Joyce Mongai Chindong | Remote Sensing in Agriculture and Vegetation | Research Excellence Award

Published on by Applied Scientist

Ms. Joyce Mongai Chindong | Remote Sensing in Agriculture and Vegetation | Research Excellence Award

Mohammed VI Polytechnic University | Morocco

Ms. Joyce Mongai Chindong is an emerging researcher in geospatial sciences whose work centers on leveraging GIS, remote sensing, and machine learning to improve environmental monitoring in data-scarce regions. Her research primarily focuses on soil degradation processes, including drought dynamics and soil salinity, by integrating multi-sensor satellite observations, proximal sensing techniques, and advanced analytical frameworks. She applies Earth Observation data—such as remotely sensed precipitation products, vegetation indices like NDVI, and field-based spectral and electrical conductivity measurements—to quantify environmental anomalies and assess ecosystem responses to climatic variability. Ms. Chindong’s work emphasizes methodological rigor through preprocessing workflows, anomaly detection, spatial modeling, and the use of supervised learning algorithms to generate accurate, scalable predictions of land surface conditions. Her recent contribution, a multi-sensor machine learning framework for field-scale soil salinity mapping, demonstrates her commitment to developing robust, transferrable solutions for sustainable land management, particularly in resource-limited environments where environmental data is sparse. By combining optical, radar, and ground-based measurements with algorithmic modeling, she advances the precision and reliability of landscape-level assessments that support agricultural resilience and environmental planning. Motivated by global sustainability goals, Ms. Chindong aims to refine geospatial intelligence to better understand environmental processes across diverse landscapes. Her interdisciplinary approach—blending geoinformation science, environmental monitoring, and computational methods—positions her as a promising contributor to research on land degradation, climate impacts, and data-driven environmental decision-making.

Profile: Orcid

Featured Publication

Chindong, J. M., Ouzemou, J.-E., Laamrani, A., El Battay, A., Hajaj, S., Rhinane, H., & Chehbouni, A. (2025). A multi-sensor machine learning framework for field-scale soil salinity mapping under data-scarce conditions. Remote Sensing, 17(22), Article 3778.

Zhiguo Meng | Remote Sensing Geology | Research Excellence

Published on by Applied Scientist

Prof. Dr. Zhiguo Meng | Remote Sensing Geology | Research Excellence

Jilin University | China

Prof. Dr. Zhiguo Meng is a prominent lunar remote sensing and planetary geoscience scholar whose research has substantially advanced our understanding of the Moon’s surface processes, thermophysical behavior, and geological evolution, supported by an impressive record of 105 scientific publications, 771 citations from 446 citing documents, and an h-index of 16. His work focuses extensively on analyzing multi-frequency microwave radiometer data, thermal radiation characteristics, and regolith properties derived from China’s Chang’e missions, including CE-2, CE-4, CE-5, and CE-6. Meng has contributed major breakthroughs in constructing global lunar brightness temperature datasets, defining effective brightness temperature differences, and developing innovative techniques to detect subsurface anomalies and assess the thermophysical properties of lunar deposits in regions such as Oceanus Procellarum, Mare Imbrium, Lacus Mortis, and the Schiller–Schickard cryptomare. His research reveals new insights into lunar volcanic evolution, crustal structure, and thermal history by studying crater emissions, lava flows, and regolith heat production rates. Meng is also active in developing advanced computational tools, including deep learning frameworks such as MFBTFF-Net, to estimate lunar surface oxide abundances using Chang’e microwave sounder data. His interdisciplinary contributions extend to planetary formation studies, notably using Chang’e-4 data to examine millimeter-scale particle–surface collisions, and to Earth-based applications, including InSAR-based ground deformation monitoring in mining and earthquake-prone regions. Through extensive collaboration, frequent contributions to leading journals, and advanced modeling of scattering, irradiation, and thermal behavior, Prof. Dr. Meng continues to shape the scientific foundation essential for lunar exploration, mission planning, and future planetary research.

Profiles: Scopus | Orcid

Featured Publications

  • Meng, Z., Mei, L., Liu, C., Xu, Y., Zhang, X., Bugiolacchi, R., Zong, Q., Cheng, W., Ping, J., & Zhang, Y. (2025). Definition of effective brightness temperature difference and its geological significance. IEEE Transactions on Geoscience and Remote Sensing.

