Prof. Steven Dufour | Fluid Mechanics | Best Researcher Award

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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.

Dr. Adarsh Kumar Shukla | Computational Methods | Young Scientist Award

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Dr. Adarsh Kumar Shukla | Computational Methods | Young Scientist Award

Dr. Bhimrao Ambedkar Government Medical College | India

Dr. Adarsh Kumar Shukla is a motivated and results-driven professional with expertise in Environmental Toxicology, Clinical Bioinformatics, NGS Data Analysis, Pathway Analysis, Computer-Aided Drug Design, Structural Biology, Metabolomics, Computational Biology, and Computational Chemistry. Currently serving as Scientist-B at the Multidisciplinary Research Unit, Dr. Bhimrao Ramji Ambedkar Government Medical College, Kannauj, he has prior experience as a Scientist and Research Associate in Paediatric Cardiac Research at Sri Sathya Sai Sanjeevani Research Foundation, as well as academic and project coordination roles in biotechnology and medicinal plant research. He has coordinated national-level academic events and completed FDPs focused on healthcare innovation. Dr. Shukla has contributed significantly to Health-, Plant-, and Food-Informatics research, presented papers at several conferences, and holds a granted Indian patent for the development of crab-apple-based jelly sheets. His research interests encompass structural bioinformatics, human genomics, and nutritional biotechnology, with strong proficiency in in-silico tools, laboratory instrumentation, and data analysis. Skilled in programming languages such as R, Biopython, and Bioperl, he combines computational and experimental approaches to address complex biomedical challenges.sics.

Profile: Scopus | Orcid | Google Scholar 

Featured Publications

Shukla, A. K., & Kukshal, P. (2025). Computational simulations aided prioritization of genomic targets for congenital heart disease (CHD) against developmental toxicity. Reproductive Toxicology, 108, 108940.

Shukla, A. K., & Kumar, A. (2025). A chemoinformatics study to prioritization of anticancer orally active lead compounds of pearl millet against adhesion G protein-coupled receptor. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 334, 125960.

Jha, R. K., Shukla, A. K., Kumari, A., & Kumar, A. (2025). Virtual screening of potential orally active anti-bacterial compounds of finger millet. Vegetos, 38(3), 1237–1248.

Jain, S., Shukla, A. K., Deepika, Panwar, S., Kumari, A., Yadav, A. K., & Kumar, A. (2024). Revolutionizing disease treatment through bioengineered probiotics and glucagon‐like peptide 1 (GLP‐1) based strategies: A path towards effective cures. Food Bioengineering, 2024, 1.

Panwar, S., Pal, S., Shukla, A. K., Kumar, A., & Sharma, P. K. (2024). Identification of micronutrient deficiency related miRNA and their targets in Triticum aestivum using bioinformatics approach. Ecological Genetics and Genomics, 31, 100236.

Prof. Xiangchao Shi | Computational Methods | Best Researcher Award

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Prof. Xiangchao Shi | Computational Methods | Best Researcher Award

Southwest Petroleum University  | China

Professor Shi Xiangchao, Assistant Dean at the School of Petroleum and Natural Gas Engineering, Southwest Petroleum University, specializes in drilling acceleration, intelligent drilling systems, and rock mechanics. His pioneering work integrates finite element analysis and rock mechanics to enhance the coupling performance of PDC bits and positive displacement motors (PDMs), improving drilling efficiency and stability in complex formations. He has contributed significantly to deep and ultra-deep shale gas drilling technologies through collaborations with CNPC, Sinopec, and international universities. His research establishes strong theoretical and computational foundations for intelligent, efficient, and safe petroleum drilling operations.

Profile: Scopus | Orcid | Google Scholar  

Featured Publications

Liu, J., Xue, F., Dai, J., Yang, J., Wang, L., Shi, X., Dai, S., Hu, J., & Liu, C. (2025). Waveform features and automatic discrimination of deep and shallow microearthquakes in the Changning shale gas field, Southern Sichuan Basin, China. Journal of Applied Geophysics, 105850.

Dai, J., Liu, J., Yang, J., Xue, F., Wang, L., Shi, X., Dai, S., Hu, J., & Liu, C. (2025). Seismicity associated with hydraulic fracturing in Changning shale gas field, China: Constraints from source mechanisms, stress field and fluid overpressure thresholds. Journal of Rock Mechanics and Geotechnical Engineering.

Wang, Z., Shi, X., Jiao, Y., Chen, S., Wang, R., & Lv, Z. (2025). Integrated selection and design method for PDC bits and positive displacement motor. Petroleum.

Fan, C., Nie, S., Li, H., Pan, Q., Shi, X., Qin, S., Zhang, M., & Yang, Z. (2024). Geological characteristics and major factors controlling the high yield of tight oil in the Da’anzhai member of the western Gongshanmiao in the central Sichuan basin, China. Geomechanics and Geophysics for Geo-Energy and Geo-Resources, 10(1), 67.

