Dr. Marran Al Qwaid | Artificial Intelligence | Best Researcher Award

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Dr. Marran Al Qwaid | Artificial Intelligence | Best Researcher Award

Assistant Professor | Shaqra University | Saudi Arabia

Dr. Marran Al Qwaid is a distinguished academic and Vice Dean of E-Learning and Digital Transformation at Shaqra University, holding a Ph.D. in Computing and Information Systems. His extensive experience as an Assistant Professor in Computer Science reflects a strong foundation in Artificial Intelligence, cybersecurity, and digital innovation. Dr. Marran Al Qwaid has contributed significantly to research in Artificial Intelligence-driven optimization, secure data systems, and computational efficiency. His academic journey spans global institutions, earning degrees from reputed universities and professional certifications in Artificial Intelligence, cybersecurity, and leadership from renowned platforms. With publications in high-impact journals and participation in international conferences, he has established a profound presence in the field of Artificial Intelligence. His research explores Artificial Intelligence applications in secure computing, data privacy, and cyber defense, demonstrating advanced analytical and problem-solving skills. As an editor and committee member in multiple international journals and conferences, he showcases leadership in Artificial Intelligence research and digital transformation. Dr. Marran Al Qwaid has received recognition for his scholarly and administrative excellence, including appointments to key university committees related to Artificial Intelligence, cloud computing, and innovation governance. His technical expertise, combined with a vision for enhancing Artificial Intelligence education and application, marks him as a pivotal contributor to the digital future. His remarkable career underlines excellence in Artificial Intelligence teaching, research, and leadership. Scopus profile of 2 Citations, 4 Documents, 1 h-index.

Profile: Scopus

Featured Publication

1. Performance Optimization of Grounding System for Multi-Voltage Electrical Installation. (2025). Applied Sciences, Switzerland.

Dr. Wu Qiuxuan | Robotics and Automation | Best Researcher Award

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Dr. Wu Qiuxuan | Robotics and Automation | Best Researcher Award

Teacher | Hangzhou Dianzi university | China

Dr. Wu Qiuxuan, an Associate Professor at the School of Automation, Hangzhou Dianzi University, is a distinguished researcher whose expertise and leadership have significantly advanced the field of Robotics and Automation. With a Ph.D. in Control Science and Engineering from Shanghai Jiaotong University, his academic journey reflects a deep commitment to innovation in Robotics and Automation, particularly in the areas of soft robotics, evolutionary learning, and home energy systems. Dr. Wu’s professional experience includes academic and research roles, notably as a visiting scholar at the Australian National University, where he furthered his understanding of intelligent robotic systems. His extensive research on bipedal robots, underwater biomimetic designs, and bio-inspired control algorithms has earned him international recognition. Dr. Wu has authored impactful papers in leading journals such as IEEE Robotics and Automation Letters and Bioinspiration & Biomimetics, contributing to global advancements in Robotics and Automation. His work integrates advanced modeling, deep reinforcement learning, and optimization techniques to enhance robotic adaptability and performance. Over the years, Dr. Wu has received numerous research grants supporting his pioneering studies on service robots, industrial automation, and 3D bioprinting technologies, underscoring his central role in the evolution of Robotics and Automation. With 721 citations, an h-index of 11, and an i10-index of 20, his scholarly influence continues to grow. Dr. Wu’s research skills encompass algorithmic innovation, system optimization, and control engineering, blending theoretical insight with practical application. In conclusion, Dr. Wu Qiuxuan stands as a driving force in Robotics and Automation, whose interdisciplinary expertise continues to shape intelligent systems and inspire the next generation of automation research worldwide.

Profiles: ORCID | Google Scholar

Featured Publications

1. Cai, N., He, M., Wu, Q., & Khan, M. J. (2019). On almost controllability of dynamical complex networks with noises. Journal of Systems Science and Complexity, 32(4), 1125–1139.