  • Li, Z., Zhao, Y., Tang, X., & Meng, Z. (2025). Heat production rate of lunar major basins: New insights into lunar thermal evolution. IEEE Transactions on Geoscience and Remote Sensing.

  • Li, Y., Yuan, Z., Mazhar, S., Meng, Z., Zhang, Y., Ping, J., & Nunziata, F. (2025). MFBTFF‐Net: A multi-frequency brightness temperature feature fusion network for lunar surface oxides abundance estimation using Chang’e-2 data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

  • Chang, W., Meng, Z., Xu, Y., Zhang, X., Bugiolacchi, R., Xiao, L., Ping, J., Zhang, H., & Zhang, Y. (2025). Microwave thermophysical properties of surface deposits in the CE-6 landing region and implications for returned samples. Earth and Planetary Science Letters.

  • Lei, L., Zhang, X., Luo, P., Zhang, G., You, J., Liu, J., Xu, Y., Fu, S., Li, X., & Meng, Z. (2025). Planetary formation constrained by collisions between millimeter-sized lunar particles and the lunar surface from the Chang’E-4 mission. The Astrophysical Journal.

Ranadheer Reddy | Environmental Science | Excellence in Research Award

Published on by Applied Scientist

Mr. Ranadheer Reddy | Environmental Science | Excellence in Research Award

King Mongkut Institute of Technology | Thailand

Mr. Ranadheer Reddy is an emerging researcher whose multidisciplinary work spans geoinformatics, remote sensing, geostatistics, environmental monitoring, public health analytics, and data-driven decision-support systems, supported by a growing academic footprint that includes 6 documents, 15 citations, and an h-index of 3. His publications demonstrate a strong commitment to applying spatial technologies and computational methods to address real-world environmental and societal challenges across India and Southeast Asia. His research on soil erosion estimation and sediment retention in the Lam Phra Phloeng watershed showcases his expertise in watershed assessment and environmental risk modelling, while his recent open-access study on flood mapping and damage assessment during the 2024 Chiang Rai Flood in Thailand highlights his proficiency in leveraging UN-SPIDER-recommended remote sensing methodologies within Google Earth Engine for rapid disaster analysis. Mr. Ranadheer Reddy has also contributed significantly to spatial public health research through a geostatistical analysis of child malnutrition determinants in India, integrating demographic and socio-economic factors to generate policy-relevant insights. His work on spatio-temporal land use and land cover changes in smart cities along the Delhi–Mumbai Industrial Corridor reflects his interest in sustainable urban development and long-term environmental change assessment. Expanding into applied data science, his book chapters explore machine learning approaches for early rice disease diagnosis and big data analytics in the healthcare sector, demonstrating his focus on technological innovation for agricultural resilience, healthcare improvement, and sustainable development. Collectively, his emerging body of work contributes to advancing geospatial intelligence, environmental modelling, and data-driven policy formulation.

Profile: Scopus

Featured Publications

  • Seebonruang, U., Mandadi, R., Thammaboribal, P., Gonzales, A. L., & Bharadwas, G. S. V. S. A. (2025). Estimation of soil erosion and enhancing sediment retention in the Lam Phra Phloeng watershed. Water, 17, 3339.

  • Thammaboribal, P., Tripathi, N., Lipiloet, S., & Mandadi, R. (2025). Flood mapping and damage assessment using UN-SPIDER recommended practices in Google Earth Engine: A case study of the 2024 Chiang Rai Flood, Thailand. International Journal of Geoinformatics, 165–179.

  • Mandadi, R. R., Tripathi, N. K., Pal, I., Mozumder, C., & Gonzales, A. L. (2023). Geostatistical exploratory analysis on child malnutrition and its determinants in India. International Journal of Geoinformatics.

  • Kanchan, A., Nitivattananon, V., Tripathi, N. K., Winijkul, E., & Mandadi, R. R. (2024). A spatio-temporal examination of land use and land cover changes in smart cities of the Delhi–Mumbai Industrial Corridor. Land, 13.

  • Sakhamuri, S., Tatini, N. B., Krishna, P. G., Mandadi, R. R., RajaSekhar, J., Gunnam, L. C., & Teja, K. R. (2025). Machine learning approach to ensure rice nutrition through early diagnosis of rice diseases. In V. Jain, M. Raman, A. Agrawal, M. Hans, & S. Gupta (Eds.), Achieving Sustainability with AI Technologies (pp. 297–310). IGI Global.