Wang, Z., Shi, X., Chen, S., Jiao, Y., Wang, R., & Lv, Z. (2024). Enhancement on PDC bit based on Archimedean spiral control method. Petroleum Science Bulletin.

Johannes Krotz | Computational Methods | Best Researcher Award

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Dr. Johannes Krotz | Computational Methods | Best Researcher Award

Postdoctoral Fellow at Notre Dame, United States

👨‍🎓 Profiles

🌟Summary

👨‍🎓 PhD candidate in Mathematics with a minor in Computer Science, specializing in probabilistic and data-driven methods for numerical PDEs and hybrid Monte Carlo methods for complex systems simulations. Experienced in statistical modeling, computational physics, and advanced simulations with a strong background in teaching and academic leadership. Currently working as a Postdoctoral Researcher at the University of Notre Dame.

🎓 Education

🎓 PhD in Mathematics (Minor in CS)
University of Tennessee Knoxville, 2021–2024

  • Dissertation on Probabilistic & Data-Driven Methods in Numerical PDEs
  • GPA: 4.0

📊 M.Sc. in Statistics
University of Tennessee, 2022–2024

  • GPA: 3.9

📚 M.Sc. in Mathematics
Oregon State University, 2019–2021

  • GPA: 4.0

⚛️ M.Sc. in Physics
University of Konstanz, 2015–2019

  • GPA: 4.0 (Honors)

🔢 B.Sc. in Mathematics & Physics
University of Konstanz, 2012–2018

  • GPA: 3.5 (Mathematics), 3.3 (Physics)

💼 Professional Experience

🔬 Postdoctoral Researcher
University of Notre Dame, 2024–Present

  • Research on hybrid Monte Carlo & deterministic kinetic transport algorithms for exascale simulations in neutron transport.

🧑‍💻 Graduate Research Assistant (GRA)
University of Tennessee/ORNL, 2023–2024

  • Advancing dynamic likelihood filters for stochastic advection-diffusion equations in collaboration with ORNL and UTK.

💼 Research Intern
Oak Ridge National Lab (ORNL), 2021–2022

  • Developed hybrid algorithms for simulating complex particle systems in 2D & 3D.

🌍 Research Intern
Los Alamos National Lab (LANL), 2020

  • Focus on high-fidelity discrete fracture networks and Poisson-disk sampling algorithms for triangulations.

🔬 Research Interests

  • 🧠 Computational Mathematics: Hybrid Monte Carlo methods, kinetic transport equations, and numerical simulations for complex physical systems.
  • 🔍 Stochastic Processes: Advanced data-driven filtering techniques and applications in fluid dynamics, advection-diffusion, and PDEs.
  • 💻 Statistical Modeling: Development of methods for high-dimensional data and stochastic modeling.
  • 🌐 Interdisciplinary Work: Collaborating across fields of mathematics, physics, and engineering to tackle real-world computational challenges.

🏆 Awards

  • 1st & 3rd place at the UTK SIAM Research Showcase (2023, 2024)
  • Randall E. Cline Award (2022) for research excellence

🖥 Technical Skills

  • Python, C++, R, Matlab, LATEX, and more
  • Basic Fortran, AWK

🔗 Professional Memberships

  • SIAM, AWM, AAAS, UCW

 Publications

A Hybrid Monte Carlo, Discontinuous Galerkin Method for Linear Kinetic Transport Equations

  • Authors: Johannes Krotz, Cory D. Hauck, Ryan G. McClarren
  • Journal: Journal of Computational Physics, Vol. 514
  • Year: 2024
Variable Resolution Poisson-Disk Sampling for Meshing Discrete Fracture Networks
  • Authors: Johannes Krotz, Matthew R. Sweeney, Jeffrey D. Hyman, Juan M. Restrepo, Carl W. Gable
  • Journal: Journal of Computational and Applied Mathematics, Vol. 407
  • Year: 2022
Dynamic Likelihood Filters for Advection Diffusion Equations
  • Authors: Johannes Krotz, Jorge M. Ramires, Juan M. Restrepo
  • Journal: The Monthly Weather Review
  • Year: Under review
Minimizing Effects of the Kalman Gain on Posterior Covariance Eigenvalues, the Characteristic Polynomial and Symmetric Polynomials of Eigenvalues
  • Authors: Johannes Krotz
  • Journal: Arxiv (preprint)
  • Year: 2024

 

 

 

Muhammad Abubaker | Computational Methods | Best Researcher Award

Published on by Global Energy Awards

Mr. Muhammad Abubaker | Computational Methods | Best Researcher Award

PhD Scholar at Kyungpook National University, South Korea

Muhammad Abubaker is a dedicated researcher and Ph.D. candidate at Kyungpook National University (KNU), South Korea, specializing in computational fluid dynamics (CFD) and energy systems. His research primarily focuses on the Lattice Boltzmann Method (LBM) for simulating fluid dynamics, particularly in lithium-ion batteries, thermal management of electric vehicle (EV) batteries, and energy harvesting systems.