2. Chi, X., Liu, B., Niu, Q., & Wu, Q. (2012). Web load balance and cache optimization design based nginx under high-concurrency environment. Proceedings of the Third International Conference on Digital Manufacturing & Automation, 69–73.

3. Wu, Q., Yang, X., Wu, Y., Zhou, Z., Wang, J., Zhang, B., Luo, Y., Chepinskiy, S. A., ... (2021). A novel underwater bipedal walking soft robot bio-inspired by the coconut octopus. Bioinspiration & Biomimetics, 16(4), 046007.

4. Wu, Q., Gu, Y., Li, Y., Zhang, B., Chepinskiy, S. A., Wang, J., Zhilenkov, A. A., ... (2020). Position control of cable-driven robotic soft arm based on deep reinforcement learning. Information, 11(6), 310.

5. Chi, X., Wang, C., Wu, Q., Yang, J., Lin, W., Zeng, P., Li, H., & Shao, M. (2023). A ripple suppression of sensorless FOC of PMSM electrical drive system based on MRAS. Results in Engineering, 20, 101427.

Dr. Temitope Adefarati | Engineering | Best Researcher Award

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Dr. Temitope Adefarati | Engineering | Best Researcher Award

Post Doctoral Fellowship | University of Johannesburg | South Africa

Dr. Temitope Adefarati is a distinguished Engineering scholar whose expertise in Electrical and Electronic Engineering has made notable contributions to renewable energy, power systems, and smart grid technology. He holds advanced Engineering degrees from prestigious universities, including a Ph.D. in Electrical Engineering, and has accumulated extensive experience in Engineering education, research, and industry. As an Engineering academic and researcher, he has served as an Associate Professor and Postdoctoral Fellow, contributing to Engineering curriculum development and the supervision of numerous postgraduate Engineering theses. His Engineering research focuses on optimizing renewable energy systems, distributed power generation, and sustainable energy integration. Dr. Adefarati’s Engineering excellence has been recognized through inclusion in the World’s Top 2% Scientists list for consecutive years and through his active role as an editorial board member of leading Engineering journals such as Frontiers in Smart Grids and International Journal of Energy Research. His Engineering research skills encompass power system reliability analysis, grid-connected PV optimization, and hybrid energy system simulation. With a prolific Engineering publication record in top-tier journals like Applied Energy, he has advanced the understanding of energy management and sustainable power systems. Dr. Adefarati’s Engineering commitment extends beyond academia through consultancy and professional affiliations, including COREN and the South African Institute of Electrical Engineers. His Engineering career demonstrates innovation, leadership, and dedication to advancing global energy solutions. Google Scholar profile of 2885 Citations, 31 i10 index, 22 h-index.

Profiles: ORCID | Google Scholar

Featured Publications

1. Adefarati, T., & Bansal, R. C. (2016). Integration of renewable distributed generators into the distribution system: A review. IET Renewable Power Generation, 10(7), 873–884.

2. Adefarati, T., & Bansal, R. C. (2019). Reliability, economic and environmental analysis of a microgrid system in the presence of renewable energy resources. Applied Energy, 236, 1089–1114.

3. Adefarati, T., & Bansal, R. C. (2017). Reliability assessment of distribution system with the integration of renewable distributed generation. Applied Energy, 185, 158–171.

4. Adefarati, T., & Bansal, R. C. (2017). Reliability and economic assessment of a microgrid power system with the integration of renewable energy resources. Applied Energy, 206, 911–933.

5. Adefarati, T., Bansal, R. C., & Just, J. J. (2017). Reliability and economic evaluation of a microgrid power system. Energy Proceedings, 142, 43–48.