Giuseppe Osteria | Cherenkov Camera in Space | Research Excellence Award

Published on by Applied Scientist

Dr. Giuseppe Osteria | Cherenkov Camera in Space | Research Excellence Award

Istituto Nazione di Fisica Nucleare | Italy

Dr. Giuseppe Osteria’s research focuses on advancing astroparticle physics with a strong emphasis on high-precision measurements of cosmic radiation using space-based and balloon-borne detectors. With a citation record of 19,296 citations, an h-index of 63, and an i10-index of 193 (with 5,131 citations, h-index 34, and i10-index 99 since 2020), his work has significantly shaped the field. Over the past 25 years, he has contributed extensively to major international experiments aimed at understanding the composition, origin, and propagation of cosmic rays, antimatter components, and high-energy astrophysical phenomena. His scientific contributions span the MACRO experiment, which provided foundational insights into atmospheric neutrinos and underground muon fluxes, as well as the MINISINGAO/ARGO and NOE/ICANOE projects investigating cosmic-ray interactions and neutrino behavior. A major portion of his career is linked to the WIZARD-PAMELA mission, where his leadership in time-of-flight systems, trigger development, and light-nuclei data analysis enabled groundbreaking results, including the discovery of anomalous positron abundance and precise measurements of proton, helium, electron, positron, and antiproton spectra. Dr. Osteria has also played central roles in the JEM-EUSO program, contributing to the advancement of space-based detection of extreme-energy cosmic rays and serving as an international data processor and operations manager for missions such as EUSO-Balloon, TA-EUSO, and MINI-EUSO. His work extends to next-generation missions—SPB2, PBR, CSES-Limadou, GAPS, and HERD-DMP—where he has overseen instrumentation, trigger electronics, calorimetry systems, and high-level data processing. Collectively, his research drives progress in cosmic-ray physics, antimatter studies, and multi-messenger astrophysics, positioning him as a leading contributor to space-borne astroparticle research.

Profiles: Google Scholar | Orcid | Scopus

Featured Publications

  • Adriani, O., Barbarino, G. C., Bazilevskaya, G. A., Bellotti, R., Boezio, M., et al. (2009). An anomalous positron abundance in cosmic rays with energies 1.5–100 GeV. Nature, 458(7238), 607–609.

  • Adriani, O., Barbarino, G. C., Bazilevskaya, G. A., Bellotti, R., Boezio, M., et al. (2011). PAMELA measurements of cosmic-ray proton and helium spectra. Science, 332(6025), 69–72.

  • Adriani, O., Barbarino, G. C., Bazilevskaya, G. A., Bellotti, R., Boezio, M., et al. (2010). PAMELA results on the cosmic-ray antiproton flux from 60 MeV to 180 GeV in kinetic energy. Physical Review Letters, 105(12), 121101.

  • Picozza, P., Galper, A. M., Castellini, G., Adriani, O., Altamura, F., Ambriola, M., … Barbarino, G. C. (2007). PAMELA–A payload for antimatter matter exploration and light-nuclei astrophysics. Astroparticle Physics, 27(4), 296–315.

  • Ambrosio, M., Antolini, R., Aramo, C., Auriemma, G., Baldini, A., Barbarino, G. C., … MACRO Collaboration. (1998). Measurement of the atmospheric neutrino-induced upgoing muon flux using MACRO. Physics Letters B, 434(3–4), 451–457.

