Prof. Dr. Rodolfo Ariel Perez | Experimental Methods | Best Research Article Award

Published on by Global Energy Awards

Prof. Dr. Rodolfo Ariel Perez | Experimental Methods | Best Research Article Award

National Atomic Energy Commission | Argentina

Prof. Dr. Rodolfo Ariel Perez is a researcher at CNEA and an Independent Researcher within CONICET, as well as an Adjunct Professor at UNSAM. He works at the Centro Atómico Constituyentes in the Materials Division, specializing in diffusion processes and materials science. He holds degrees in Physics and has completed advanced postgraduate training in metallurgy, materials technology, thin film techniques, ceramics, and diffusion studies across several international institutions in Europe, Asia, and South America. He has supervised numerous undergraduate, master’s, and doctoral theses in the field of materials science, particularly diffusion phenomena in metals, alloys, and nuclear-related materials. His academic activity includes more than sixty conference presentations in major scientific events. He has also served as a jury member for theses, participated in academic committees, and contributed to scientific advisory boards. He is proficient in English, Portuguese, and French, and his experimental expertise includes techniques such as Laser Induced Breakdown Spectroscopy.

Featured Publications

Perez, R. A., & Gomez Sanchez, Y. P. (2025). How to address self-absorption in LIBS using millisecond time-width detectors. Spectrochimica Acta Part B: Atomic Spectroscopy.

Gaviola, P. A., Sallese, M., Suarez Anzorena, M., Ararat Ibarguen, C. E., Bertolo, A. A., Iribarren, M., Perez, R., Morel, E., Torga, J., Kreiner, A. J., & del Grosso, M. F. (2021). Development of a simple method based on LIBS for evaluation of neutron production targets made of hydrogen isotopes. Measurement: Journal of the International Measurement Confederation.

Ararat-Ibarguen, C. E., Lucia, A., Corvalan, C., Di Lalla, N., Iribarren, M. J., Rinaldi, C. A., & Pérez, R. (2020). Laser induced breakdown spectroscopy application to reaction-diffusion studies in nuclear materials. Spectrochimica Acta Part B: Atomic Spectroscopy.

Perez, R. A., Ararat-Ibarguen, C., & Iribarren, M. (2020). H diffusion in excel measured by LIBS. Journal of Nuclear Materials.

Dr. Bapun Barik | Materials for Energy | Best Researcher Award

Published on by Global Energy Awards

Dr. Bapun Barik | Materials for Energy | Best Researcher Award

Econain Co. Ltd | South Korea

Dr. Bapun Barik is a scientist and innovator specializing in advanced materials for environment and energy technologies. His expertise includes designing, synthesizing, and characterizing organic, inorganic, and polymeric composite materials for applications such as fuel cells, electrocatalysis, water purification, heterogeneous catalysis, heavy metal adsorption, photocatalysis, and sensor development. He has led projects on PEMFC electrolytes, regenerative fuel cell components, and membrane electrode assembly, contributing to patent filings and publications. He also collaborates on catalyst development, electrolyte optimization, and stack fabrication for hydrogen energy systems. Dr. Barik is skilled in advanced instrumentation, electrochemical analysis, and technical software tools, with strong leadership experience in managing research teams, confidential projects, proposal writing, and mentoring students.

Barik, B., Kasbe, A., Oh, S. J., & Moon, S. H. (2025). A two-way synergistic approach to boost proton transfer and chemical durability in polymer electrolyte membrane fuel cells. Chemical Engineering Journal, 520, 165796.

Lilly, K., Agrawal, A., Barik, B., Gugulothu, S. B., Rath, S. N., Oh, S. J., & Joshi, A. (2025). Toward next-generation therapies for intrauterine adhesions: A perspective on granular hydrogel systems. Journal of Materials Chemistry B.

Barik, B., & Rout, L. (2025). Graphene–metal oxide-based hybrid materials for fuel cell applications. In Graphene–Metal Oxide Composites: Synthesis, Properties, and Applications (Chapter 17).