Otilia Pitulac | Engineering | Best Researcher Award

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Ms. Otilia Pitulac | Engineering | Best Researcher Award

Teaching Assistant | Technical University Gheorghe Asachi Iasi | Romania

Ms. Otilia Pitulac is an emerging scholar in the field of Environmental Engineering, recognized for her growing expertise and dedication to sustainability-driven Engineering innovations. She currently serves as a Teaching Assistant at the “Gheorghe Asachi” Technical University of Iași, where she contributes to academic and research excellence in hydrotechnics, geodesy, and environmental Engineering. Her academic journey includes a PhD in Environmental Engineering, a Master’s in Geomatics and Cartography, and a Bachelor’s in Geography, reflecting a strong foundation in both theoretical and applied Engineering disciplines. Ms. Pitulac’s research interests lie in environmental management, green city development, climate resilience, and sustainable Engineering practices. Her work emphasizes innovative approaches to soil conservation, resource optimization, and urban ecological balance within modern Engineering systems. Throughout her academic and professional experience, she has demonstrated Engineering skills in GIS analysis, project coordination, sustainable soil management, and environmental modeling. Her Engineering achievements are complemented by strong teamwork and communication abilities, essential for collaborative research environments. Ms. Pitulac has been actively engaged in guiding students and supporting Engineering research projects focused on sustainability and urban innovation. She has shown excellence in applying Engineering principles to address real-world environmental challenges, contributing meaningfully to the field’s evolution. Through continuous learning, practical engagement, and technical proficiency, Ms. Otilia Pitulac exemplifies the new generation of researchers shaping the future of sustainable Engineering, demonstrating an unwavering commitment to innovation, academic integrity, and interdisciplinary advancement.

Profile: ORCID

Featured Publication

1. Pitulac, O., Chirilă, C., Stătescu, F., & Marcoie, N. (2025). GIS-based assessment of photovoltaic and green roof potential in Iași, Romania. Applied Sciences, 15(19), 10786.

Prof. Viktor Mykhas’kiv | Computational Methods | Best Researcher Award

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Prof. Viktor Mykhas’kiv | Computational Methods | Best Researcher Award

Leading Scientific Researcher | Institute for Applied Problemss of Mechanics and Mathematics | Ukraine

Prof. Viktor Mykhas’kiv is a distinguished researcher at the Pidstryhach Institute for Applied Problems of Mechanics and Mathematics, National Academy of Sciences of Ukraine. His academic achievements include a Doctor of Science in Physics and Mathematics and a professorship in Mechanics of Deformable Solids. His extensive expertise in Computational Methods spans across Computational Mechanics, Materials Science, Structural Mechanics, and Multiscale Mathematical Modeling. Through his pioneering work, he has applied Computational Methods to study wave propagation, metamaterials, and nanomechanics, advancing knowledge in multiple scattering theory. His research leadership in international collaborations under INTAS, STCU, DAAD, DFG, and Fulbright programs highlights his ability to integrate Computational Methods within global scientific frameworks. As a team leader and project manager, he has promoted innovative Computational Methods in the investigation of elastic metamaterials and complex lattice structures. He has published widely, authoring over seventy-six Scopus-indexed papers, two books, and contributing to editorial boards of international journals like Mathematical Methods and Physicomechanical Fields. His commitment to excellence in Computational Methods is reflected in his role as a member of the European Structural Integrity Society. He has also served as a visiting researcher in the USA and Germany, applying Computational Methods to solve advanced mechanical and physical problems. His awards and honors recognize his groundbreaking use of Computational Methods in applied mechanics and theoretical modeling. With remarkable research skills and professional integrity, Prof. Viktor Mykhas’kiv continues to contribute significantly to global scientific progress. Scopus profile of 474 Citations, 76 Documents, 14 h-index.

Profiles: Scopus | ORCID

Featured Publications

1. Stankevych, V. Z., & Mykhas’kiv, V. V. (2023). Intensity of dynamic stresses of longitudinal shear in a periodically layered composite with penny-shaped cracks. Journal of Mathematical Sciences, 269(2), 268–280.

2. Mykhas’kiv, V. V., & Stasyuk, B. M. (2021). Effective elastic moduli of short-fiber composite with sliding contact conditions at interfaces. Mechanics of Composite Materials, 57(6), 845–854.

