Oluwaseun Akinte | Optimization | Best Researcher Award

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Dr. Oluwaseun Akinte | Optimization | Best Researcher Award

Oluwaseun Akinte | Rajamangala University of Technology Thanyaburi | Thailand

Dr. Oluwaseun Olanrewaju Akinte is a Postdoctoral Researcher in Energy and Materials Engineering at Rajamangala University of Technology Thanyaburi, specializing in renewable energy systems, hybrid microgrids, and advanced storage technologies. He earned his Ph.D. in Energy and Materials Engineering from Rajamangala University of Technology Thanyaburi, an M.Sc. in Electrical and Electronic Engineering from Coventry University, United Kingdom, and a B.Sc. in Electrical and Electronic Engineering from Olabisi Onabanjo University, Nigeria. His professional journey spans academia and industry, including roles as Research Assistant at RMUTT, Academic Tutor in Nigeria, Project/Site Engineer with Electromechanical Integrators Inc., and voluntary postgraduate lecturer at the University of the People, USA. His research contributions focus on energy storage optimization, hybrid renewable energy networks, and techno-econometric analysis of integrated microgrids, producing impactful publications in high-ranking journals such as IEEE Access, Energies, Sustainability, and Franklin Open, alongside international conference presentations. Dr. Akinte has co-authored over 16 journal and conference papers with 18 citations across 18 documents, reflecting his growing scholarly influence. His leadership extends to collaborative projects with industrial partners, addressing energy efficiency and sustainability challenges, while his invited talks at international congresses highlight his recognition in the global research community. He has been honored with the E-CUBE-I RMUTT Scholarship and the Best Oral Presentation Award at the Energy Society and Sustainability Conference. In addition, he is an active member of the International Association of Engineers (IAENG), contributing to knowledge exchange in the field of electrical and energy engineering. With strong expertise in power system modeling, microgrid optimization, and renewable integration, Dr. Akinte continues to advance innovative energy solutions with global impact. Citations: 18, Documents: 5, h-index: 2.

Profiles: Google Scholar | Scopus | ORCID

Featured Publications

1. Akinte O.O.*, Plangklang B., Prasartkaew B., Aina T.S., Energy storage management of a solar photovoltaic–biomass hybrid power system. Energies, 2023, 16(13), 5122.

2. Aina T.S.*, Akinte O.O., Awelewa A.J., Adelakun D.O., Critical evaluation of waterfall project management methodology: A case study of digital management conference project. Int. J. Adv. Multidiscip. Res. Stud., 2022, 2, 1–10.

3. Akinte O.O.*, Aina T.S., HVAC vs HVDC power system: Contemporary development in HVAC and HVDC power transmission system. Int. J. Sci. Technol. Res., 2021, 19, 252–261.

4. Aina T.S.*, Akinte O.O., Iyaomolere B.A., Investigation on performance of microstrip patch antenna for a practical wireless local area network (WLAN) application. Int. J. Res. Appl. Sci. Eng. Technol. (IJRASET), 2022, 10, 221–226.

5. Aina T.S.*, Akinte O.O., Iyaomolere B., Tosin A.E., Abode I.I., Awelewa A.J., Implementation of an intelligent motion detector. Int. Res. J. Eng. Technol. (IRJET), 2022, 9(1), 1148–1165.

Muhammad Yousaf Iqbal | Optimization | Best Scholar Award

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Dr. Muhammad Yousaf Iqbal | Optimization | Best Scholar Award

Research Assistant at Zhejiang University of Technology, China

Dr. Muhammad Yousaf Iqbal is a Mechanical Engineer and Postdoctoral Researcher at Zhejiang University of Technology, specializing in vibration-based virtual sensors, RCCI engines, renewable energy systems, and advanced combustion monitoring. He earned his Ph.D. in Mechanical Engineering from Taiyuan University of Technology, with expertise spanning vehicle engineering, automotive design, vibration analysis, and energy regenerative systems. His research portfolio includes projects on hydrogen–diesel RCCI engines, methanol-blended fuels, and regenerative hydraulic electromagnetic shock absorbers, demonstrating a strong link between academic innovation and industrial application. He has authored more than 18 peer-reviewed articles in Q1–Q3 SCI/Scopus indexed journals, co-authored a technical book, and contributed as a reviewer and editorial member with IEEE. With over 230 citations, leadership in international collaborations, and active involvement in student organizations, he continues to advance sustainable automotive and mechanical research globally.

Professional Profile

Google Scholar 

Education

Dr. Muhammad Yousaf Iqbal completed his Ph.D. in Mechanical Engineering from Taiyuan University of Technology, focusing on vibration-based virtual sensors, RCCI engines, and sustainable energy systems. His doctoral research centered on combustion monitoring and virtual sensing technologies to enhance efficiency and reduce emissions in advanced engines. Prior to his Ph.D., he built a strong academic foundation in mechanical and automotive engineering, acquiring expertise in thermodynamics, heat transfer, and mechanical design. His academic training combined rigorous theoretical studies with practical industrial exposure, enabling him to develop advanced problem-solving skills and interdisciplinary knowledge. The breadth of his education reflects a commitment to combining innovation with real-world applications, laying the groundwork for his postdoctoral research at Zhejiang University of Technology and his continuous contributions to mechanical and energy engineering fields.

