Safaa Najah Saud Al-Humairi | Optimization | Innovative Research Award

Published on by Math Scientist

Innovative Research Award

Safaa Najah Saud Al-Humairi
Management and Science University, Malaysia

Safaa Najah Saud Al-Humairi
Affiliation Management and Science University
Country Malaysia
Scopus ID 55851376600
Documents 135
Citations 1,993
h-index 27
Subject Area Optimization
Event Math Scientist Awards
ORCID 0000-0001-5978-7651

Safaa Najah Saud Al-Humairi is a researcher affiliated with Management and Science University in Malaysia whose documented scholarly profile is associated with optimization and computationally supported engineering research. The available bibliographic record lists 135 documents, 1,993 citations, and an h-index of 27. These indicators provide a quantitative context for considering the researcher for an Innovative Research Award.

Abstract

This academic recognition profile examines the research record of Safaa Najah Saud Al-Humairi in the context of optimization-oriented scientific work. Recent publications address photovoltaic panel modelling, curved photovoltaic structures, Internet of Things-enabled environmental monitoring, artificial intelligence in materials research, and bioactive nanomaterials. Collectively, these works illustrate interdisciplinary applications of modelling, optimization, computation, and engineering design.

Keywords

  • Optimization
  • Photovoltaic Modelling
  • Computational Techniques
  • Artificial Intelligence
  • Sustainable Energy

Introduction

Optimization research frequently connects mathematical or computational methods with practical engineering objectives. In this profile, the documented publication portfolio includes studies that apply modelling and design approaches to renewable-energy systems and emerging computational applications. The researcherโ€™s Scopus record supplies an additional bibliometric basis for evaluating scholarly activity. [1]

Research Profile

The profile is characterized by 135 indexed documents, 1,993 citations, and an h-index of 27, as supplied for this recognition article. The subject-area designation is Optimization. These bibliometric measures should be interpreted as indicators of publication and citation activity rather than as standalone measures of research quality. [1]

Research Contributions

Recent work demonstrates attention to sustainable photovoltaic engineering. One 2026 study investigates modelling and optimization of curved photovoltaic panels for high-efficiency solar-energy conversion. [2] Another examines a floating curved photovoltaic panel combined with IoT-enabled weather monitoring for river and lake environments. [3] Additional contributions extend toward artificial intelligence and advanced computational techniques in shape memory alloy research, alongside biomedical nanomaterial applications. [4] [5]

Publications

  • Modelling and optimisation of curved photovoltaic panels for high-efficiency solar energy conversion โ€” Next Sustainability, 2026. [2]
  • Design of a Floating Curved Photovoltaic Panel with IoT-Enabled Weather Monitoring for Rivers and Lakes Environments โ€” Al-Khwarizmi Engineering Journal, 2026. [3]
  • The Role of AI and Advanced Computational Techniques in Transforming Shape Memory Alloy Research โ€” book chapter, 2026. [4]
  • Bioactive Nanomaterials: Revolutionizing Biomedical Science โ€” book chapter, 2026.ย [5]

Research Impact

The supplied bibliometric record indicates substantial scholarly visibility, with 1,993 citations and an h-index of 27. The publication themes also connect optimization with renewable energy, environmental monitoring, computational engineering, and biomedical research. Such cross-domain activity may support knowledge transfer between computational methods and applied scientific problems. [1]

Award Suitability

The documented research profile provides relevant evidence for consideration for the Innovative Research Award at the Math Scientist Awards. Its suitability is supported by an established publication and citation record and by recent research addressing optimization, sustainable photovoltaic technologies, IoT monitoring, and advanced computational methods. Final award decisions remain subject to the applicable evaluation criteria and review process.

Conclusion

Safaa Najah Saud Al-Humairiโ€™s research profile combines optimization-oriented scholarship with applied investigations in renewable energy, computational engineering, and emerging scientific technologies. The supplied Scopus indicators and recent publications provide a structured basis for academic recognition and demonstrate a research trajectory relevant to interdisciplinary innovation.