🎓Profile

🧑‍🎓 Early Academic Pursuits

Muhammad Abubaker’s academic journey has been marked by a strong foundation in Mechanical Engineering, starting with his undergraduate studies at Bahauddin Zakariya University, Multan, Pakistan, where he completed his B.Sc. in Mechanical Engineering. His early interest in thermal systems engineering was reflected in his M.Sc. at the University of Engineering and Technology, Taxila, where he researched the effect of vapor velocity on condensate retention on pin-fin tubes, a crucial study for improving heat transfer systems. His academic excellence during these years was recognized with multiple scholarships, including the MSc Scholarship from UET Taxila and later, the prestigious Ph.D. Kings Scholarship at Kyungpook National University, South Korea.

💼 Professional Endeavors

Abubaker’s professional journey includes a rich teaching career as a Lecturer at COMSATS University Islamabad, Sahiwal, Pakistan, where he taught courses on Thermodynamics, Fluid Mechanics, Power Plants, and Renewable Energy Technologies. His commitment to teaching excellence was reflected in his design of outcome-based education (OBE) courses, as well as his innovative hands-on approach to learning through semester projects on heat exchangers, power plant schematics, and aeroplane models. His contributions to curriculum design and ISO compliance further demonstrate his leadership within academia.

🧪 Contributions and Research Focus

Muhammad Abubaker’s primary research focus is in the development and application of Lattice Boltzmann Method (LBM) for simulating complex multicomponent fluid dynamics in various systems. His work on Li-ion battery wettability is groundbreaking, as it addresses key challenges in battery performance and safety. Through his innovative use of LBM, he has investigated the electrolyte wetting behavior in lithium-ion batteries, offering insights into optimizing battery designs for better performance and longevity.

Abubaker is also focused on thermal management of electric vehicle (EV) batteries—a crucial aspect of improving EV performance and energy efficiency. His research into thermal LBM in porous media and energy harvesting systems, such as solar panels and flexible structures, aims to push the boundaries of energy conversion and sustainability. His work on energy systems, particularly in solar energy technology and energy harvesters, is a testament to his commitment to advancing green energy solutions.

🌍 Impact and Influence

Abubaker’s research has had significant impact, particularly in the field of energy storage and battery technology, with implications for industries ranging from automotive to consumer electronics. His work on battery electrode-electrolyte interfaces is helping solve critical issues related to wettability and ion transport, thereby contributing to the development of more efficient and durable lithium-ion batteries.

📚 Academic Cites and Scholarly Contributions

Abubaker’s academic contributions are well-recognized in the scholarly community, as evidenced by his numerous journal publications in highly regarded peer-reviewed journals, such as Energy Reports, Thermal Science, and Applied Thermal Engineering. His Google Scholar Profile highlights the growing recognition of his work, with citations that underscore the relevance and impact of his research. Notable papers such as “Wetting Performance Analysis of Porosity Distribution in NMC111 Layered Electrodes in Li-Ion Batteries” and “Wetting Characteristics of Li-ion Battery Electrodes” have made significant strides in advancing battery technology and thermal management.

⚙️ Technical Skills

Abubaker is highly proficient in advanced computational techniques and tools essential for modern engineering and energy research. His technical skills in Lattice Boltzmann Method (LBM), COMSOL Multiphysics, Ansys, ICEM CFD, C++, and CUDA for parallel processing make him an expert in simulating and modeling complex systems. These skills are crucial for his work in energy harvesting, thermal systems, and fluid dynamics, particularly in the context of Li-ion battery performance, fluid-solid interaction, and energy conversion systems.

👨‍🏫 Teaching Experience and Mentorship

Abubaker’s academic career is not only defined by his research but also by his dedication to teaching and mentoring students. As a Lecturer, he developed and implemented Outcome-Based Education (OBE) courses, designed course assessments, and introduced hands-on project-based learning for students. His experience in mentoring final-year projects (including topics like PV panel cooling and ground-coupled heat exchangers) reflects his ability to guide students through complex engineering challenges.

🔮 Legacy and Future Contributions

Muhammad Abubaker is well on his way to leaving a lasting legacy in the fields of energy systems, thermal management, and computational fluid dynamics. His innovative use of Lattice Boltzmann Methods in energy storage and battery systems is paving the way for advancements in battery technology and electric vehicle efficiency.Looking ahead, his future contributions could play a pivotal role in addressing the global need for sustainable energy solutions. His ongoing work on energy harvesting and thermal systems optimization could lead to more efficient renewable energy technologies that are critical for a sustainable future.

📖Publication Top Notes