M. R. Rajan | Nanoparticles | Excellence in Research Award

Published on by Applied Scientist

Prof. Dr. M. R. Rajan | Nanoparticles | Excellence in Research Award

The Gandhigram Rural Institute- Deemed to be University | India

Prof. Dr. M. R. Rajan is a distinguished researcher whose work spans aquaculture toxicology, green nanotechnology, environmental biotechnology, and fish health management. His research primarily explores the synthesis, characterization, and safe application of diverse metal and metal oxide nanoparticles—including selenium, silver, copper oxide, manganese oxide, magnesium oxide, chromium oxide, aluminum oxide, zinc oxide, carbon quantum dots, and graphene quantum dots—and their physiological impacts on numerous freshwater fish species. A major focus of his work is the incorporation of nanoparticles into fish diets to enhance growth performance, haematological and biochemical responses, antioxidant activity, and overall aquatic health, helping advance the emerging field of nanonutrition. He contributes significantly to the development of green-synthesized nanoparticles using plant extracts and waste-derived materials, assessing their antibacterial, larvicidal, and biomedical potentials, as well as their suitability for aquaculture applications. His studies also address key environmental challenges, including wastewater toxicity, tannery effluent pollution, and eco-friendly remediation strategies, while other works explore the role of probiotic gut microbiota in improving fish immunity and disease resistance. With 44 scientific publications and more than 220 citations, Prof. Dr. M. R. Rajan research offers valuable insights into sustainable aquaculture practices, nanoparticle biosafety, environmental health, and innovative nanobiotechnological solutions for aquatic systems.

Profile: Scopus

Featured Publications

  • Varghese Edwin Hillary, V., Dayana Senthamarai, M., Antony Ceasar, A., Ignacimuthu, S., & Rajan, M. R. (2025). Characterization of a silver nanoparticle derived from the fruit peel of Myristica fragrans on mosquito control. International Journal of Tropical Insect Science.

  • Dayana Senthamarai, M., Edwin Hillary, V., Rajan, M. R., & Antony Ceasar, A. (2025). Phyto-synthesis of selenium nanoparticles using Mentha spicata extract and its larvicidal and antibacterial activities. Journal of Asia-Pacific Entomology, 28(1), 102370.

  • Malavika, V., Rajan, M. R., Soundhariya, N., Prethika, J., & Chandrakala, V. (2025). Comparative evaluation of chemically and green-synthesised carbon quantum dots for aquatic applications. Journal of Environmental Nanotechnology, 14(3), 505–515.

  • Chinnadurai Kaleeswaran, M., Dayana Senthamarai, M., & Rajan, M. R. (2024). Evaluation of disparate multiplicities of copper oxide nanoparticles integrated feed on the growth and hematology of koi carp. Journal of Toxicological Studies, 2(1), 497.

  • Dayana Senthamarai, M., Rekha, M., & Rajan, M. R. (2024). Incorporation of nano selenium in fish diet and assessment of growth performance and biochemical criteria of Labeo rohita. Journal of Environmental Nanotechnology, 13(1), 01–09.*

 

Shoresh Shokoohi | Fault Detection | Editorial Board Member

Published on by Applied Scientist

Dr. Shoresh Shokoohi | Fault Detection | Editorial Board Member

University of Kurdistan | Iran

Dr. Shoresh Shokoohi is a distinguished researcher in power systems, smart microgrids, intelligent control, and condition monitoring, with a strong focus on advanced control strategies for voltage, frequency, and stability enhancement in inverter-based microgrids. His research emphasizes intelligent, data-driven, and model-based approaches—including fuzzy logic controllers, ANN-based self-tuning schemes, neuro-fuzzy systems, and optimization-based droop control—to ensure resilient, reliable, and autonomous operation of microgrids under dynamic conditions. Dr. Shokoohi has made notable contributions to intelligent secondary control, transient stability enhancement, load-frequency control, and robust online tuning methods, publishing influential works in top-tier journals such as IEEE Transactions on Smart Grid, International Journal of Electrical Power & Energy Systems, Electric Power Components and Systems, Optimization and Engineering, and Neural Computing & Applications. Extending beyond microgrid control, he has advanced the field of electric machine diagnostics through innovative model-based techniques, such as Luenberger observer–based fault detection, parity-equation methods, and current-noise cancellation for accurate bearing fault diagnosis. His interdisciplinary work integrates artificial intelligence, optimization algorithms, and intelligent control applications to address emerging challenges in smart grid reliability and inverter-based distributed generation. With a strong publication record across journals and conferences, Dr. Shoresh Shokoohi research continues to support the evolution of next-generation smart grids, providing practical, intelligent, and robust solutions that enhance the performance, stability, and resilience of modern power and energy systems.

Profile: Google Scholar

Featured Publications

  • Bevrani, H., & Shokoohi, S. (2013). An intelligent droop control for simultaneous voltage and frequency regulation in islanded microgrids. IEEE Transactions on Smart Grid, 4(3), 1505–1513.

