Surgery–Global Open, 13(S2), 98–99

  • Title: SP43. Impact of SSRI Use on Postoperative Complications in DIEP Flap Breast Reconstruction
    Authors: J Frost, J Roth, C Wang, KE Montalmant, BZ Yu, R Shah, M Tang, E Kim, et al.
    Year: 2025
    Source: Plastic and Reconstructive Surgery–Global Open, 13(S1), 166–167

  • Title: SP59. Impact of Food Swamp Scores and Insurance on DIEP Flap Breast Reconstruction Outcomes: A Quantitative Analysis
    Authors: KE Montalmant, CY Wang, E Kim, R Shah, J Frost, M Tang, N Seyidova, et al.
    Year: 2025
    Source: Plastic and Reconstructive Surgery–Global Open, 13(S1), 177–178

  • Title: Randomized Controlled Trial Outcomes for Non-Operative Management of Lateral Epicondylitis of the Elbow Are Statistically Fragile: A Systematic Review
    Authors: R Shah, A Yu, MG Kelley, A Yendluri, D Bienstock, K Nietsch, MN Megafu, et al.
    Year: 2025
    Source: JSES Reviews, Reports, and Techniques

  • Title: Optimizing Wound Healing Following Cervical Spine Surgery
    Authors: MP Saturno, R Shah, D Kwon, O Oleru, N Seyidova, J Russell, AC Hecht, et al.
    Year: 2025
    Source: Annals of Plastic Surgery, 94(4S), S238–S242

  • Title: Optimizing Wound Healing Following Lumbar Spine Surgery
    Authors: DY Kwon, R Shah, M Saturno, S Genet, E Kim, I Fu, N Seyidova, O Oleru, et al.
    Year: 2025
    Source: Journal of Plastic, Reconstructive & Aesthetic Surgery, 103, 73–79

  • Title: Investigation of Lower Extremity Injuries in Men’s Ice Hockey: A 10-Year Analysis Across the COVID-19 Era
    Authors: MG Kelley, H Denwood, R Shah, A Yendluri, S Dhanjani, A Fitch, et al.
    Year: 2025
    Source: The Physician and Sportsmedicine, 1–9

  • Title: Understanding the Role of Intraoperative Hypothermia in Perioperative Opioid Requirements in Immediate Implant-Based Breast Reconstruction
    Authors: CY Wang, R Shah, J Frost, M Tang, E Kim, PE Shamamian, O Oleru, et al.
    Year: 2024
    Source: Journal of Plastic, Reconstructive & Aesthetic Surgery, 98, 246–254

  • Title: The Role of Normal Nasal Morphological Variations from Race and Gender Differences on Respiratory Physiology (Reprint)
    Authors: R Shah, DO Frank-Ito
    Year: 2024
    Source: ESS Open Archive eprints, 7, 00738250

🧠 Conclusion

Dr. Reanna Shah is a driven, multidisciplinary medical researcher whose clinical insights, research precision, and collaborative approach distinguish her as a rising figure in surgical science. Her work bridges the gap between clinical excellence and academic innovation, consistently addressing patient-centered concerns like surgical outcomes, pain control, and health equity. Through mentorship under renowned clinicians and her own initiative, she has built a profile that reflects curiosity, rigor, and leadership potential 🌟. Her growing presence at national conferences and commitment to data-driven decision-making align her with the ideals of modern medicine. With continued growth in publications and leadership roles, Dr. Shah is poised to contribute significantly to the future of surgical research and healthcare innovation 🔗. Her evolving contributions embody the core values of dedication, impact, and integrity in science and medicine.

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