3. Mykhas’kiv, V., & Stankevych, V. (2019). Elastodynamic problem for a layered composite with penny-shaped crack under harmonic torsion. ZAMM – Zeitschrift für Angewandte Mathematik und Mechanik, 99(8), e201800193.

4. Mykhas’kiv, V. V., Zhbadynskyi, I. Y., & Zhang, C. (2019). On propagation of time-harmonic elastic waves through a double-periodic array of penny-shaped cracks. European Journal of Mechanics - A/Solids, 74, 68–77.

5. Zhbadynskyi, I. Y., & Mykhas’kiv, V. V. (2018). Acoustic filtering properties of 3D elastic metamaterials structured by crack-like inclusions. Proceedings of the International Seminar/Workshop on Direct and Inverse Problems of Electromagnetic and Acoustic Wave Theory (DIPED), 54–59.

Yuyao Wang | Artificial Intelligence | Best Scholar Award

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Mr. Yuyao Wang | Artificial Intelligence | Best Scholar Award

Master's Candidate | Henan Polytechnic University | China

Mr. Yuyao Wang, a Master’s candidate in Cartography and Geographic Information Systems at Henan Polytechnic University, has made significant contributions to remote sensing and artificial intelligence integration for agricultural and environmental monitoring. His research primarily focuses on remote sensing image processing, land use classification, and artificial intelligence-driven multi-source data fusion. With strong expertise in applying artificial intelligence to satellite data interpretation, Mr. Wang has developed novel frameworks for rice field identification in mountainous regions and cloud removal techniques using SAR and optical imagery fusion. His innovative use of artificial intelligence in remote sensing enhances precision agriculture and sustainable land management practices. Mr. Wang’s professional journey reflects his commitment to applying artificial intelligence and geospatial analytics to complex real-world challenges. His works published in prestigious journals like Remote Sensing and PLOS ONE demonstrate robust analytical skills, methodological innovation, and interdisciplinary thinking powered by artificial intelligence. He continues to explore advanced artificial intelligence techniques for improving data accuracy and environmental insights, bridging gaps between technology and agricultural sciences. Mr. Wang’s achievements highlight excellence in artificial intelligence research, demonstrating potential for transformative advancements in geoinformatics and environmental sustainability. His dedication, scientific curiosity, and mastery of artificial intelligence tools reinforce his reputation as a promising researcher in remote sensing and GIS. 12 Citations, 3 Documents, 2 h-index.

Profiles: Scopus | ORCID

Featured Publications

1. Wang, Y., Cheng, J., Yuan, Z., & Zang, W. (2025). Research on rice field identification methods in mountainous regions. Remote Sensing, 17(19), 3356.

2. Wang, Y. (2025, March 19). A novel cloud removal method by fusing features from SAR and neighboring optical remote sensing images.

Dr. Bahadir Kopcasiz | Computational Methods | Best Researcher Award

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Dr. Bahadir Kopcasiz | Computational Methods | Best Researcher Award