  • Ahmadi, S., Shokoohi, S., & Bevrani, H. (2015). A fuzzy logic-based droop control for simultaneous voltage and frequency regulation in an AC microgrid. International Journal of Electrical Power & Energy Systems, 64, 148–155.

  • Bevrani, H., Habibi, F., & Shokoohi, S. (2013). ANN-based self-tuning frequency control design for an isolated microgrid. In Meta-heuristics Optimization Algorithms in Engineering, Business, Economics.

  • Khezri, R., Golshannavaz, S., Shokoohi, S., & Bevrani, H. (2016). Fuzzy logic-based fine-tuning approach for robust load frequency control in a multi-area power system. Electric Power Components and Systems, 44(18), 2073–2083.

  • Shokoohi, S., Golshannavaz, S., Khezri, R., & Bevrani, H. (2018). Intelligent secondary control in smart microgrids: An on-line approach for islanded operations. Optimization and Engineering, 19(4), 917–936.

Abdiqani Hassan | Sustainable Management | Editorial Board Member

Published on by Applied Scientist

Dr. Abdiqani Hassan | Sustainable Management | Editorial Board Member

University of Hargeisa | Somalia

Dr. Abdiqani Hassan is a prolific researcher in management, sustainability, green supply chain systems, and decision-support models, with impactful contributions to sustainable construction and circular economy transitions in Somaliland and across Asia. With 260 citations, an h-index of 8, and an i10-index of 7, his work demonstrates strong scholarly influence and growing global recognition. Dr. Abdiqani Hassan research focuses on construction and demolition waste management, digital transformation barriers, sustainable supply chain finance, and governance frameworks that enhance environmental and operational performance. He publishes extensively in high-quality international journals including the Journal of Cleaner Production, Environmental Science and Pollution Research, Journal of Construction Engineering and Management, Ain Shams Engineering Journal, Sustainability, and Results in Engineering. His cited work examines regulatory barriers in sustainable construction waste management, project success under uncertainty, causal frameworks for natural rubber sustainability, and behavioral determinants of household waste separation. His recent studies highlight cooperative governance mechanisms, digital enablement, and value innovation as critical drivers of digital and sustainable transformation in construction and supply chain sectors. Dr. Abdiqani Hassan has secured notable research grants from the University of Hargeisa and Taiwan’s Ministry of Science and Technology, supporting projects on smart circular product–service systems, green reliability design, and sustainable supply chain management. He actively shares his findings at leading academic conferences in Malaysia, Thailand, Indonesia, and Djibouti, contributing to global discussions on sustainability, digitalization, and resilient management systems. Overall, Dr. Abdiqani Hassan research advances data-driven, governance-oriented, and context-appropriate solutions that improve sustainability, efficiency, and strategic decision-making across construction and environmental management fields.

Profile: Google Scholar 

Featured Publications

  • Negash, Y. T., Hassan, A. M., Tseng, M. L., Wu, K. J., & Ali, M. H. (2021). Sustainable construction and demolition waste management in Somaliland: Regulatory barriers lead to technical and environmental barriers. Journal of Cleaner Production, 297, 126717.

  • Negash, Y. T., & Hassan, A. M. (2020). Construction project success under uncertainty: Interrelations among the external environment, intellectual capital, and project attributes. Journal of Construction Engineering and Management, 146(10), 05020012.

  • Hassan, A. M., Negash, Y. T., & Hanum, F. (2024). An assessment of barriers to digital transformation in circular construction: An application of stakeholder theory. Ain Shams Engineering Journal, 15(7), 102787.

  • Shirwa, A. M., Hassan, A. M., Hassan, A. Q., & Kilinc, M. (2025). A cooperative governance framework for sustainable digital transformation in construction: The role of digital enablement and digital strategy. Results in Engineering, 25, 104139.

  • Negash, Y. T., Sriplod, T., & Hassan, A. M. (2021). A causal sustainable natural rubber development framework using a hierarchical structure with linguistic preferences in Thailand. Journal of Cleaner Production, 305, 127095.

