Zeliha Coskun Tas | Statistical Applications in Engineering | Best Researcher Award

Published on by Statistics

Mrs. Zeliha Coskun Tas | Statistical Applications in Engineering | Best Researcher Award

Kocaeli University | Turkey

Mrs. Zeliha Coskun Tas is a distinguished researcher in the field of Biomedical Engineering, currently serving as a Research Assistant at Kocaeli University, Faculty of Technology, Biomedical Engineering Department. She is actively pursuing her Ph.D. at the Institute of Science, Kocaeli University, where she also completed her Master’s degree, following her Bachelor’s degree in Biomedical Engineering from Erciyes University. Her research expertise encompasses biomaterials, biometals, bioceramics, and functionally graded biomaterials, with a strong emphasis on developing innovative bioactive implant interfaces and evaluating biomechanical performance in medical applications. Zeliha Coskun Tas has authored and co-authored several impactful publications in high-ranking SCI-E journals, including the Journal of Biomedical Materials Research: Part A, World Neurosurgery, and the Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine. Her study, “A Novel Radially Graded Hydroxyapatite-Based Composite for Bioactive Implant Interfaces,” reflects her commitment to advancing bioengineering materials for enhanced implant functionality. In addition, she has presented multiple peer-reviewed papers at international conferences in Italy and Turkey, focusing on 3D printing applications, biomechanical testing, and advanced implant design. Her research contributions have also extended to nationally funded projects supported by Kocaeli University’s Scientific Research Project Unit (BAP), where she played a leading role in projects such as Production and Characterization of Functionally Graded Ceramic and Polymer Doped Titanium Implants and Development of an Apparatus Design for Radial Gradient Powder Material Casting. Her earlier project, Development of Torsion and Four-Point Bending Test Systems for Finger and Toe Bones, demonstrates her interdisciplinary approach linking materials science and biomechanics. Beyond research, she actively contributes to the scientific community through peer reviews for reputed journals such as the Journal of Materials Engineering and Performance, Sakarya University Journal of Science, and Physical and Engineering Sciences in Medicine. A recipient of the TÜBİTAK 2211-C and 2214-A scholarships, she continues to pursue excellence in biomedical research with a focus on creating advanced, sustainable, and biocompatible materials for medical innovation. Through her dedication, academic rigor, and innovative research, Res. Asst. Zeliha Coskun Tas exemplifies the new generation of biomedical engineers shaping the future of healthcare technology.

Profiles: Google Scholar

Featured Publications

Coşkun, Z., Çelik, T., & Kişioğlu, Y. (2023). Metatarsal bone model production using 3D printing and comparison of material properties with results obtained from CT-based modeling and real bone. Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine, 5.

Coşkun, Z., Çelik, T., & Kişioğlu, Y. (2021). Design and manufacture of the torque test setup for small and shapeless materials. Turkish Journal of Engineering, 6(1), 81–86.

Coşkun, Z., Çelik, T., & Kişioğlu, Y. (2021). Comparison of the stress distribution between high-heeled and flat shoes on the first metatarsal bone. Politeknik Dergisi, 24(3), 1303–1308.

Çelik, T., & Coşkun Taş, Z. (2024). Biomechanical evaluation of a newly developed functional-grade composite material for pedicle screws. World Neurosurgery, 187, e525–e533.

Coşkun Taş, Z., & Çelik, T. (2022). Design of new pedicle screw and biomechanical evaluation using finite element analysis. 3rd International Conference on Applied Engineering and Natural Sciences, 1.

Abhijeet Das | Statistical Applications in Engineering | Machine Learning Award

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Dr. Abhijeet Das | Statistical Applications in Engineering | Machine Learning Award

C.V. Raman Global University | India

Dr. Abhijeet Das, Ph.D. in Water Resource Engineering from C.V. Raman Global University, Bhubaneswar, is an accomplished civil engineering researcher specializing in watershed hydrology, hydrological modeling, climate change impact assessment, and GIS-based water resources management. With a strong academic foundation, including M.Tech and B.Tech degrees from Biju Patnaik University of Technology, he has combined rigorous research with nearly a decade of professional and teaching experience. Dr. Das has contributed extensively to collaborative national and international projects across Tunisia, USA, Oman, UK, South Africa, Syria, and Lebanon, focusing on water quality, hydrologic extremes, and sustainable water management through remote sensing, machine learning, and optimization techniques. He has published 88 documents indexed in Scopus, which have received 199 citations, achieving an h-index of 7, reflecting both productivity and the growing impact of his research contributions. His intellectual property portfolio includes over 30 patents filed in water resource engineering, geoinformatics, and environmental sustainability, showcasing innovation and applied problem-solving capacity. Dr. Das has actively engaged in more than 30 seminars, workshops, and international conferences, presenting advancements in civil and water resource engineering. His career trajectory illustrates a blend of academic excellence, applied research, and industry collaboration, making him a promising contributor to the advancement of sustainable infrastructure and water management systems.

Profiles: Scopus | Orcid

Featured Publications

Das, A. (2025). An optimization-based framework for water quality assessment and pollution source apportionment employing GIS and machine learning techniques for smart surface water governance. Discover Environment.

Das, A., & Mishra, S. (2025). Reimagining biofiltration for sustainable industrial wastewater treatment. Discover Sustainability.

Das, A. (2025). A data-driven approach utilizing machine learning (ML) and geographical information system (GIS)-based time series analysis with data augmentation for water quality assessment in Mahanadi River Basin, Odisha, India. Discover Sustainability.

Das, A. (2025). Evaluation and prediction of surface water quality status for drinking purposes using integrated water quality indices, GIS approaches, and machine learning techniques. Desalination and Water Treatment.

Das, A., Mishra, S., & Tripathy, B. (2025). Bioplastics: A sustainable alternative or a hidden microplastic threat? Innovative Infrastructure Solutions.