Chandrakanta Behera | Materials Science | Innovative Research Award

Innovative Research Award

Chandrakanta Behera
National Institute of Technology Rourkela, India

Chandrakanta Behera
Affiliation National Institute of Technology Rourkela
Country India
Scopus ID 58986119100
Documents 7
Citations 19
h-index 2
Subject Area Materials Science
Event International Material Scientist Awards
ORCID 0009-0006-8568-0560

Chandrakanta Behera is a researcher affiliated with the National Institute of Technology Rourkela whose scholarly contributions are centered on rock mechanics, blasting engineering, geological characterization, and mining-related risk assessment. His published studies investigate blast-induced fragmentation, rock mass classification systems, geological strength indices, and predictive frameworks for mining operations. Through a growing portfolio of peer-reviewed publications, Behera has contributed to the advancement of data-driven methodologies that support safer and more efficient excavation and blasting practices in the mining sector.[1]

Abstract

This article highlights the academic achievements of Chandrakanta Behera in the field of materials and mining-related engineering research. His work focuses on integrating geological parameters, risk assessment models, and predictive analytical frameworks to improve blast performance and operational safety. Published in recognized international journals, his studies provide practical approaches for evaluating rock fragmentation, drilling performance, and vibration attenuation in mining environments.[2]

Keywords

Rock Mechanics, Blast Fragmentation, Geological Strength Index, Mining Engineering, Risk Assessment, Materials Science, Surface Mining, Ground Vibration Analysis.

Introduction

Modern mining operations increasingly rely on predictive engineering models to optimize productivity while reducing operational risks. Researchers in this area contribute by developing methodologies that incorporate geological variability and engineering parameters into decision-making processes. Chandrakanta Behera’s investigations align with this objective through the application of geological strength indices, vulnerability assessments, and advanced comparative modeling approaches.[3]

Research Profile

Behera’s research profile demonstrates specialization in blast engineering and rock mass characterization. His publication record includes studies examining drilling rate estimation, fragmentation prediction, blast risk assessment, and the influence of geological factors on vibration attenuation. These investigations combine field observations with analytical and computational techniques to enhance engineering reliability.[4]

Research Contributions

  • Development of geological strength index and crack index frameworks for blast fragmentation prediction.
  • Comparative evaluation of RES and ANFIS methodologies for blast fragmentation risk assessment.
  • Research on rock mass drillability indices for estimating drilling rates in surface mines.
  • Integration of geological strength index parameters into vibration attenuation models.
  • Application of quantitative approaches for risk mitigation and operational optimization.

Publications

  • Development and validation of a geological strength index and crack indices based framework for predicting blast-induced rock fragmentation (2026).
  • Vulnerability Index-Based Risk Assessment of Blast Fragmentation: Comparative Analysis of RES and ANFIS Methodologies (2026).
  • A Robust Framework for Blast Fragmentation and Risk Mitigation: A Comparative Analysis (2025).
  • Rock mass classification for estimating the drilling rate in a surface mine using rock mass drillability index (2025).
  • Incorporating the Geological Strength Index into attenuation laws of ground vibration from open-pit bench blasting operations (2025).

Research Impact

The available bibliometric indicators show a developing scholarly profile with seven indexed publications, nineteen citations, and an h-index of two. His research contributes to improving the understanding of geological controls on blasting outcomes and supports evidence-based mining practices. The practical orientation of his work provides value for both academic researchers and industry professionals seeking improved predictive tools.[5]

Award Suitability

Chandrakanta Behera’s contributions align with the objectives of the International Material Scientist Awards through his emphasis on scientific rigor, engineering innovation, and practical applicability. His studies address contemporary challenges in mining and materials-related engineering by integrating geological knowledge with analytical modeling techniques. The publication of his research in internationally recognized journals demonstrates sustained engagement with scholarly advancement and professional dissemination.[6]