Assistant Professor | Istanbul Gelisim University | Turkey

Dr. Bahadir Kopcasiz is an accomplished academic whose expertise centers on Computational Methods, with strong emphasis on nonlinear partial differential equations, soliton theory, symbolic and semi-analytical analysis, and advanced mathematical modeling. He earned his Ph.D. in Mathematics from Bursa Uludag University, preceded by a Master’s in Mathematics from Yeditepe University and a Bachelor’s from Karadeniz Technical University, building a solid foundation for his contributions in Computational Methods. Currently serving as an Assistant Professor at Istanbul Gelisim University, he actively teaches courses such as Differential Equations, Statistics, Probability, and Numerical Analysis, integrating Computational Methods into both undergraduate and graduate programs. His research primarily focuses on soliton solutions in nonlinear Schrödinger-type systems, dynamical structures in quantum physics, and the development of innovative Computational Methods to study complex dynamical systems, with numerous publications in high-impact journals including Archives of Computational Methods in Engineering, Nonlinear Dynamics, and Symmetry. He has also presented extensively at international conferences, showcasing advancements in Computational Methods for applied physics and engineering. Among his recognitions, he received the Best Researcher Award at the International Research Awards on Composite Materials and academic incentive awards from Istanbul Gelisim University, which highlight his outstanding scholarly contributions in Computational Methods. His research skills are distinguished by mastery of symbolic computation, semi-analytical modeling, and integration of Computational Methods with machine learning for dynamic system optimization, as evidenced by his involvement in national projects. In conclusion, Dr. Bahadir Kopcasiz exemplifies excellence in academia through his dedication to advancing Computational Methods, innovative problem-solving, impactful publications, and mentorship, establishing himself as a valuable contributor to mathematics, physics, and engineering research. His Google Scholar citations 337, h-index 12, i10-index 14, showcasing measurable research impact.

Profiles: Google Scholar | ORCID

Featured Publications

1. Kopçasız, B., & Yaşar, E. (2022). The investigation of unique optical soliton solutions for dual-mode nonlinear Schrödinger’s equation with new mechanisms. Journal of Optics, 1–15.

2. Kopçasız, B., & Yaşar, E. (2022). Novel exact solutions and bifurcation analysis to dual-mode nonlinear Schrödinger equation. Journal of Ocean Engineering and Science.

3. Kopçasız, B., & Yaşar, E. (2024). Dual-mode nonlinear Schrödinger equation (DMNLSE): Lie group analysis, group invariant solutions, and conservation laws. International Journal of Modern Physics B, 38(02), 2450020.

4. Kopçasız, B. (2024). Qualitative analysis and optical soliton solutions galore: Scrutinizing the (2+1)-dimensional complex modified Korteweg–de Vries system. Nonlinear Dynamics, 112(23), 21321–21341.

5. Kopçasız, B., Seadawy, A. R., & Yaşar, E. (2022). Highly dispersive optical soliton molecules to dual-mode nonlinear Schrödinger wave equation in cubic law media. Optical and Quantum Electronics, 54(3), 194.

Dr. Lijuan Li | Artificial Intelligence | Best Researcher Award

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Dr. Lijuan Li | Artificial Intelligence | Best Researcher Award

Deputy Director of Academic Affairs Office at Nanjing Tech University, China

Dr. Lijuan Li is a distinguished professional whose career embodies excellence in automation, engineering, and artificial intelligence. Her contributions extend across teaching, research, and leadership, demonstrating a commitment to advancing knowledge in artificial intelligence. She integrates artificial intelligence into modeling, optimization, and process control, shaping the direction of modern automation. Through her academic and professional efforts, Dr. Li enhances the global understanding of artificial intelligence. She emphasizes innovation and collaboration in artificial intelligence, ensuring sustainable growth in her research. With dedication to academic leadership and artificial intelligence applications, she serves as a role model. Her work consistently reflects the transformative role of artificial intelligence in engineering, research, and advanced automation systems.

Professional Profile

Scopus Profile

Education 

Dr. Lijuan Li has established a strong educational foundation that has supported her professional journey in artificial intelligence. Her academic background demonstrates a thorough engagement with control science, engineering, and artificial intelligence. Through her advanced studies, Dr. Li developed expertise in artificial intelligence methodologies, modeling, and optimization. Education played a central role in shaping her vision, allowing her to expand artificial intelligence applications across multiple disciplines. She integrated artificial intelligence in both theoretical frameworks and practical experiments, enhancing the impact of her academic growth. Dr. Li emphasizes the essential role of artificial intelligence in research and teaching. Her education reflects a structured pathway where artificial intelligence consistently supported her achievements. With a robust educational background, she continuously fosters innovation and builds meaningful contributions through artificial intelligence.