Experience

Dr. Muhammad Yousaf Iqbal possesses extensive academic, research, and industrial experience, combining over seven years of professional engagement across mechanical and automotive domains. As a Postdoctoral Researcher at Zhejiang University of Technology, he contributes to international collaborations and innovative research projects in vibration analysis, RCCI engines, and regenerative systems. His prior involvement includes doctoral research in advanced combustion systems and hands-on training with Dayun Truck Industry in vehicle design and assembly. He has successfully balanced teaching, mentoring, and supervising student research while actively contributing to the scientific community as a reviewer and editorial board member with IEEE. His experience demonstrates the ability to integrate academic rigor with industrial applications, ensuring impactful outcomes in automotive design, renewable energy solutions, and mechanical engineering innovations with strong global relevance.

Research Interest

Dr. Muhammad Yousaf Iqbal’s research interests span vibration-based virtual sensing, advanced combustion technologies, and sustainable energy systems. He specializes in the optimization of RCCI engines through alternative fuels, including hydrogen, diesel, and methanol blends, aiming to improve efficiency while reducing emissions. His work extends to developing energy regenerative hydraulic electromagnetic shock absorbers that contribute to energy recovery in vehicles, as well as projects involving automotive design, vehicle dynamics, and propulsion systems. He is equally engaged in mechanical design, thermodynamics, heat transfer, and composite materials, ensuring a multidisciplinary approach to innovation. His research bridges the gap between theory and practice, contributing to both academic advancements and industrial solutions. These interests reflect his long-term vision of fostering sustainable technologies for cleaner and more efficient mechanical and automotive engineering applications.

Award and Honor

Dr. Muhammad Yousaf Iqbal has been recognized for his significant contributions to research and innovation through multiple awards and honors. He has published more than 18 peer-reviewed articles in Q1–Q3 SCI/Scopus indexed journals, a recognition of his scientific rigor and dedication to impactful research. His academic achievements are complemented by international collaborations with prestigious research groups, earning him acknowledgment within the global research community. He co-authored a technical book on 3D Mechanical Design, which highlights his dedication to advancing engineering knowledge. His involvement with IEEE as an editorial member further adds to his professional recognition. These distinctions reflect his excellence in research, teaching, and leadership, underscoring his growing influence in mechanical and energy engineering while reinforcing his potential for continued recognition in future academic and professional endeavors.

Research Skill

Dr. Muhammad Yousaf Iqbal demonstrates advanced research skills in mechanical design, vibration analysis, thermodynamics, and combustion monitoring. He is proficient in developing vibration-based virtual sensors, enabling cost-effective real-time monitoring of NOx emissions in diesel and RCCI engines. His expertise includes experimental design, computational modeling, and data analysis for automotive and energy systems. Skilled in working with renewable and alternative fuels, he has contributed to optimizing hydrogen–diesel RCCI engines and investigating methanol fuel blends. He combines theoretical understanding with practical engineering skills, integrating design, manufacturing, and simulation to deliver innovative solutions. His cross-cultural collaboration experience and project management abilities strengthen his role in international research projects. With a strong publication record and editorial contributions, he possesses the technical, analytical, and leadership skills essential for advancing mechanical and automotive research.

Publication Top Notes

  • Title: A double-channel hybrid deep neural network based on CNN and BiLSTM for remaining useful life prediction
    Authors: C Zhao, X Huang, Y Li, M Yousaf Iqbal
    Year: 2020
    Citation: 119

  • Title: A fractional Whitham-Broer-Kaup equation and its possible application to tsunami prevention
    Authors: Y Wang, YF Zhang, ZJ Liu, M Iqbal
    Year: 2017
    Citation: 23

  • Title: A study of advanced efficient hybrid electric vehicles, electric propulsion and energy source
    Authors: MY Iqbal, T Wang, G Li, D Chen, MM Al-Nehari
    Year: 2022
    Citation: 16

  • Title: Development and Validation of a Vibration-Based Virtual Sensor for Real-Time Monitoring NOx Emissions of a Diesel Engine
    Authors: MY Iqbal, T Wang, G Li, S Li, G Hu, T Yang, F Gu, M Al-Nehari
    Year: 2022
    Citation: 15

  • Title: A short review on analytical methods for fractional equations with He’s fractional derivative
    Authors: Y Wang, YF Zhang, JG Liu, M Iqbal
    Year: 2017
    Citation: 15

  • Title: Investigation of accumulator main parameters of hydraulic excitation system
    Authors: Z Wu, Y Xiang, M Li, MY Iqbal, G Xu
    Year: 2019
    Citation: 13

  • Title: Study of external characteristics of hydraulic electromagnetic regenerative shock absorber
    Authors: MY Iqbal, Z Wu, G Xu, SA Bukhari
    Year: 2019
    Citation: 7

  • Title: A High-Efficiency Energy Harvesting by Using Hydraulic Electromagnetic Regenerative Shock Absorber
    Authors: MY Iqbal, Z Wu, W Tie, G Li, J Zhiyong, H GuiCheng
    Year: 2020
    Citation: 6

  • Title: Improving the effect of air chambers on micro-pressure waves from tunnel portals: Moderate underdamping
    Authors: F Liu, H Lei, M Wei, H Sun, MY Iqbal, D Chen
    Year: 2024
    Citation: 5

  • Title: A Triboelectric Piston–Cylinder Assembly with Condition‐Monitoring and Self‐Powering Capabilities
    Authors: G Li, H Wu, R Guo, H Zhang, L Li, MY Iqbal, F Gu
    Year: 2022
    Citation: 4