Conclusion

The academic record of Chandrakanta Behera reflects a focused contribution to blast engineering, rock mechanics, and mining-related materials research. Through investigations involving geological strength indices, fragmentation prediction, and risk assessment methodologies, he has contributed to the development of analytical tools that support efficient and safer mining operations. These achievements provide a credible basis for recognition under the Innovative Research Award category.[7]

References

  1. Elsevier. (n.d.). Scopus author details: Chandrakanta Behera, Author ID 58986119100. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=58986119100
  2. Behera, C. (2026). Development and validation of a geological strength index and crack indices based framework for predicting blast-induced rock fragmentation.
    DOI: https://doi.org/10.1007/s10064-026-05065-0
  3. Behera, C. (2026). Vulnerability Index-Based Risk Assessment of Blast Fragmentation: Comparative Analysis of RES and ANFIS Methodologies.
    DOI: https://doi.org/10.1007/s42461-025-01425-8
  4. Behera, C. (2025). Rock mass classification for estimating the drilling rate in a surface mine using rock mass drillability index.
    DOI: https://doi.org/10.1080/10916466.2024.2347961
  5. Behera, C. (2025). Incorporating the Geological Strength Index into attenuation law of ground vibration from open pit bench blasting operations.
    DOI: https://doi.org/10.1007/s12665-025-12303-3
  6. International Material Scientist Awards. (n.d.). Award program and recognition criteria.
    materialscientists.com
  7. Behera, C. (2025). A Robust Framework for Blast Fragmentation and Risk Mitigation: A Comparative Analysis.
    DOI: https://doi.org/10.1007/s00603-025-04678-3

Assist. Prof. Dr Xanthoula Eirini Pantazi | Materials Science | Best Researcher Award

Assist. Prof. Dr Xanthoula Eirini Pantazi | Materials Science | Best Researcher Award

🌾 Dr. Xanthoula Eirini Pantazi is an Assistant Professor at Aristotle University of Thessaloniki, specializing in precision agriculture, artificial intelligence, and biosystems engineering. πŸŽ“ She holds a Ph.D. in Biosystems Engineering and has contributed extensively to AI-driven agricultural solutions, machine learning, and sensor fusion. πŸš€ Dr. Pantazi has been involved in 20+ EU-funded projects, including Horizon 2020 initiatives. Her expertise spans decision support systems, UAV applications, and crop monitoring. 🌱 She has received prestigious scholarships and keynote speaker invitations at international conferences. πŸ† Her research continues to advance smart farming and sustainable agriculture. πŸŒπŸ“‘

Assist. Prof. Dr Xanthoula Eirini Pantazi Aristotle University of Thessaloniki, School of Agriculture Greece

Profile

GOOGLE SCHOLAR

SCOPUS

Research Expertise 🌾

Assist. Prof. Dr. Xanthoula Eirini Pantazi is a distinguished researcher in biosystems engineering, holding a Ph.D. in Biosystems Engineering from Aristotle University of Thessaloniki, Greece. πŸ›οΈ Her expertise lies in bio-inspired computational systems, data mining, and artificial intelligence applications in agriculture. πŸŒ±πŸ“Š Over the years, she has contributed to 20+ EU-funded research projects, serving as a coordinator and work package leader in multiple Horizon 2020, PRIMA, and ERANET projects. πŸš€ Dr. Pantazi has also authored 26 scientific papers, 9 book chapters, and the monograph “Intelligent Data Mining and Fusion Systems in Agriculture.” πŸ“–

ExperienceΒ πŸš€

Assist. Prof. Dr. Xanthoula Eirini Pantazi has an extensive academic and research background in precision agriculture and bio-systems engineering. Since 2020, she has been an Assistant Professor at the Faculty of Agriculture, Forestry, and Natural Environment at Aristotle University of Thessaloniki, Greece. πŸ›οΈ From 2016 to 2019, she worked as an Adjunct Lecturer, teaching undergraduate courses in agricultural engineering. πŸ“š Additionally, she served as a Research Engineer and Technical Manager at CERTH (2016-2020) and contributed to major EU-funded research projects as a Research Engineer at Aristotle University (2013-2020). πŸ”¬πŸŒΎ