Rout, V., Barik, B., Panda, D. K., Subudhi, S., Mohapatra, A., Sharma, R. K., & Dash, P. (2024). Grafting of CuCo alloy nanoparticles on g-C3N4 sheet: An efficient strategy for solar-driven photocatalytic degradation of ibuprofen and H₂ gas evolution by water splitting. Industrial & Engineering Chemistry Research, 63(18), 8054–8075.

Priyadarsini, P., Barik, D., & Barik, B. (2024). Plastic pollution and associated emerging contaminant across Indian subcontinent river catchments: A grave concern of anthropogenic epoch. In River Basin Ecohydrology in the Indian Sub-Continent (pp. 169–181).

Dr. Safaa Hriez | Spatio-Temporal Analysis | Research Excellence Award

Published on by Global Energy Awards

Dr. Safaa Hriez | Spatio-Temporal Analysis | Research Excellence Award

Al Hussein Technical University | Jordan

Dr. SAFAA HRIEZ is an experienced academic professional working as an Assistant Professor with expertise in Security, Secure Coding, Computing Research, Networking, Forensics, Data Structures, Algorithms, Object-Oriented Programming, Database Systems, Operating Systems, and Deep Learning. She has delivered both theoretical and practical courses across multiple universities and training programs, consistently achieving high student evaluations. Her teaching experience spans on-campus and online platforms including Zoom and Microsoft Teams, and she has contributed to various institutional committees such as ABET, Scientific Research and Conferences, Graduation Projects, Practical Training, and Library Committees. She is proficient in multiple programming languages including Python, C, C++, C#, Java, MATLAB, PHP, Android, HTML, CSS, JavaScript, Visual Basic, Oracle, and MySQL, with hands-on experience in Linux and Windows operating systems. Her data science profile includes working with TensorFlow, Scikit-learn, Pandas, Matplotlib, and Numpy, alongside practical knowledge of machine learning fundamentals, linear and logistic regression, clustering, ensemble methods, probabilistic models, neural networks, CNNs, and RNNs for real-world applications. She is also certified in AI and possesses strong digital security expertise with tools such as FTK, Autopsy, Wireshark, Metasploit, and Immunity Debugger, covering offensive and defensive security techniques, network forensics, database security, memory corruption, web application attacks, and automation of security tasks. Her technical strengths also extend to data analysis techniques, including spatio-temporal analysis.

Hriez, S., & Hmidan, M. (2025). Energy-saving potentials in high-temperature data centers: A spatio-temporal analysis. Results in Engineering, 108–138.

Hriez, S. (2025). Face swap detection: A systematic literature review. IEEE Access.

Hriez, S., & Hmidan, M. (2025). Temperature forecasting for high-temperature data centers: Enhancing energy efficiency through predictive modeling. In 2025 12th International Conference on Information Technology (ICIT).

Hriez, S., Almajali, S., Elgala, H., Ayyash, M., & Salameh, H. B. (2021). A novel trust-aware and energy-aware clustering method that uses stochastic fractal search in IoT-enabled wireless sensor networks. IEEE Systems Journal.

Al Gharaibeh, R. S., Ali, M. Z., Daoud, M. I., Alazrai, R., AbdelNabi, H., Hriez, S., & Suganthan, P. N. (2021). Real parameter constrained optimization using enhanced quality-based cultural algorithm with novel influence and selection schemes. Information Sciences.

Dr. Laura Xiomara Gutierrez Guerrero | Hadronic Physics | Women Researcher Award

Published on by Global Energy Awards

Dr. Laura Xiomara Gutierrez Guerrero | Hadronic Physics | Women Researcher Award

Mesoamerican Centre for Theoretical Physics | Mexico

Dr. Laura Xiomara Gutiérrez Guerrero is currently an Investigadora por México at the Mesoamerican Centre for Theoretical Physics (MCTP) in Tuxtla Gutiérrez, Chiapas. Her work has been distinguished through multiple recognitions at both the National System of Researchers in Mexico and the State System of Researchers in Chiapas, along with active participation in editorial committees, academic coordination programs, and scientific events. She has supervised numerous research theses in the areas of QCD, hadronic physics, and particle phenomenology, guiding students from multiple universities across Mexico and Central America. Her research collaborations include scientific visits to national and international institutes, and her academic leadership extends to organizing and coordinating physics education programs and scientific Olympiads. Additionally, she has been an active referee and evaluator for scientific journals, research programs, academic competitions, and national scientific project evaluations. Her core research areas focus on high-energy physics and hadronic physics.