  • Title: Grinding mechanism of high-temperature nickel-based alloy using FEM-FBM technique
    Authors: M Al-Nehari, G Liang, L Ming, W Yahya, A Algaradi, MY Iqabal
    Year: 2021
    Citation: 4

  • Title: Cavitation Failure Analysis of Cylinder Liner in Diesel Engines Caused by Increased Combustion Pressure
    Authors: P Liu, R Tan, L Li, W Shi, J Chen, MY Iqbal, D Liu, G Li
    Year: 2024
    Citation: 1

  • Title: Combustion Parametric Investigations of Methanol-Based RCCI Internal Combustion Engine and Comparison with the Conventional Dual Fuel Mode
    Authors: MY Iqbal, T Wang, GX Li, W Ali
    Year: 2023
    Citation: 1

  • Title: Performance comparison of switching losses of SiC DMOS vs Si IGBT
    Authors: SA Bukhari, H Zhang, SH Bukhari, MY Iqbal
    Year: 2020
    Citation: 1

  • Title: Impact of Fischer-Tropsch diesel and methanol blended fuel on diesel engine performance
    Authors: Z Wu, T Wang, P Zuo, MY Iqbal
    Year: 2019
    Citation: 1

Conclusion

Dr. Muhammad Yousaf Iqbal stands out as an accomplished researcher whose work bridges academic innovation and industrial application. His expertise in vibration-based virtual sensing, RCCI engine optimization, and regenerative energy systems has contributed to advancements in sustainable automotive engineering. With extensive publications, international collaborations, and leadership in professional organizations, he has established himself as a rising figure in global research. His dedication to mentoring students, engaging in cross-disciplinary projects, and contributing as a reviewer and editorial member reflects both academic excellence and community involvement. Beyond his current achievements, he holds strong potential to lead pioneering projects that shape future technologies in clean energy and advanced mechanical systems. These contributions affirm his suitability for recognition, positioning him as a deserving candidate for prestigious research awards.

 

Seyed Mehdi Tavakkoli | Optimization | Best Researcher Award

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Assoc. Prof. Dr. Seyed Mehdi Tavakkoli | Optimization | Best Researcher Award

Associate Professor at Shahrood University of Technology, Iran

Dr. Seyed Mehdi Tavakkoli is a distinguished scholar in structural and computational engineering 🏗️📊, serving as Associate Professor at Shahrood University of Technology, Iran. With a Ph.D. in Civil Engineering – Structures from Iran University of Science & Technology 🎓, he has pioneered research in isogeometric analysis, structural topology optimization, and continuum mechanics. His prolific academic career includes over 30 peer-reviewed journal publications 📝, mentorship of MSc and Ph.D. students, and international collaboration at the University of Bath, UK 🌍. Dr. Tavakkoli is highly skilled in MATLAB, Python, and leading structural software tools 💻, blending theory with practical applications. His innovative contributions to damage detection, shape optimization, and smart materials position him as a leading voice in modern civil engineering 🔍🏅. He is deeply committed to advancing research, education, and global knowledge exchange.

Professional Profile 

Google Scholar
Scopus Profile
ORCID Profile

🎓 Education

Dr. Seyed Mehdi Tavakkoli holds a Ph.D. in Civil Engineering – Structures from Iran University of Science & Technology 🎓, where he specialized in isogeometric analysis and topology optimization using NURBS basis functions. Guided by renowned experts like Prof. Behrooz Hassani and Prof. Ali Kaveh, his dissertation laid the foundation for integrating computational geometry with structural optimization. His education blends strong mathematical rigor, numerical methods, and engineering design 🧠📐. Earlier degrees were equally grounded in high academic achievement, with a consistent focus on advanced mechanics and structural systems. His academic journey demonstrates a fusion of innovation and precision, making him an expert in structural modeling, finite elements, and smart structural systems. Dr. Tavakkoli’s education has positioned him as a forward-thinking engineer capable of solving complex multi-scale problems 🏗️🔍.

📊Professional Experience

Dr. Tavakkoli has over 15 years of academic and international research experience. He currently serves as an Associate Professor in the Civil Engineering Department at Shahrood University of Technology 🏛️, where he teaches undergraduate and postgraduate courses in structural analysis, finite element methods, and optimization. From 2013–2014, he worked as a Research Associate at the University of Bath, UK 🇬🇧, where he developed nonlinear models of piezoelectric-bistable laminates for energy harvesting. His teaching record is distinguished by the design of curricula focused on mechanics, computational methods, and structural systems. He has supervised numerous MSc and PhD theses, bringing theoretical insight into practical applications 📘👨‍🔧. His professional journey reflects a balanced commitment to academic excellence, innovation, and global collaboration 🌍📊.

🔬 Research Interests

Dr. Tavakkoli’s research lies at the intersection of computational mechanics, structural optimization, and smart materials. He specializes in isogeometric analysis, finite element modeling, and topology optimization of structures, particularly for energy-efficient and damage-tolerant design systems 🧮⚙️. His recent studies include multiscale modeling, couple stress theory, level-set methods, and elastoplastic material behavior in structural systems. He has also contributed to damage detection using time-domain responses and modal expansion methods. His work is regularly published in high-impact journals like Engineering with Computers, Computer-Aided Design, and Finite Elements in Analysis and Design 📑📈. Passionate about integrating theory and real-world solutions, his research advances fields such as additive manufacturing, structural health monitoring, and sustainable civil engineering systems 🌱🏗️.