Scholarly Contributions βœοΈπŸ”¬

Assist. Prof. Dr. Xanthoula Eirini Pantazi has significantly contributed to the field of precision agriculture and artificial intelligence through her numerous book chapters. Her work includes data fusion for soil and crop sensing, leaf disease recognition using machine learning, and hyperspectral sensing for weed and crop differentiation. πŸŒΎπŸ“‘ She has co-authored chapters in Springer and Wageningen Academic Publishers, focusing on AI applications in farming, sustainable agriculture, and bioinformatics. Her expertise in remote sensing, spectral data analysis, and machine learning models has helped develop innovative solutions for smart farming and soil health monitoring. πŸšœπŸ€–

πŸ“‘ Scientific Research πŸ”¬πŸŒΎ

Assist. Prof. Dr. Xanthoula Eirini Pantazi has led and contributed to numerous EU-funded and international research projects in precision agriculture, AI-driven crop monitoring, and smart farming solutions. As a principal investigator and work package leader, she has developed machine learning models for disease detection, decision support systems (DSS) for sustainable farming, and sensor fusion techniques for soil and crop health assessment. πŸš€πŸ“Š Her projects include Horizon 2020 initiatives (AfriCultuReS, SiEUSOIL, ATLAS, STARGATE), ICT-AGRI ERANET, and PRIMA projects. Her work integrates AI, robotics, and IoT-based solutions, advancing climate-resilient and precision-driven agricultural systems. πŸŒπŸ€–

Research Focus πŸ”βœ¨

Assist. Prof. Dr. Xanthoula Eirini Pantazi’s research focuses on applying machine learning, advanced sensing, and data fusion in agriculture πŸŒΎπŸ’». Key areas include crop yield prediction using machine learning and sensing techniques πŸ“ŠπŸŒ±, disease detection in plants through image analysis and spectroscopy πŸ¦ πŸ”¬, and weed recognition using hyperspectral sensing and UAV imagery 🚁🌾. She also works on soil health monitoring and water stress detection using multisensor fusion πŸ’§πŸŒ. Dr. Pantazi’s contributions aim to optimize agricultural practices through innovative technologies, improving sustainability and precision in farming 🌿🚜.

Publications πŸ“š

Forecasting of Fusarium head blight spatial distribution in winter wheat using machine learning
Authors: Morellos, A., Pantazi, X.E., Almoujahed, M.B., Ε arauskis, E., Mouazen, A.M.
Journal: Computers and Electronics in Agriculture (2025)
πŸŒΎπŸ’»

Non-Destructive Quality Estimation Using a Machine Learning-Based Spectroscopic Approach in Kiwifruits
Authors: Tziotzios, G., Pantazi, X.E., Paraskevas, C., Michailidis, M., Molassiotis, A.
Journal: Horticulturae (2024)
πŸ₯πŸ“Š

A Hybrid LSTM Approach for Irrigation Scheduling in Maize Crop
Authors: Dolaptsis, K., Pantazi, X.E., Paraskevas, C., Bustan, D., Mouazen, A.M.
Journal: Agriculture (2024)
πŸŒΎπŸ€–

Application of Machine Learning for Disease Detection Tasks in Olive Trees Using Hyperspectral Data
Authors: Navrozidis, I., Pantazi, X.E., Lagopodi, A., Bochtis, D., Alexandridis, T.K.
Journal: Remote Sensing (2023)
πŸŒΏπŸ’»

Early Detection of Cavitation in Centrifugal Pumps Using Low-Cost Vibration and Sound Sensors
Authors: Karagiovanidis, M., Pantazi, X.E., Papamichail, D., Fragos, V.
Journal: Agriculture (2023)
βš™οΈπŸ”Š