References

  1. Elsevier. (n.d.). Scopus author details: Safaa Najah Saud Al-Humairi, Author ID 55851376600. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=55851376600
  2. Elsevier. (2026). Modelling and optimisation of curved photovoltaic panels for high-efficiency solar energy conversion. Next Sustainability.
    https://doi.org/10.1016/j.nxsust.2026.100495
  3. Al-Khwarizmi Engineering Journal. (2026). Design of a Floating Curved Photovoltaic Panel with IoT-Enabled Weather Monitoring for Rivers and Lakes Environments.
    https://doi.org/10.22153/kej.2026.03.002
  4. IGI Global. (2026). The Role of AI and Advanced Computational Techniques in Transforming Shape Memory Alloy Research.
    https://doi.org/10.4018/979-8-3373-6127-7.ch006
  5. Springer. (2026). Bioactive Nanomaterials: Revolutionizing Biomedical Science.
    https://doi.org/10.1007/978-981-96-8023-8_5
  6. ORCID. (n.d.). Safaa Najah Saud Al-Humairi, ORCID iD 0000-0001-5978-7651.
    https://orcid.org/0000-0001-5978-7651
  7. Math Scientist Awards. (n.d.). Math Scientist Awards.
    mathscientists.com

Sina Samadi Gharehveran | Optimization | Innovative Research Award

Published on by Math Scientist

Innovative Research Award

Sina Samadi Gharehveran
Tabriz Islamic Art University, Iran

Sina Samadi Gharehveran
Affiliation Tabriz Islamic Art University
Country Iran
Scopus ID 57741285600
Documents 21
Citations 367
h-index 11
Subject Area Optimization
Event Math Scientist Awards
ORCID 0000-0001-5442-2485

Sina Samadi Gharehveran is a researcher affiliated with Tabriz Islamic Art University, Iran, whose documented research profile is associated with optimization and computational approaches to complex engineering and scientific problems. The researcher has 21 indexed documents, 367 citations, and an h-index of 11, providing a measurable basis for academic recognition. The profile is considered in the context of the Math Scientist Awards.

Abstract

Sina Samadi Gharehveran’s research profile reflects scholarly activity in optimization, with applications extending to electric vehicles, adaptive cybersecurity, intelligent agricultural diagnosis, and predictive construction materials research. Available bibliographic indicators document 21 research documents, 367 citations, and an h-index of 11. Recent publications demonstrate the application of multi-objective optimization, reinforcement learning, active vision, and interpretable machine-learning techniques to multidisciplinary problems.

Keywords

  • Optimization
  • Multi-objective optimization
  • Electric vehicles
  • Reinforcement learning
  • Artificial intelligence
  • Predictive modeling

Introduction

Optimization research addresses the systematic selection of solutions under defined objectives and constraints. In contemporary computational research, optimization increasingly intersects with artificial intelligence and machine learning to address complex, data-intensive systems. Gharehveran’s recent publication record illustrates this multidisciplinary orientation, particularly through work involving multi-objective optimization and intelligent computational methods. [1]

Research Profile

The research profile is associated with 21 documents indexed in Scopus, 367 citations, and an h-index of 11. These indicators provide quantitative evidence of research dissemination and citation influence within the indexed scholarly literature. The primary subject area identified for the researcher is Optimization, while the publication portfolio shows applications across engineering, cybersecurity, agriculture, and materials-related computational research. [2]

Research Contributions

A notable research direction concerns the optimization of battery quantity and arrangement in electric vehicles through multi-objective optimization. This work addresses a practical engineering design problem in which competing performance considerations must be evaluated systematically. [3] Other recent work applies graph-aware reinforcement learning to adaptive advanced persistent threat hunting in dynamic enterprise networks, demonstrating the relevance of intelligent optimization strategies to cybersecurity environments. [4]

Publications

  • Optimization of the Number of Batteries and their Arrangement in Electric Vehicles Based on Multi-Objective Optimization. Passive Defense, 2026. [3]
  • Graph-Aware Reinforcement Learning for Adaptive APT Threat Hunting in Dynamic Enterprise Networks. Technologies, 2026. [4]
  • RAVA: a robust recurrent active vision agent for plant disease diagnosis under severe environmental noise. Scientific Reports, 2026. [5]
  • Interpretable Prediction of Geopolymer Concrete Compressive Strength Using DBOโ€“CatBoost and SHAP Analysis. Buildings, 2026. [6]

Research Impact

The combination of 367 citations and an h-index of 11 indicates an established level of scholarly visibility within indexed literature. The range of application domains represented in the recent publications also suggests a research approach that connects optimization with practical computational problems. Citation indicators should, however, be interpreted alongside publication quality, disciplinary norms, collaboration patterns, and the characteristics of individual research fields. [2]