🏅 Awards and Honors

Dr. Tavakkoli’s sustained contributions to civil and structural engineering have earned him recognition as a prolific researcher in computational design and optimization. While formal award titles are not explicitly listed, his continuous publication in top-tier international journals and collaborations with leading institutions, including the University of Bath, reflect his scholarly impact 🏆🌍. His research papers—cited widely in structural optimization and computational mechanics—have influenced both academia and industry. His role as a supervisor and project leader in complex optimization frameworks also underlines his academic leadership. The innovative nature of his work in isogeometric topology optimization is gaining increasing recognition across structural engineering circles, positioning him as a thought leader in the evolving landscape of smart and sustainable design systems 🧠🛠️.

🛠️ Research Skills

Dr. Tavakkoli possesses deep expertise in structural modeling, numerical methods, and advanced optimization techniques. He is proficient in programming languages such as MATLAB, Python, Visual Fortran, and Visual Basic 👨‍💻. His computational skillset includes structural analysis software like ETABS, SAP2000, and SAFE, alongside core platforms like AutoCAD and MS Office. His research utilizes isogeometric and finite element methods, multiscale modeling, and optimization algorithms including ant colony and level-set techniques 🔄📊. His capabilities also extend to damage detection and nonlinear modeling of smart materials. This combination of practical software fluency and high-level theoretical modeling makes him highly adaptable for modern engineering challenges—especially in the development of smart, safe, and efficient structural systems ⚡🏗️.

📝Publications Top Note

  • Title: Structural topology optimization using ant colony methodology
    Authors: A. Kaveh, B. Hassani, S. Shojaee, S.M. Tavakkoli
    Year: 2008
    Citations: 210
    Source: Engineering Structures, 30(9), 2559–2565

  • Title: An isogeometrical approach to structural topology optimization by optimality criteria
    Authors: B. Hassani, M. Khanzadi, S.M. Tavakkoli
    Year: 2012
    Citations: 169
    Source: Structural and Multidisciplinary Optimization, 45(2), 223–233

  • Title: Simultaneous shape and topology optimization of shell structures
    Authors: B. Hassani, S.M. Tavakkoli, H. Ghasemnejad
    Year: 2013
    Citations: 100
    Source: Structural and Multidisciplinary Optimization, 48(1), 221–233

  • Title: An isogeometrical approach to structural level set topology optimization
    Authors: H.A. Jahangiri, S.M. Tavakkoli
    Year: 2017
    Citations: 88
    Source: Computer Methods in Applied Mechanics and Engineering, 319, 240–257

  • Title: Application of isogeometric analysis in structural shape optimization
    Authors: B. Hassani, S.M. Tavakkoli, N.Z. Moghadam
    Year: 2011
    Citations: 74
    Source: Iranian Science, 18(4), 846–852

  • Title: An isogeometrical approach to error estimation and stress recovery
    Authors: B. Hassani, A. Ganjali, M. Tavakkoli
    Year: 2012
    Citations: 37
    Source: European Journal of Mechanics A: Solids, 31(1), 101–109

  • Title: Isogeometric shape optimization of three dimensional problems
    Authors: B. Hassani, M. Khanzadi, S.M. Tavakkoli, N.Z. Moghadam
    Year: 2009
    Citations: 33
    Source: 8th World Congress on Structural and Multidisciplinary Optimization, 1–5

  • Title: Isogeometric topology optimization of structures by using MMA
    Authors: S.M. Tavakkoli, B. Hassani, H. Ghasemnejad
    Year: 2013
    Citations: 27
    Source: International Journal of Optimization in Civil Engineering, 3(2), 313–326

  • Title: Free vibration of functionally graded thick circular plates: An exact and three-dimensional solution
    Authors: M.Z. Roshanbakhsh, S.M. Tavakkoli, B.N. Neya
    Year: 2020
    Citations: 25
    Source: International Journal of Mechanical Sciences, 188, 105967

  • Title: Structural damage detection in plane stress problems by using time domain responses and topology optimization
    Authors: F. Damghani, S.M. Tavakkoli
    Year: 2023
    Citations: 2
    Source: International Journal of Optimization in Civil Engineering (IJOCE), 13(2)

  • Title: An analytical study on piezoelectric-bistable laminates with arbitrary shapes for energy harvesting
    Authors: S.M. Tavakkoli, P.M. Weaver, C.R. Bowen, D.J. Inman, H. Alicia
    Year: 2015
    Citations: 2
    Source: [Not specified, likely conference proceedings or journal]

  • Title: Topology optimization of space structures using ant colony method
    Authors: S.M. Tavakkoli, L. Shahryari, A. Parsa
    Year: 2013
    Citations: 2
    Source: International Journal of Optimization in Civil Engineering, 3(3), 359–370

  • Title: Channels flow modeling by using isogeometric analysis
    Authors: R. Amini, R. Maghsoodi, N.Z. Moghaddam, S.M. Tavakkoli
    Year: 2016
    Citations: 1
    Source: Journal of Solid and Fluid Mechanics, 5(4)

  • Title: Size-dependent topology optimization for eigenfrequency maximization of microplates using consistent couple stress theory
    Authors: M.Z. Roshanbakhsh, S.M. Tavakkoli
    Year: 2025
    Source: Advances in Engineering Software, 206, 103941

🧾 Conclusion

Dr. Seyed Mehdi Tavakkoli exemplifies a rare blend of academic depth, technical precision, and forward-thinking research in structural engineering. With over three decades of cumulative experience across teaching, research, and international collaboration, he has become a key contributor to the evolving landscape of computational civil engineering 📘🌐. His isogeometric approach, grounded in rigorous mathematics and real-world applications, continues to influence emerging scholars and professionals alike. Whether through supervising doctoral candidates, publishing high-impact research, or exploring optimization in additive manufacturing, his work consistently pushes the boundary of what’s possible in engineering design. Dr. Tavakkoli stands out not only as a researcher but as a mentor, innovator, and thought leader of 21st-century structural systems 🏅🚀.