García-Muñoz, J. D., Alfaro, A., Gutiérrez-Guerrero, L. X., & Raya, A. (2025). Dynamical mass generation in QED: Miransky scaling and Schrödinger-like infinite well and barrier potentials supporting a bound state. Few-Body Systems.

Ramírez-Garrido, M. A., Hernández-Pinto, R. J., Higuera-Angulo, I. M., & Gutiérrez-Guerrero, L. X. (2025). Screening masses for scalar and pseudoscalar mesons and their diquark partners: Insights from the contact interaction model. Physical Review D.

Paredes-Torres, G., Gutiérrez-Guerrero, L. X., Bashir, A., & Miramontes, Á. S. (2024). First radial excitations of mesons and diquarks in a contact interaction. Physical Review D.

Alfaro, J. A., Gutiérrez-Guerrero, L. X., Albino, L., & Raya, A. (2024). Perturbative analysis of the three gluon vertex in different gauges at one-loop. Few-Body Systems.

Hernández-Pinto, R. J., Gutiérrez-Guerrero, L. X., Bedolla, M. A., & Bashir, A. (2024). Electric, magnetic, and quadrupole form factors and charge radii of vector mesons: From light to heavy sectors in a contact interaction. Physical Review D.

Dr. Gehad Metwally | Sustainable Materials | Best Researcher Award

Published on by Global Energy Awards

Dr. Gehad Metwally | Sustainable Materials | Best Researcher Award

Obour Higher Institute for Engineering and Technology | Egypt

Dr. Gehad Ahmed Metwally is a civil engineering researcher focused on developing environmentally friendly and sustainable construction solutions that reduce carbon dioxide emissions. His work explores the use of bacteria in concrete to create self-healing bio-concrete, investigates the behavior and mechanical properties of fresh and hardened concrete using various materials, and examines the incorporation of natural and waste materials to minimize cement usage for lower CO₂ emissions. He also studies geopolymer concrete using fly ash, ground-granulated slag, and metakaolin combined with fibres such as steel and glass to achieve more resilient built environments. In his research role, he is responsible for data collection, reviewing recent literature, planning research, designing experimental mixtures, and performing tests to achieve optimal results, in addition to contributing to academic supervision. He has teaching experience in multiple civil engineering subjects and is skilled in SAP2000, ETABS, SAFE, AutoCAD, quantity surveying, and ICDL. His research contributions have been recognized with an appreciation certificate from the Dean of the Faculty of Engineering for publications in Q1 and Q2 scientific journals.

Metwally, G. A. M., Elemam, W. E., Mahdy, M., & Ghannam, M. (2025). Metakaolin-based ultra-high-performance geopolymer concrete: Role of basalt, glass, granite, and marble waste powders. Innovative Infrastructure Solutions, 10(11), 527.

Metwally, G. A. M., Elemam, W. E., Mahdy, M., & Ghannam, M. (2025). A comprehensive review of metakaolin-based ultra-high-performance geopolymer concrete enhanced with waste material additives. Journal of Building Engineering, 103, 112019.

Metwally, G. A. M., Mahdy, M., & Abd El-Raheem, A. E.-R. H. (2020). Performance of bio concrete by using Bacillus pasteurii bacteria. Civil Engineering Journal, 6(8), 1443–1456.