Award Suitability

The available profile provides a reasonable scholarly basis for consideration for an Innovative Research Award. The evidence includes measurable citation impact, an established h-index, and recent research addressing optimization and intelligent computational methods in several application areas. The award assessment should consider the complete publication record and applicable evaluation criteria in addition to bibliometric indicators. [1]

Conclusion

Sina Samadi Gharehveran’s documented research profile combines optimization-focused scholarship with interdisciplinary applications involving electric vehicles, cybersecurity, plant disease diagnosis, and predictive materials research. With 21 documents, 367 citations, and an h-index of 11, the profile demonstrates measurable academic impact. Recent publications further indicate engagement with contemporary computational methods, supporting consideration for recognition through the Innovative Research Award.

References

  1. Elsevier. (n.d.). Scopus author details: Sina Samadi Gharehveran, Author ID 57741285600. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57741285600
  2. Scopus. (n.d.). Author metrics and indexed publication record: Sina Samadi Gharehveran. Elsevier.
  3. Passive Defense. (2026). Optimization of the Number of Batteries and their Arrangement in Electric Vehicles Based on Multi-Objective Optimization.
    https://doi.org/10.47176/pd.2026.1490
  4. MDPI. (2026). Graph-Aware Reinforcement Learning for Adaptive APT Threat Hunting in Dynamic Enterprise Networks. Technologies.
    https://doi.org/10.3390/technologies14100624
  5. Nature Portfolio. (2026). RAVA: a robust recurrent active vision agent for plant disease diagnosis under severe environmental noise. Scientific Reports.
    https://doi.org/10.1038/s41598-026-67160-2
  6. MDPI. (2026). Interpretable Prediction of Geopolymer Concrete Compressive Strength Using DBOโ€“CatBoost and SHAP Analysis. Buildings.
    https://doi.org/10.3390/buildings16163326

Fuat Tรผrk | Optimization | Best Researcher Award

Published on by Math Scientist

Assist. Prof. Dr. Fuat Tรผrk | Optimization | Best Researcher Award

Researcher| Gazi University | Turkey

Assist. Prof. Dr. Fuat Tรผrk is a researcher in artificial intelligence, medical image analysis, and machine learning, currently affiliated with Gazi University, Turkey. His research focuses on developing intelligent diagnostic and segmentation models for healthcare applications, including kidney and renal tumor detection, lung opacity analysis, heart disease prediction, and cancer diagnosis. He has contributed to advancing hybrid deep-learning architectures, CNN-based image fusion models, machine learningโ€“driven feature selection, and optimization techniques for clinical decision support systems. Dr. Tรผrkโ€™s work integrates computational modeling with real-world medical datasets, aiming to improve diagnostic accuracy, automate radiological workflows, and support early disease detection. His published works demonstrate a strong interdisciplinary approach bridging mathematics, computer vision, and biomedical engineering, and his studies have been cited widely in the fields of medical imaging and machine learning.

Profiles: Scopus | Orcid | Google Scholar

Featured Publications

  1. Tรผrk, F., Lรผy, M., & BarฤฑลŸรงฤฑ, N. (2020). Kidney and renal tumor segmentation using a hybrid V-Net-based model. Mathematics, 8(10), 1772. Citations: 98

  2. Tรผrk, F. (2023). Analysis of intrusion detection systems in UNSW-NB15 and NSL-KDD datasets with machine learning algorithms. Bitlis Eren รœniversitesi Fen Bilimleri Dergisi, 12(2), 465โ€“477. Citations: 59

  3. Tรผrk, F., & Kรถkver, Y. (2023). Detection of lung opacity and treatment planning with three-channel fusion CNN model. Arabian Journal for Science and Engineering, 49, 2973โ€“2985. Citations: 17

  4. Tรผrk, F. (2024). Investigation of machine learning algorithms on heart disease through dominant feature detection and feature selection. Signal, Image and Video Processing. Citations: 15

  5. Akkur, O. E. E., & Tรผrk, F. (2022). Breast cancer diagnosis using feature selection approaches and Bayesian optimization. Computer Systems Science and Engineering, 45(2), 1017โ€“1031. Citations: 13

Oluwaseun Akinte | Optimization | Best Researcher Award

Published on by Math Scientist

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 photovoltaicโ€“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, 1โ€“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, 252โ€“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, 221โ€“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), 1148โ€“1165.