Binghao OuYang | Optimization | Best Researcher Award

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Dr. Binghao OuYang | Optimization | Best Researcher Award

Research assistant at City University of Hong Kong, China

Dr. OuYang Binghao (欧阳炳濠) is a promising early-career researcher specializing in game theory and distributed Nash equilibrium seeking algorithms ⚙️📊. Currently pursuing a joint PhD at City University of Hong Kong and University of Science and Technology of China, he holds a strong academic record with a GPA of 3.78/4.3 🎓. His research focuses on fixed-time convergence algorithms for complex control systems, with practical applications in non-cooperative games and Euler-Lagrange systems 🔍🤖. Dr. OuYang has earned several awards, including a gold medal at the National College Student Innovation Competition 🥇 and recognition as an outstanding undergraduate graduate. Skilled in Python, C++, and Matlab, he also applies reinforcement and deep learning techniques to advance his research 💻🧠. With a solid mathematical foundation and innovative approach, Dr. OuYang is a rising talent in control science and engineering, poised to make significant contributions to his field.

Professional Profile 

🎓 Education

Dr. OuYang Binghao (欧阳炳濠) has pursued a rigorous academic path in engineering and control science. He earned his Bachelor’s degree in Automation from the University of Science and Technology of China (USTC) (2016–2020) 🎯, followed by PhD studies in Control Science and Engineering (2020–2022) with a GPA of 3.50/4.3 📚. Currently, he is completing a Joint PhD in Biomedical Engineering and Control Science at City University of Hong Kong and USTC, maintaining an impressive GPA of 3.78/4.3 🏅. Guided by Professors Feng Gang and Wang Yong, his education blends theoretical depth with applied research, equipping him to tackle complex engineering challenges across interdisciplinary domains 🎓🔬.

💼 Professional Experience

Dr. OuYang has demonstrated practical innovation from early in his academic career. In 2020, his excellent undergraduate graduation project involved the development of a fingerprint attendance system 🛠️. Later, in 2021, he participated in the China International College Students Innovation Competition, helping design a motion perception and high-precision positioning system, which won a gold award 🥇. From 2022–2023, he conducted research at City University of Hong Kong focused on distributed Nash equilibrium seeking in non-cooperative games 🤝📈. His hands-on experience bridges theoretical modeling and real-world applications, showcasing a promising blend of technical creativity and research diligence 💡🧪.

🔬 Research Interest

Dr. OuYang’s core research areas include game theory, distributed Nash equilibrium algorithms, and fixed-time convergence strategies for control systems 📐⚙️. He is particularly focused on solving equilibrium-seeking problems in constrained and dynamic non-cooperative games, as well as Euler-Lagrange systems 🔄🧠. With expertise in reinforcement learning, deep learning, and optimization, his work integrates modern computational tools to address long-standing challenges in control science 🚀. His interest in convergence algorithms extends to real-time systems, offering broad applications in autonomous systems, multi-agent robotics, and decentralized networks 🤖🌐. His work is driven by a strong mathematical foundation and a vision for robust and scalable algorithm design 📊🧮.

🏆 Awards and Honors

Dr. OuYang has received multiple honors reflecting both academic excellence and innovation 🏅. He earned the Outstanding Undergraduate Graduate award from USTC in 2020, recognizing his stellar academic performance 🎓. His graduation project was named an Excellent Graduation Project, and he secured First-Class Graduate Scholarships in both 2020 and 2021 💸. In 2021, he won a Gold Award in the National College Student Innovation Competition for his contributions to a motion perception and positioning system 🥇. Earlier, in 2019, he received the Second Prize in the NXP Cup Intelligent Car Competition 🚗. These recognitions affirm his technical competence, creativity, and dedication to impactful research and development.

💼📘Conclusion

Dr. OuYang Binghao stands out as a dynamic and skilled researcher, combining academic excellence with practical innovation 💼📘. With a strong educational background, impactful project work, and research in high-impact areas such as game theory and fixed-time algorithms, he exhibits the qualities of a future leader in engineering and control systems 🧭. His proficiency in programming, AI integration, and control dynamics, along with international research exposure, positions him as a valuable contributor to the global research community 🌍. Dr. OuYang’s trajectory reflects not only promise but also a clear commitment to solving critical real-world problems through mathematics, computation, and collaborative research 🤝🔬..