Prof. Dr. Andras Bardossy | Spatial Statistics | Excellence in Research Award

Published on by Global Energy Awards

Prof. Dr. Andras Bardossy | Spatial Statistics | Excellence in Research Award

University of Stuttgart | Germany

Prof. Dr. András Bardossy is a distinguished expert in hydrology with research contributions spanning stochastic hydrology, geostatistics, surface and subsurface hydrology, hydroclimatology, climate change, and fuzzy computations. His professional career includes leading academic and research roles in prominent international institutions, focusing on hydrology, geohydrology, and water management. He has conducted extensive research in precipitation modeling, GCM downscaling, regionalization of hydrological models and parameters, groundwater and soil moisture evaluation, infiltration modeling, and environmental decision-making under uncertainty. His work further covers groundwater pollution modeling, multivariate statistical modeling, sediment transport, water quality analysis, and geostatistical investigation of environmental systems. Prof. Bardossy has held honorary and invited professorships at several globally recognized universities and has supervised 56 PhD scholars, with a strong publication record comprising 231 scientific papers. His core expertise also includes spatial statistics and advanced data analysis techniques.

Baste, S., Klotz, D., Acuña Espinoza, E., Bardossy, A., & Loritz, R. (2025). Unveiling the limits of deep learning models in hydrological extrapolation tasks. Hydrology and Earth System Sciences, 29(21), 5871–5891.

Zhang, Q., Zhang, K., Bárdossy, A., Li, Y., & Wu, N. (2025). Improving representation of hydrological process heterogeneity in grid-Xin’anjiang model through a stepwise approach. Journal of Hydrology, 655, 132897.

El Hachem, A., Seidel, J., & Bárdossy, A. (2025). Probabilistic downscaling of EURO-CORDEX precipitation data for the assessment of future areal precipitation extremes for hourly to daily durations. Hydrology and Earth System Sciences.

Hörning, S., & Bárdossy, A. (2025). Simulation of conditional non-Gaussian random fields with directional asymmetry. Spatial Statistics, 65, 100872.

El Hachem, A., Seidel, J., O'Hara, T., Villalobos Herrera, R., Overeem, A., Uijlenhoet, R., Bárdossy, A., & de Vos, L. (2024). Technical note: A guide to using three open-source quality control algorithms for rainfall data from personal weather stations. Hydrology and Earth System Sciences.

Dr. Abdolreza Farhadian | Flow Assurance | Excellence in Research Award

Published on by Global Energy Awards

Dr. Abdolreza Farhadian | Flow Assurance | Excellence in Research Award

Kazan Federal University | Russia

Dr. Abdolreza Farhadian is a leading researcher in the oil and gas field, specializing in the development of environmentally friendly and advanced classes of kinetic hydrate inhibitors, anti-agglomerants, and corrosion inhibitors. His work focuses on hybrid inhibition strategies to simultaneously manage hydrate formation and corrosion challenges while overcoming compatibility issues between conventional inhibitors. He is also actively engaged in designing innovative kinetic hydrate promoters to enhance natural gas storage and transportation, along with carbon dioxide sequestration via clathrate hydrates. His research further extends to the development of oil-soluble catalysts and surfactants for heavy oil aquathermolysis, contributing to improved recovery efficiency. Dr. Farhadian has held progressive research leadership roles at Kazan Federal University and currently leads a joint research laboratory in collaboration with Dalian University of Technology. He has been a key contributor to multiple major industrial and government-supported projects and has received international recognitions including Top 2% Scientist rankings and multiple advisory and editorial board appointments. His broader research interests encompass gas storage, flow assurance, CO₂ capture, hydrogen storage, corrosion inhibition, biomaterials synthesis, water desalination, and enhanced oil recovery.

Chen, Z., Farhadian, A., Sadeh, E., Chen, C., & Striolo, A. (2025). Counterion-dependent promotion of methane hydrate formation by anionic biosurfactants: A molecular perspective for efficient gas storage. Chemical Engineering Journal, 170846.

Zhang, Y., Qiang, Y., Zhang, W., Ramakrishna, S., Farhadian, A., & Jin, Y. (2025). Formation of a green protective layer by symmetric imidazolium-based ionic liquids for metal corrosion inhibition: Interfacial adsorption and mechanistic insights. Colloids and Surfaces A: Physicochemical and Engineering Aspects, 723, 137299.