 

Mohamed Moustafa | Nuclear energy | Editorial Board Member

Published on by Applied Scientist

Dr. Mohamed Moustafa | Nuclear Energy | Editorial Board Member

Harbin Engineering Unversity | Egypt

Dr. Mohamed Moustafa is a dedicated researcher in nuclear engineering and thermal hydraulics, with a strong focus on multiphase flow behavior, water film dynamics, and advanced diagnostic techniques essential for improving heat transfer and safety in nuclear systems. His work spans experimental analysis, numerical simulation, and machine learning applications, offering a comprehensive approach to understanding gas–liquid interactions and thin-film behaviors under various operating conditions. Dr. Mohamed Moustafa has made notable contributions through the use of Planar Laser-Induced Fluorescence (PLIF) to study wavy water films on horizontal plates and within horizontal rectangular ducts, generating high-resolution insights into film instabilities, flow distribution, and interfacial behavior. He has also pioneered the integration of artificial intelligence into thermal-hydraulic research by employing artificial neural networks and deep convolutional neural networks for predicting wavy film characteristics and classifying critical water-film images. His publications, presented in reputable journals and international conferences, include work on numerical simulation of spent fuel pools using shell-and-tube heat exchangers, PLIF-based characterization of gas–liquid films, and state-of-the-art reviews on water-film properties. Dr. Mohamed Moustafa research aims to enhance cooling performance, improve thermal-hydraulic predictive capabilities, and strengthen safety analyses within nuclear engineering. By combining experimental rigor, computational modeling, and data-driven techniques, he continues to advance scientific understanding of complex thermal-hydraulic phenomena and contribute meaningful solutions for modern nuclear reactor design and operation.

Profile: Google Scholar

Featured Publications

  • Moustafa, M. (2015). Numerical simulation of spent fuel pool using shell and tube heat exchanger. International Journal of Engineering and Technology Research, 869(12), 96–104.

  • Mohamed, M., Ruifeng, T., Bo, W., Wen, J., Ullah, A., & Mohamad, H. A. E. (2023). A detailed experimental evaluation of gas–liquid film attributes in a horizontal rectangular duct by Planar Laser-Induced Fluorescence (PLIF) approach. Nuclear Engineering and Design, 408, 112331.

  • Mohamed, M., Ruifeng, T., Wen, J., Bo, W., Ullah, A., Alm ElDin Mohamad, H., & Cheng, H. (2024). Modeling of wavy water film by application of artificial neural network: A state of art study. Nuclear Engineering and Design, 417, 112731.

  • Mohamed, M., Ruifeng, T., & Renteria, F. (2019). Classification of water film critical images using deep convolutional neural networks. In Proceedings of the 2nd International Conference on Algorithms, Computing and Artificial Intelligence (pp. 225–229). Association for Computing Machinery.

  • Mohamed, M., & Ruifeng, T. (2019). Review paper on water film characteristics. In Proceedings of the 18th International Topical Meeting on Nuclear Reactor Thermal Hydraulics (NURETH 2019) (pp. 5616–5630).

Taşkın Deniz Yıldız | Mining Engineering | Editorial Board Member

Published on by Applied Scientist

Assoc. Prof. Dr. Taşkın Deniz Yıldız | Mining Engineering | Editorial Board Member

Adana Alparslan Türkeş Science and Technology University | Turkey

Assoc. Prof. Dr. Taşkın Deniz Yıldız is a leading researcher in mining engineering whose work focuses on the economic, environmental, and regulatory dimensions of mining activities in Turkey, with special emphasis on sustainable resource management and policy impacts. His research extensively examines how legislation, permit procedures, land-use constraints, and waste regulations shape the operational, financial, and ecological outcomes of mining enterprises. A significant portion of his scholarly contributions addresses the rising importance of waste management in mining, analyzing waste management costs, recovery potential, and the implications of EU-compliant waste regulations for the Turkish mining sector. He has produced influential studies on the effects of Environmental Impact Assessment (EIA) procedures, mining operation permits, forestland-use fees, agricultural land restrictions, and private land acquisition costs, offering data-driven evaluations that reveal the challenges mining companies face in regulatory environments. His work also investigates the financial burdens associated with state rights, forest fees, and overlapping infrastructure investments, highlighting how these factors influence overall investment decisions and sector competitiveness. Additionally, Dr. Yıldız contributes to land-use planning research by analyzing conflicts between mining activities and agricultural zones, olive groves, pastures, and forest areas, proposing policy reforms that balance environmental protection with the strategic importance of mineral extraction. His recent studies extend toward the sustainability potential of mineral recovery from tailings and urban mining wastes, positioning waste valorization as a key component of circular economy strategies. Overall, Dr. Yıldız’s research provides comprehensive, practical insights that support more effective, equitable, and sustainable mining governance.