Publication Top Notes

Title: Vertically Oriented Micron-Thick Perovskite Film Enables Efficient and Stable Inverted Perovskite Solar Cells

Authors: Bing-Hao Lv, Yong-Chun Ye, Jun-Gan Wang, Liu-Jiang Zhang, Yu-Hang Zhang, Ming-Li Zheng, Xian-Min Chen, Hui-Wei Du, Jie Yang, Xin-Yu Zhang, Meng-Lei Xu, Qiu-Feng Ye, Xingyu Gao, Jian-Xin Tang, Yongbing Tang

Year: 2025

Source: Chemical Engineering Journal, Volume 511, Article 161966CoLab

DOI: 10.1016/j.cej.2025.161966

Citation Metrics:

 

 

Saeed Farsad | Optimization | Excellence in Research

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Dr. Saeed Farsad | Optimization | Excellence in Research

Assistant Professor at Birjand University of Technology, Iran

Dr. Saeed Farsad is an accomplished researcher and academic with expertise in experimental fluid dynamics, renewable energy, and heat transfer. He holds a Ph.D. in Mechanical Engineering from the Iranian Research Organization for Science and Technology (IROST) and has extensive experience in wind/water tunnel testing, aerodynamics, and energy conversion systems. Currently serving as an Assistant Professor at Birjand University of Technology (BUT), he has published numerous high-impact journal articles in Q1 and Q2-ranked journals, focusing on vortex shedding, energy storage, and thermo-fluidic properties. His research contributions extend beyond academia, including patents, award papers, and a book on solar desalination. With international collaborations at Toronto Metropolitan University and York University, Dr. Farsad has strengthened his global research footprint. Recognized as an Elective Researcher of the Province, his work has significant industrial and academic applications, making him a prominent figure in mechanical and applied engineering sciences.

Professional Profile 

Google Scholar
Scopus Profile
ORCID Profile

Education

Dr. Saeed Farsad holds a Ph.D. in Mechanical Engineering from the Iranian Research Organization for Science and Technology (IROST), specializing in experimental fluid dynamics, wind/water tunnel tests, and advanced measurement techniques. He completed his M.Sc. in Mechanical Engineering – Energy Conversion at the University of Sistan & Baluchestan, where he focused on solar desalination, heat transfer, and numerical simulations. His B.Sc. in Automotive Technology from the Technical College of Mashhad provided a strong foundation in vehicle systems, transmission lines, and automotive engineering. His academic journey showcases a deep multidisciplinary approach, integrating energy systems, experimental fluid mechanics, and automotive applications. With supervisors from renowned institutions, his education has been instrumental in shaping his expertise in thermo-fluid sciences and renewable energy applications. His ability to blend theoretical knowledge with practical applications has led to impactful research contributions, journal publications, and patented innovations in mechanical and automotive engineering.

Professional Experience

Dr. Saeed Farsad has over a decade of professional experience, combining academic research, teaching, and industry involvement. He is currently an Assistant Professor at Birjand University of Technology (BUT), where he teaches courses in fluid mechanics, statics, technical drawing (CATIA), and automotive technology. His international exposure includes a Visiting Assistant Professorship at Toronto Metropolitan University (TMU) and a Research Assistant position at York University, where he contributed to energy storage and fluid mechanics research. Beyond academia, Dr. Farsad has worked in the automotive industry, including roles at Toyota Motor Manufacturing Canada (TMMC) and Mechatronic Diagnostic Inc., where he gained hands-on experience in diagnostics and assembly line operations. His expertise spans experimental fluid flow measurement, energy systems, and mechanical design, making him a versatile researcher and educator with a unique blend of theoretical and applied engineering knowledge.

Research Interest

Dr. Saeed Farsad’s research interests lie in experimental fluid dynamics, renewable energy, and heat transfer. His work focuses on vortex shedding, aerodynamics, and thermo-fluidic properties, with applications in wind and water tunnel experiments. He has also made significant contributions to solar desalination, adsorption-based energy storage, and magnetic nanofluid heat transfer. His interdisciplinary research integrates advanced experimental techniques such as Particle Image Velocimetry (PIV), Laser Doppler Velocimetry (LDV), and Hot-Wire Anemometry (HWA) to enhance the understanding of fluid flow and heat exchange mechanisms. In addition, Dr. Farsad explores automotive aerodynamics, energy-efficient HVAC systems, and turbulence modeling, bridging the gap between engineering applications and sustainable energy solutions. His collaborations with international researchers in Canada and Iran further strengthen his impact in the global scientific community, ensuring that his research contributes to both theoretical advancements and industrial applications.

Awards and Honors

Dr. Saeed Farsad has received several awards and recognitions for his contributions to mechanical engineering and applied sciences. He was honored as the Elective Researcher of the Province in 2011, recognizing his pioneering research in fluid mechanics and energy systems. His academic excellence is reflected in his third-place ranking in Associate Graduate Courses at Mashhad Technical College and his 16th rank among 6,000 applicants in the B.Sc. Automotive Mechanics Entrance Exam. His innovative research has led to multiple patents, including a Smart Filter equipped with an alarm system and a device for the collection and separation of machine tool waste. With publications in high-impact journals and invitations to prestigious international awards, Dr. Farsad’s achievements highlight his significant contributions to engineering innovation and scientific advancements.