Experience 

Dr. Lijuan Li has cultivated a broad professional experience that centers on artificial intelligence applications in automation and engineering. Her role as Professor and Director allows her to expand artificial intelligence within research and academic leadership. She has guided multiple research initiatives where artificial intelligence shaped outcomes in modeling, process design, and optimization. Through professional roles, she integrates artificial intelligence to strengthen collaborations and inspire colleagues. Artificial intelligence remains a consistent theme in her professional journey, supporting innovation in automation. She applies artificial intelligence in research projects and administrative leadership. As a professional leader, she builds institutional strategies that align with artificial intelligence-driven advancements. Her professional experience reflects her dedication to artificial intelligence as a core element. By integrating artificial intelligence across academic and applied domains, Dr. Li continues to influence automation research.

Research Interest 

Dr. Lijuan Li research interests are centered on artificial intelligence with emphasis on automation, process modeling, and optimization. She explores artificial intelligence for improving industrial systems and control performance evaluation. Her research applies artificial intelligence across process engineering, enhancing efficiency and sustainability. With focus on artificial intelligence, she builds methodologies that integrate innovation and practical applications. She actively investigates artificial intelligence for complex system management. Artificial intelligence serves as the foundation of her interdisciplinary research projects. Her interests combine automation, engineering, and artificial intelligence to improve real-world outcomes. She highlights artificial intelligence as the driver of progress in process industries. Dr. Li’s work demonstrates how artificial intelligence fosters adaptability in automation. Her research interests continually evolve with artificial intelligence, addressing both theoretical development and practical impact in automation.

Award and Honor

Dr. Lijuan Li has earned recognition through awards and honors that celebrate her expertise in artificial intelligence. Her achievements highlight how artificial intelligence advances contribute to automation and research leadership. Awards demonstrate the value of integrating artificial intelligence into engineering and academic fields. Honors reflect her dedication to artificial intelligence innovations and their societal impact. She consistently promotes artificial intelligence as a transformative tool in academia. Recognitions validate her ability to advance artificial intelligence knowledge and its applications. Each award highlights her strong commitment to artificial intelligence excellence. Her honors emphasize leadership in research and teaching where artificial intelligence remains central. The impact of artificial intelligence in her achievements underscores her pioneering contributions. Through these recognitions, Dr. Li’s role in promoting artificial intelligence within academia and research is continually reinforced.

Research Skill

Dr. Lijuan Li possesses advanced research skills with deep expertise in artificial intelligence. Her skills include modeling, simulation, optimization, and performance evaluation driven by artificial intelligence. She demonstrates the capacity to apply artificial intelligence across interdisciplinary projects. Her research skills extend to developing methodologies where artificial intelligence supports process innovation. Artificial intelligence plays a consistent role in her experiments, data analysis, and optimization strategies. She uses artificial intelligence to design frameworks that enhance automation. With research skills grounded in artificial intelligence, she contributes to advancing industrial applications. Her expertise ensures innovation in artificial intelligence for automation systems. Dr. Li’s research skills emphasize adaptability, precision, and creative integration of artificial intelligence. Through these capabilities, she continues to strengthen the scientific community’s reliance on artificial intelligence as a key research driver.

Publication Top Notes 

Title: Real-time prediction of temperature field during welding by data-mechanism driving 
Journal: Journal of Manufacturing Processes
Year : 2025

Title: A new method of simulation and optimization in biogas high-pressure water scrubbing process based on surrogate model
Journal: Separation Science and Technology Philadelphia
Year : 2025

Title: Factor Graph Optimization Localization Method Based on GNSS Performance Evaluation and Prediction in Complex Urban Environment  
Journal: IEEE Sensors Journal
Year : 2025

Title: Digital twin for weld pool evolution by data-physics integrated driving 
Journal: Journal of Manufacturing Processes
Year : 2024

Title: Kinetic parameter identification in the residue hydro refining reaction using a novel optimizer: IAC-SCA
Journal: Chemical Engineering Science
Year : 2024