Profiles: Google Scholar | Orcid

Featured Publications

  • Yıldız, T. D. (2020). Waste management costs (WMC) of mining companies in Turkey: Can waste recovery help meeting these costs? Resources Policy, 68, 101706.

  • Yıldız, T. D. (2020). Evaluation of forestland use in mining operation activities in Turkey in terms of sustainable natural resources. Land Use Policy, 96.

  • Yıldız, T. D. (2020). Effects of the private land acquisition process and costs on mining enterprises before mining operation activities in Turkey. Land Use Policy, 97.

  • Yıldız, T. D. (2020). The impacts of EIA procedure on the mining sector in the permit process of mining operating activities: Turkey analysis. Resources Policy, 67.

  • Yıldız, T. D. (2019). The share of required costs in investment amounts for mining operating activities in pasture lands in Turkey. Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi.

Thi Huynh Anh Le | Smart Grid | Editorial Board Member

Published on by Applied Scientist

Dr. Thi Huynh Anh Le | Smart Grid | Editorial Board Member

The university of Danang, University of Science and Technology | Vietnam

Dr. Le Thi Huynh Anh is a rising researcher in renewable energy systems whose work has gained notable scholarly impact, reflected in 104 citations, an h-index of 5, and an i10-index of 4. Her research centers on sustainable microgrid design, peer-to-peer (P2P) energy trading, uncertainty modeling, and computational intelligence for optimizing modern power systems. She has published influential studies in leading journals such as Renewable and Sustainable Energy Reviews, Renewable Energy, Expert Systems with Applications, and Applied Sciences. Dr. Anh’s contributions emphasize advanced multi-microgrid planning frameworks that integrate seasonal demand patterns, government subsidies, stochastic uncertainties, and digital technologies to enhance economic, operational, and environmental performance. Her collaborative works on blockchain-enabled P2P energy trading propose innovative pathways for decentralized and consumer-centric energy markets. Alongside system optimization, she has developed intelligent methodologies for improving data quality and decision-making in energy systems, including dynamic-programming-based time-series anomaly detection using the longest common subsequence approach, as well as advanced clustering techniques that blend fuzzy logic, possibilistic modeling, and genetic algorithms for handling mixed data types. Her research also extends to maintenance optimization for offshore wind systems, demonstrating a broader commitment to the renewable energy ecosystem. Across her body of work, Dr. Anh integrates sustainability principles, AI-driven modeling, and robust optimization techniques to support the development of next-generation, resilient, and intelligent energy infrastructures. Her recent studies continue advancing sustainable multi-microgrid systems by addressing the challenges of uncertainty, seasonality, and evolving energy trading mechanisms.

Profile: Google Scholar

Featured Publications

  • Vincent, F. Y., Le, T. H. A., & Gupta, J. N. D. (2022). Sustainable microgrid design with multiple demand areas and peer-to-peer energy trading involving seasonal factors and uncertainties. Renewable and Sustainable Energy Reviews, 161, 112342.

  • Nguyen, T. P. Q., Phuc, P. N. K., Yang, C. L., Sutrisno, H., Luong, B. H., Le, T. H. A., … (2023). Time-series anomaly detection using dynamic programming based longest common subsequence on sensor data. Expert Systems with Applications, 213, 118902.

  • Yu, V. F., Chiang, F. Y., Le, T. H. A., & Lin, S. W. (2022). Using the ISM method to analyze the relationships between various contractor prequalification criteria. Applied Sciences, 12(8), 3726.

  • Vincent, F. Y., Le, T. H. A., & Gupta, J. N. D. (2023). Sustainable microgrid design with peer-to-peer energy trading involving government subsidies and uncertainties. Renewable Energy, 206, 658–675.

  • Nguyen, T. P. Q., Kuo, R. J., Le, M. D., Nguyen, T. C., & Le, T. H. A. (2022). Local search genetic algorithm-based possibilistic weighted fuzzy c-means for clustering mixed numerical and categorical data. Neural Computing and Applications, 34(20), 18059–18074.