Chen, Z., Farhadian, A., Sadeh, E., & Chen, C. (2025). Micellization effects in surfactant-enhanced gas hydrate formation for efficient solidified methane storage. Energy, 332, 137088.

Sadeh, E., Liu, Y., Farhadian, A., Semenov, M. E., & Mohammadi, A. (2025). Impact of hydroxyl group in surfactant structure on methane hydrate formation, pelletization, and dissociation for advanced transportable methane pellets. Journal of Colloid and Interface Science, 690, 137306.

Liu, Y., Farhadian, A., Chen, C., Chen, Z., Chen, X., Yang, L., & Wang, H. (2025). Molecular dynamics insights into surfactant-regulated methane hydrate nucleation and growth: Comparative roles of sodium oleate and hydroxylated sodium oleate. Crystal Growth & Design, 25(12), 4426–4440.

Prof. Steven Dufour | Fluid Mechanics | Best Researcher Award

Published on by Global Energy Awards

Prof. Steven Dufour | Fluid Mechanics | Best Researcher Award

Polytechnique Montreal | Canada

Prof. Steven Dufour is a distinguished faculty member at École Polytechnique de Montréal with extensive international academic experience, including visiting professorships in the United States, Saudi Arabia, and Brazil. He is an active member of IEEE, SIAM, and PMI, and has led numerous research projects in computational methods and fluid mechanics, supervising a large number of researchers across different levels. His projects span areas such as scientific machine learning, quantum computing, wireless power transfer, magnetohydrodynamics, turbulence modeling, superconductivity, artificial neural networks, numerical methods, and optimization for engineering systems. He has taught a wide range of mathematical and engineering courses, including finite element methods, deep learning mathematics, linear algebra, and scientific computing, and has coordinated major undergraduate programs. Prof. Dufour also plays a strong leadership role in university governance, contributing significantly to academic councils, program development, labor agreement negotiations, and institutional committees, demonstrating consistent commitment to advancing engineering education and research.

Khademi, A., & Dufour, S. (2025). Physics-informed neural networks with trainable sinusoidal activation functions for approximating the solutions of the Navier–Stokes equations. Computer Physics Communications.

Khademi, A., Salari, E., & Dufour, S. (2025). Simulation of 3D turbulent flows using a discretized generative model physics-informed neural networks. International Journal of Non-Linear Mechanics, 170, 104988.

Khademi, A., & Dufour, S. (2024). A novel discretized physics-informed neural network model applied to the Navier–Stokes equations. Physica Scripta, 99(7), 076016.

Arab, H., Wang, D., Wu, K., & Dufour, S. (2022). A full-wave discontinuous Galerkin time-domain finite element method for electromagnetic field mode analysis. IEEE Access, 10, 125243–125253.

Arab, H., Arabsalmanabadi, B., & Dufour, S. (2022). A novel time-domain numerical methodology for the electromagnetic analysis of an H-plane tee power divider. The Journal of Engineering, 2022(10), 1032–1036.

Prof. Vladimir Filinov | Quantum Thermodynamics | Best Researcher Award

Published on by Global Energy Awards

Prof. Vladimir Filinov | Quantum Thermodynamics | Best Researcher Award

Joint Institute for High Temperatures of the Russian Academy of Sciences | Russia

Prof. Vladimir Filinov is a distinguished scientist at the Theoretical Department of the Institute for High Temperatures, Russian Academy of Sciences in Moscow, with a long-standing career in advanced theoretical and computational physics. His primary specialization focuses on computational methods of quantum statistical mechanics and wave propagation in random media, along with contributions to computer physics, Monte Carlo methods, perturbation theory of dense gases and plasmas, and solid-state systems. He has pioneered quantum complex-valued Monte Carlo techniques, path-integral approaches for stationary and non-stationary quantum problems, quantum molecular dynamics for the Wigner–Liouville equation, and the tomographic representation of quantum mechanics, with significant research on strongly correlated dusty, electromagnetic, and quark–gluon plasmas. His work has been widely recognized through notable awards, memberships in professional scientific societies, research grants, collaborative international programs, and visiting professorships across several universities worldwide. He has authored more than two hundred papers, numerous scientific communications, and several influential books and encyclopedia chapters, contributing extensively to the advancement of quantum statistical physics.

