Mustafa Kerem Kockar | Statistical Applications in Engineering | Best Researcher Award

Published on by Statistics

Assoc Prof. Dr. Mustafa Kerem Kockar | Statistical Applications in Engineering | Best Researcher Award

Hacettepe University | Turkey

Assoc Prof. Dr. Mustafa Kerem Kockar is a Turkish engineering geologist and geotechnical expert currently serving in the Department of Civil Engineering at Hacettepe University, Ankara. He holds a B.Sc., M.Sc., and Ph.D. in Geological Engineering from Middle East Technical University (METU), where his research focused on engineering geological and geotechnical site characterization of Upper Pliocene and Quaternary deposits west of Ankara. He has also conducted research at The University of Texas at Austin and Texas A&M University. His key research interests include engineering geology, rock and soil mechanics-particularly tunnelling, dam sites, slopes, and landslides-in-situ geotechnical and seismic site characterization, dynamic and static numerical modelling of geotechnical problems, environmental geotechnology, and engineering seismology with an emphasis on ground-motion amplification, attenuation modelling, earthquake hazard assessment, and enhanced geothermal systems involving hydraulic fracturing and micro-seismic monitoring. He has authored or co-authored 47 documents and has received 650 citations with an h-index of 17, reflecting his strong contribution to the field. He has supervised several postgraduate theses on landslide monitoring, slope stability, fibre-optic methods for early warning, and solar farm foundation design. His professional experience includes academic and research roles at METU, UT Austin, Texas A&M, Gazi University’s Earthquake Engineering Research Center, and Hacettepe University. He also contributes to Turkey’s national seismology and earth-interior advisory commission under the Disaster and Emergency Management Authority (AFAD) and has provided expert consultancy on major infrastructure projects such as the Trans Anatolian Natural Gas Pipeline (TANAP) and slope-erosion surveys, showcasing his interdisciplinary expertise in geotechnical fieldwork, seismic hazard analysis, and numerical modelling.

Profiles: Scopus | Google Scholar | Orcid

Featured Publications

Oner, G., Akgun, H., Koçkar, M. K., & Arslan Kelam, A. (2025). Municipal landfill site selection using TOPSIS methodology: A case study for Polatlı, Ankara, Türkiye. Bulletin of Engineering Geology and the Environment, 84(3), 126.

Arslan Kelam, A., Akgun, H., Bobet, A., & Kockar, M. K. (2025). Assessment of complex rock slope instabilities in Mudurnu, Turkey, through kinematic and dynamic analyses: A case study. Rock Mechanics and Rock Engineering, 58(2), 2223–2242.

cınar, Ö. F., Aldemir, A., Zervent, A., Yücel, O. B., Erberik, M. A., Anıl, O., & Koçkar, M. K. (2024). Fundamental period estimation of RC buildings by considering structural and non-structural damage distributions through neural network. Neural Computing and Applications, 36(3), 1329–1350.

Askan, A., Altindal, A., Aydin, M. F., Erberik, M. A., Koçkar, M. K., Tun, M., et al. (2025). Assessment of urban seismic resilience of a town in Eastern Türkiye: Turkoglu, Kahramanmaras before and after 6 February 2023 M 7.8 Kahramanmaras earthquake. Earthquake Spectra, 41(1), 146–175.

Sahin, G., Okalp, K., Koçkar, M. K., Yilmaz, M. T., Jalehforouzan, A., Temiz, F. A., et al. (2024). Development of a GIS-based predicted map of Türkiye using geological and topographical parameters: Case study for the region affected by the 6 February 2023 earthquakes. Seismological Research Letters, 95(4), 2044–2057.

Arun Kumar Gudivada | Statistical Applications in Engineering | Best Researcher Award

Published on by Statistics

Assoc Prof. Dr. Arun Kumar Gudivada | Statistical Applications in Engineering | Best Researcher Award

Aditya University | India

Assoc. Prof. Dr. Arun Kumar, currently Associate Professor in the Department of Electronics & Communication Engineering at Aditya University, Surampalem, is an emerging researcher whose work spans VLSI, quantum computing, and quantum communication. Born in Kakinada, Andhra Pradesh, he obtained his B.Tech and M.Tech from a JNTU Kakinada–affiliated college, and earned his Ph.D. from Pondicherry University. Dr. Arun Kumar has published multiple peer-reviewed articles in well-recognized journals such as the Journal of Computational Science and Journal of Supercomputing, and has also presented at numerous international conferences. He serves as a reviewer for several Springer journals. According to his Google Scholar profile, he currently holds an h-index of 7 with a total of 129 citations across 19 published documents. His research contributions explore the theoretical and practical frontiers of quantum-enabled electronics and communication systems, seeking to bridge classical VLSI design with emerging quantum paradigms. He is committed to mentoring students and fostering collaborative research in the evolving fields of quantum technologies and nano-electronics.

Profiles: Scopus | Google Scholar

Featured Publications

Reddy, T. V., Kandadi, R., Suresh, R., Arunkumar, G. A., Kalli, S. R., & D, S. (2025). Design, modeling and comparative analysis of SRAM performance and functionality under the subthreshold regime for various technologies. 2025 Fourth International Conference on Smart Technologies, Communication …

Gudivada, A. A., Sattibabu, G., & Relangi, A. K. (2025). Power, area, and delay efficient synchronous ring counter using clock gating and multi-bit flip-flops in QCA technology. International Journal of Electronics Letters, 1–11.

Bhoopathi, A. A., R., R., Sailaja, C., Jennifer, D., & Gudivada, A. (2025). A study on microstructures and physical properties of high-entropy alloys and materials. Oxidation Communications, 48(1), 162–171.

Gudivada, A. A., Avala, E., Gummarekula, S., & Tulasi, V. R. (2025). ST-QCA based error free and area efficient 4:2 compressor design. Recent Trends in VLSI and Semiconductor Packaging, 111–118.

Noorbasha, S. K. (2024). VME-EFD: A novel framework to eliminate the electrooculogram artifact from single-channel EEGs. Biomedical Physics & Engineering Express, 11(1), 015041.

Abhijeet Das | Statistical Applications in Engineering | Machine Learning Award

Published on by Statistics

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.