Conclusion

Dr. Saeed Farsad is a highly accomplished researcher, educator, and engineer with expertise in experimental fluid dynamics, renewable energy, and heat transfer. His strong academic background, diverse professional experience, and impactful research contributions make him a leading figure in mechanical engineering. His ability to integrate theoretical research with practical applications has resulted in high-impact journal publications, patents, and industrial collaborations. His work in aerodynamics, solar desalination, and energy storage has broad implications for sustainable engineering and environmental solutions. With international research experience and teaching roles in Canada and Iran, Dr. Farsad has established himself as a global expert in his field. His dedication to scientific excellence and innovation positions him as a strong candidate for prestigious research awards, reinforcing his influence in the engineering and academic communities worldwide.

Publications Top Noted

 

Farshid Dehghan | Optimization | Best Researcher Award

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Dr. Farshid Dehghan | Optimization | Best Researcher Award

Doctoral Researcher at Universidad Politécnica de Madrid, Iran

Farshid Dehghan is a dedicated Building Energy Performance Analyst with expertise in simulation-based optimization, energy efficiency, and machine learning applications. He is affiliated with Escuela Técnica Superior de Edificación, Universidad Politécnica de Madrid, Spain, where he focuses on sustainable building solutions. His research includes optimizing building retrofits in Iran to improve energy consumption, emissions reduction, comfort, and indoor air quality in the face of climate change. He is currently working on predicting energy consumption and emissions using machine learning approaches, reflecting his innovative mindset in data-driven sustainability. His scholarly contributions include a publication in the Sustainability journal, showcasing his ability to address real-world energy challenges. While his research impact is growing, expanding his indexed publications, securing patents, and increasing industry collaborations could further enhance his profile. With his commitment to sustainable energy solutions, Farshid Dehghan is a promising researcher in the field of building energy performance and smart optimization techniques.

Professional Profile 

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Education

Farshid Dehghan is affiliated with Escuela Técnica Superior de Edificación, Universidad Politécnica de Madrid, Spain, where he has built a strong academic foundation in building energy performance, sustainable design, and simulation-based optimization. His educational background is deeply rooted in engineering and environmental sustainability, equipping him with the necessary skills to tackle challenges related to energy efficiency, emissions control, and indoor air quality. His studies have provided him with expertise in machine learning applications for energy prediction and optimization, making him a forward-thinking researcher in the field. Throughout his academic journey, he has developed a strong analytical approach and a problem-solving mindset, allowing him to apply innovative methodologies to complex building energy problems. His educational background has played a crucial role in shaping his research focus, emphasizing the intersection of technology, energy efficiency, and sustainability, which forms the core of his work in simulation-based multi-objective optimization.

Professional Experience

Farshid Dehghan is a Building Energy Performance Analyst with expertise in sustainable building solutions, energy efficiency modeling, and simulation-based optimization techniques. His professional experience includes research on building retrofits in Iran, where he focuses on optimizing energy consumption, minimizing emissions, and improving occupant comfort while considering climate change impacts. His work integrates machine learning and data-driven approaches to predict energy consumption and emissions, demonstrating his strong analytical and computational skills. Through his research, he has gained experience in working with building simulation software, optimization tools, and statistical modeling techniques. His role requires him to analyze real-world building performance, propose effective retrofit solutions, and contribute to the advancement of energy-efficient building designs. Additionally, his work in academic publishing and industry-related consultancy projects has enabled him to apply his research to practical applications, making him a valuable asset in the field of sustainable building energy performance.

Research Interest

Farshid Dehghan’s research primarily focuses on building energy performance, simulation-based optimization, and machine learning applications in sustainability. He is particularly interested in multi-objective optimization for energy-efficient building retrofits, aiming to reduce energy consumption, minimize emissions, and enhance indoor air quality while ensuring occupant comfort. His work extends to predictive modeling using machine learning techniques, where he applies advanced algorithms to forecast energy usage patterns and environmental impacts. Additionally, he is exploring the integration of smart building technologies to develop data-driven strategies for optimizing building operations. His research aligns with global efforts to combat climate change by promoting energy-efficient and low-carbon building solutions. He is also interested in developing policy-driven strategies for sustainable urban environments, collaborating with experts across disciplines to create innovative frameworks for energy management and optimization. His research contributions reflect his commitment to sustainability and technological innovation in the built environment.

Awards and Honors

Farshid Dehghan’s contributions to building energy performance research have positioned him as a promising researcher in his field. While he is in the early stages of his career, his publication in the Sustainability journal and ongoing research projects demonstrate his growing impact. His work in simulation-based optimization for building retrofits has gained recognition, and as he continues to expand his research, he is likely to attract more academic and industry accolades. By securing indexed journal publications, patents, and industry collaborations, he has the potential to achieve prestigious honors in sustainable building research. His dedication to improving energy efficiency and indoor air quality aligns with global sustainability goals, making him a strong candidate for future research awards. As he continues to contribute to innovative energy solutions, his work is expected to receive further recognition in academic, industry, and policy-making circles.

Conclusion

Farshid Dehghan is a dedicated researcher and analyst specializing in building energy performance, sustainable design, and machine learning-driven energy optimization. His work addresses critical challenges in energy efficiency, emissions reduction, and occupant comfort, making significant contributions to the field of sustainable built environments. While his research is gaining traction, further expansion in indexed journal publications, patents, and industry partnerships will strengthen his profile. His expertise in simulation-based optimization and predictive modeling demonstrates his forward-thinking approach to sustainability. As he continues his research, his contributions will play a vital role in shaping the future of energy-efficient building solutions. His strong technical background, research-driven mindset, and commitment to innovation make him a valuable asset in the pursuit of sustainable and climate-resilient building technologies.