Filinov, V., Levashov, P., & Larkin, A. (2025). Wigner path integral representation of the density of states: Monte Carlo simulation of plasma media. Journal of Statistical Physics.

Filinov, V., Levashov, P., & Larkin, A. (2025). Density response and correlation functions in the Wigner path integral representation: Monte Carlo simulations. Physics Letters A: General Atomic and Solid State Physics.

Filinov, V. S., Levashov, P. R., & Larkin, A. S. (2025). Spectral density of the Wigner path integral operator correlation function representation: Monte Carlo simulation of the fermion dynamic structure factor. Molecular Physics.

Filinov, V. S., Levashov, P. R., & Larkin, A. S. (2024). Phase-space path-integral representation of the quantum density of states: Monte Carlo simulation of strongly correlated soft-sphere fermions. Physical Review E.

Filinov, V., Levashov, P., & Larkin, A. (2023). Density of states of a 2D system of soft-sphere fermions by path integral Monte Carlo simulations. Journal of Physics A: Mathematical and Theoretical.

Assoc. Prof. Dr. Adnan Ozsoy | Computational Methods | Best Researcher Award

Published on by Global Energy Awards

Assoc. Prof. Dr. Adnan Ozsoy | Computational Methods | Best Researcher Award

Hacettepe University | Turkey

Dr. Adnan Ozsoy is a computer engineering academic specializing in blockchain, cryptocurrencies, distributed systems, parallel computing, HPC, GPGPU technologies, and big data problems. He has led and contributed to multiple prestigious funded research projects covering efficient parallelization on GPUs, lattice-based cryptographic protocols, and NTRU-based cryptosystems. His current research focuses on blockchain applications across sectors such as health, land registry, digital identity, secure distributed storage, scalable microservices, high-rate message handling, voltage scaling on GPUs, data compression, SDR-based real-time signal detection, and sequence alignment. He has supervised numerous Ph.D. and M.S. theses in blockchain technologies, parallel and embedded systems, cryptography, and secure distributed computing. At Hacettepe University, he teaches core and advanced subjects including data structures, algorithms, parallel programming, and blockchain, and has pioneered Turkey’s first undergraduate and graduate blockchain course. His professional engagements include consultancy at NETGSM on big data architecture, cloud and container technologies, microservices, scalability challenges, and academic R&D outcomes. His career is further supported by several major international and national awards, invitations for seminars and trainings, and industry collaborations in GPU computing and blockchain technologies.

Erdogan, H. T., & Ozsoy, A. (2025). CUDA-supported 5G multi-access edge computing modifications on 5G-air-simulator. EURASIP Journal on Wireless Communications and Networking, 2025(1), 29.

Ozsoy, A., Nazli, M., Cankur, O., & Sahin, C. (2025). CUSMART: Effective parallelization of string matching algorithms using GPGPU accelerators. Frontiers of Information Technology & Electronic Engineering, 26(6), 877–895.

Cihan, S., Yılmaz, N., Ozsoy, A., & Beyan, O. D. (2025). A systematic review of the blockchain application in healthcare research domain: Toward a unified conceptual model. Medical & Biological Engineering & Computing, 63(5), 1319–1342.

Zorlu, O., & Ozsoy, A. (2024). A blockchain-based secure framework for data management. IET Communications, 18(10), 628–653.

Fisne, A., Kalay, A., Yavuz, F., Cetintepe, C., & Ozsoy, A. (2023). Energy-efficient computing for machine learning based target detection. Concurrency and Computation: Practice and Experience, 35(24), e7582.