Title: A method for predicting methane production from anaerobic digestion of kitchen waste under small sample conditions
Journal: Environmental Science and Pollution Research
Year : 2024

Conclusion

Dr. Lijuan Li career demonstrates excellence in artificial intelligence, automation, and engineering. She highlights artificial intelligence as a transformative power in education, research, and professional leadership. Her journey illustrates how artificial intelligence enriches scientific contributions and technological applications. She applies artificial intelligence consistently across teaching, research, and management. Artificial intelligence remains the foundation of her innovation strategies and academic vision. Through leadership, she integrates artificial intelligence in advancing automation fields. Dr. Li’s conclusion underscores her dedication to artificial intelligence in academia and industry. Her career is a testament to the enduring relevance of artificial intelligence. She inspires peers by demonstrating the potential of artificial intelligence for global progress. In conclusion, her professional path reflects a strong and lasting commitment to artificial intelligence across disciplines.

Assist. Prof. Dr. Kifle Adula Duguma | Computational Methods | Best Researcher Award

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Assist. Prof. Dr. Kifle Adula Duguma | Computational Methods | Best Researcher Award

Assistant Professor at Addis Ababa Science and Technology University, Ethiopia

Assist. Prof. Dr. Kifle Adula Duguma is a distinguished academic in the field of Computational Methods, dedicated to advancing knowledge in computational fluid dynamics, applied mathematics, and numerical analysis. His work on Computational Methods spans theoretical research, practical applications, and interdisciplinary collaboration. In his professional journey, Dr. Duguma has integrated Computational Methods into both undergraduate and postgraduate education, guiding students in research and project work. His publications in high-impact journals consistently emphasize Computational Methods for solving complex fluid flow, heat transfer, and porous media problems. By applying Computational Methods to nanofluid dynamics, magnetohydrodynamics, and hybrid modeling, he has contributed valuable insights to modern engineering problems. His academic leadership also promotes Computational Methods as a cornerstone of innovative problem-solving.

Professional Profile

ORCID Profile | Google Scholar Profile

Education 

Assist. Prof. Dr. Kifle Adula Duguma has built his academic foundation through extensive studies in mathematics, numerical analysis, and computational fluid dynamics, always centered on Computational Methods. From undergraduate studies in mathematics to advanced doctoral research, Computational Methods formed the core of his learning. His doctoral thesis applied Computational Methods to complex flow and heat transfer problems, integrating theory with simulation. During his master’s degree, he refined his expertise in Computational Methods for solving nonlinear partial differential equations. Each academic stage strengthened his ability to innovate with Computational Methods, whether in finite element approaches, finite difference applications, or numerical modeling techniques. His training consistently reflects a deep engagement with Computational Methods, preparing him for impactful contributions in teaching and research.

Experience 

Assist. Prof. Dr. Kifle Adula Duguma has extensive professional experience applying Computational Methods in both teaching and research. As an assistant professor, he has taught courses in applied mathematics, computational fluid dynamics, and numerical analysis, always embedding Computational Methods in lectures, laboratories, and projects. His leadership roles, including heading the mathematics division, emphasized curriculum design with strong Computational Methods components. His research applies Computational Methods to nanofluid flows, magnetohydrodynamics, hybrid models, and porous media. He supervises student projects that rely on Computational Methods for simulation and optimization. Across his career, Dr. Duguma has demonstrated that Computational Methods are essential in solving complex engineering problems, from industrial applications to academic challenges, ensuring students and peers value Computational Methods in their work.