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Zohaib Khan | Optimization | Best Researcher Award

Published on by Math Scientist

Dr. Zohaib Khan | Optimization | Best Researcher Award

Jiangsu University, China

Zohaib Khan is a dedicated researcher specializing in machine learning, object detection, and control science engineering, with a strong focus on precision agriculture and AI-driven automation. Currently pursuing a PhD at Jiangsu University, China, he has made significant contributions to deep learning-based agricultural robotics, publishing multiple first-author papers in high-impact SCI Q1, Q2, and EI journals. His work emphasizes real-time detection, optimization algorithms, and AI-driven sustainability solutions. With extensive mentoring experience (50+ Bachelor’s and 10 Master’s students), he has played a key role in academic development. Zohaib has received numerous national and international awards, including first prizes in elite research and innovation competitions. His technical expertise spans Python, MATLAB, LaTeX, and AI-driven modeling, complementing his ability to lead interdisciplinary research. With a passion for advancing AI applications in agriculture, he continues to drive innovation in sustainable and automated farming solutions.

Professional Profile 

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Scopus Profile
ORCID Profile

Education

Zohaib Khan is currently pursuing a PhD in Control Science Engineering at Jiangsu University, China (2022–2026), specializing in machine learning and object detection. He previously earned an MSc in Electrical Engineering (2019–2022) from the same institution, focusing on power systems and renewable energy. His Bachelor’s degree in Electrical Power Engineering (2013–2017) from Swedish College of Engineering and Technology, Pakistan, laid the foundation for his technical expertise. His early academic years were marked by excellence, having completed Pre-Engineering at Fazaia Degree College (2011–2013) and his Secondary School Certificate (2009–2011) at Agricultural University Public School. Zohaib’s academic journey is distinguished by his strong analytical skills and passion for integrating AI and automation in engineering solutions. His education reflects a deep commitment to advanced research, innovation, and interdisciplinary problem-solving, positioning him as a future leader in AI-driven technologies and precision agriculture.

Professional Experience

Zohaib Khan has gained substantial experience in both academic research and engineering practice. As an intern at WAPDA, Pakistan, he developed hands-on expertise in power distribution and transmission lines, strengthening his understanding of grid operations and maintenance. Later, as an Electrical Engineer at LIMAK (JV) ZKB – CPEC Project (2017–2018), he contributed to electrical system design, installation, and maintenance, gaining valuable project management experience. His role involved troubleshooting, safety compliance, and interdisciplinary collaboration, enhancing his problem-solving capabilities. In academia, Zohaib has mentored over 50 Bachelor’s and 10 Master’s students, guiding them through research projects in machine learning, object detection, and automation. His strong writing, teaching, and IT skills have been instrumental in fostering innovation. His diverse experience, spanning applied research and engineering implementation, makes him a well-rounded professional capable of driving breakthroughs in AI-powered automation and precision agriculture.

Research Interest

Zohaib Khan’s research focuses on machine learning, deep learning, object detection, and AI-driven automation, with applications in precision agriculture and robotics. His studies revolve around real-time detection, optimization algorithms, and advanced control systems for agricultural sustainability and industrial automation. He has pioneered AI-driven precision farming techniques, developing deep learning-enhanced YOLOv7 and YOLOv8 algorithms for real-time crop health assessment and robotic spraying systems. Additionally, his work explores autonomous navigation in unstructured farmlands, energy-efficient control systems, and reinforcement learning for AI-based decision-making. His research extends to risk assessment in renewable energy systems, contributing to more efficient and resilient smart grids. Through interdisciplinary collaborations, Zohaib continues to push the boundaries of AI in sustainable agriculture, robotics, and industrial automation, aiming to develop intelligent, scalable, and high-impact solutions for modern technological challenges.

Awards and Honors

Zohaib Khan has received multiple prestigious awards recognizing his contributions to research, innovation, and academic excellence. He has won First Prizes in National Competitions, including the China University Business Elite Challenge (2024) and the Brand Planning Competition (2024). His research excellence was acknowledged with the Excellent Paper Award at the Sino-award (2021) and special recognition in Jiangsu Province Graduate Energy-saving and Low-Carbon Research Competition (2023). Additionally, he was honored as an Outstanding Student in the 17th “Yale School of Jiangsu University” program and received a Certificate of Excellence for Teaching Assistance. His leadership and public speaking skills earned him first place in an English debate at Jiangsu University. These accolades reflect his dedication to research, leadership in innovation, and commitment to advancing AI applications in engineering and agriculture, solidifying his reputation as a promising researcher in his field.

Conclusion

Zohaib Khan’s academic, professional, and research journey showcases his exceptional talent in AI-driven automation, machine learning, and precision agriculture. His extensive experience in research, mentoring, and engineering practice positions him as a leading scholar in intelligent agricultural robotics and sustainable AI applications. With a strong publication record in high-impact journals (SCI Q1, Q2, and EI) and multiple national and international awards, he has demonstrated his ability to drive innovation and solve real-world problems. His work in deep learning-based automation and AI-driven optimization techniques continues to push the boundaries of technology for sustainability and efficiency. As he progresses in his career, Zohaib remains committed to advancing cutting-edge research, fostering academic collaborations, and contributing transformative solutions in AI, robotics, and smart energy systems. His dedication and achievements make him a strong candidate for prestigious research awards and a key contributor to the future of AI in engineering and agriculture.

Publications Top Noted