Research Interest 

Assist. Prof. Dr. Kifle Adula Duguma’s research interests revolve around the innovative application of Computational Methods in science and engineering. His primary focus areas include computational fluid dynamics, nanofluids, magnetohydrodynamics, electrohydrodynamics, and thermal transport phenomena, all driven by Computational Methods. He explores new algorithms, optimization techniques, and simulation strategies using Computational Methods for real-world problems. His studies in non-Newtonian fluids and hybrid nanofluids apply Computational Methods to enhance prediction accuracy and performance modeling. By integrating Computational Methods into multidisciplinary research, he addresses challenges in heat and mass transfer, stability analysis, and porous media flows. The consistent thread in his scholarly work is the advancement of Computational Methods as powerful tools for solving emerging engineering and scientific challenges worldwide.

Award and Honor

Assist. Prof. Dr. Kifle Adula Duguma’s academic achievements are closely linked to his pioneering contributions in Computational Methods. His recognition comes from publishing high-impact research where Computational Methods solve advanced engineering problems. Awards and honors highlight his leadership in integrating Computational Methods into both research and teaching. Serving as a journal reviewer, he evaluates work that applies Computational Methods across various domains. His leadership positions and contributions to academic communities are built upon advancing Computational Methods knowledge. These honors reflect not only technical expertise but also his ability to inspire others to apply Computational Methods in innovative ways. By consistently promoting Computational Methods, Dr. Duguma has earned respect as a leading figure in computational science and engineering.

Research Skill

Assist. Prof. Dr. Kifle Adula Duguma’s research skills are deeply rooted in Computational Methods, making him proficient in multiple numerical and analytical approaches. He expertly applies Computational Methods such as finite difference, finite element, finite volume, and Runge-Kutta techniques to model complex systems. His use of Computational Methods extends to software like MATLAB, Mathematica, Maple, and Python for simulation and analysis. He excels in data interpretation, algorithm development, and scientific computation, all grounded in Computational Methods. His capacity to integrate Computational Methods into experimental validation and theoretical frameworks strengthens his research output. Whether in teaching, mentoring, or publication, his skill set ensures Computational Methods remain central to his work and to the advancement of modern engineering practices globally.

Publication Top Notes

Title: Stability analysis of dual solutions of convective flow of casson nanofluid past a shrinking/stretching slippery sheet with thermophoresis and brownian motion in porous media

Authors: KA Duguma, OD Makinde, LG Enyadene

Journal: Journal of Mathematics

Title: Dual Solutions and Stability Analysis of Cu-H2O-Casson Nanofluid Convection past a Heated Stretching/Shrinking Slippery Sheet in a Porous Medium

Authors: KA Duguma, OD Makinde, LG Enyadene

Journal: Computational and Mathematical Methods

Title: Stagnation Point Flow of CoFe2O4/TiO2-H2O-Casson Nanofluid past a Slippery Stretching/Shrinking Cylindrical Surface in a Darcy–Forchheimer Porous Medium

Authors: KA Duguma, OD Makinde, LG Enyadene

Journal: Journal of Engineering

Title: Effects of buoyancy on radiative MHD mixed convective flow of casson nanofluid across a preamble slippery sheet in Darcy–Forchheimer porous medium: Shrinking/stretching surface …

Authors: KA Duguma

Journal: Numerical Heat Transfer, Part B: Fundamentals

Title: Stability Analysis of Dual Solutions of Convective Flow of Casson Nanofluid past a Shrinking/Stretching Slippery Sheet with Thermophoresis and Brownian Motion …

Authors: KA Duguma, OD Makinde, LG Enyadene

Journal: Journal of Mathematics

Conclusion

In conclusion, Assist. Prof. Dr. Kifle Adula Duguma’s career reflects unwavering dedication to Computational Methods in education, research, and professional service. His expertise ensures Computational Methods are applied rigorously across scientific domains, from computational fluid dynamics to nanotechnology. Through teaching, supervision, and publication, he promotes the strategic use of Computational Methods to solve critical engineering problems. His leadership in academic and research settings consistently elevates the role of Computational Methods as indispensable tools in modern science. By advancing Computational Methods methodologies, fostering innovation, and inspiring students, he has established a legacy that underscores the transformative power of Computational Methods in solving global scientific and technological challenges.