Muhammad Yousaf Iqbal | Optimization | Best Scholar Award

Published on by Math Scientist

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 hydrogenโ€“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 Q1โ€“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 Scholarย 

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 Iqbalโ€™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 Q1โ€“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 hydrogenโ€“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 Heโ€™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 Pistonโ€“Cylinder Assembly with Conditionโ€Monitoring and Selfโ€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.

ย 

Binghao OuYang | Optimization | Best Researcher Award

Published on by Math Scientist

Dr. Binghao OuYang | Optimization | Best Researcher Award

Research assistant at City University of Hong Kong, China

Dr. OuYang Binghao (ๆฌง้˜ณ็‚ณๆฟ ) is a promising early-career researcher specializing in game theory and distributed Nash equilibrium seeking algorithms โš™๏ธ๐Ÿ“Š. 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 ๐ŸŽ“. His research focuses on fixed-time convergence algorithms for complex control systems, with practical applications in non-cooperative games and Euler-Lagrange systems ๐Ÿ”๐Ÿค–. Dr. OuYang has earned several awards, including a gold medal at the National College Student Innovation Competition ๐Ÿฅ‡ 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 ๐Ÿ’ป๐Ÿง . 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 Profileย 

๐ŸŽ“ Education

Dr. OuYang Binghao (ๆฌง้˜ณ็‚ณๆฟ ) 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) (2016โ€“2020) ๐ŸŽฏ, followed by PhD studies in Control Science and Engineering (2020โ€“2022) with a GPA of 3.50/4.3 ๐Ÿ“š. 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 ๐Ÿ…. 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 ๐ŸŽ“๐Ÿ”ฌ.

๐Ÿ’ผ 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 ๐Ÿ› ๏ธ. 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 ๐Ÿฅ‡. From 2022โ€“2023, he conducted research at City University of Hong Kong focused on distributed Nash equilibrium seeking in non-cooperative games ๐Ÿค๐Ÿ“ˆ. His hands-on experience bridges theoretical modeling and real-world applications, showcasing a promising blend of technical creativity and research diligence ๐Ÿ’ก๐Ÿงช.

๐Ÿ”ฌ Research Interest

Dr. OuYangโ€™s core research areas include game theory, distributed Nash equilibrium algorithms, and fixed-time convergence strategies for control systems ๐Ÿ“โš™๏ธ. He is particularly focused on solving equilibrium-seeking problems in constrained and dynamic non-cooperative games, as well as Euler-Lagrange systems ๐Ÿ”„๐Ÿง . With expertise in reinforcement learning, deep learning, and optimization, his work integrates modern computational tools to address long-standing challenges in control science ๐Ÿš€. His interest in convergence algorithms extends to real-time systems, offering broad applications in autonomous systems, multi-agent robotics, and decentralized networks ๐Ÿค–๐ŸŒ. His work is driven by a strong mathematical foundation and a vision for robust and scalable algorithm design ๐Ÿ“Š๐Ÿงฎ.

๐Ÿ† Awards and Honors

Dr. OuYang has received multiple honors reflecting both academic excellence and innovation ๐Ÿ…. He earned the Outstanding Undergraduate Graduate award from USTC in 2020, recognizing his stellar academic performance ๐ŸŽ“. His graduation project was named an Excellent Graduation Project, and he secured First-Class Graduate Scholarships in both 2020 and 2021 ๐Ÿ’ธ. In 2021, he won a Gold Award in the National College Student Innovation Competition for his contributions to a motion perception and positioning system ๐Ÿฅ‡. Earlier, in 2019, he received the Second Prize in the NXP Cup Intelligent Car Competition ๐Ÿš—. These recognitions affirm his technical competence, creativity, and dedication to impactful research and development.

๐Ÿ’ผ๐Ÿ“˜Conclusion

Dr. OuYang Binghao stands out as a dynamic and skilled researcher, combining academic excellence with practical innovation ๐Ÿ’ผ๐Ÿ“˜. 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 ๐Ÿงญ. 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 ๐ŸŒ. Dr. OuYangโ€™s trajectory reflects not only promise but also a clear commitment to solving critical real-world problems through mathematics, computation, and collaborative research ๐Ÿค๐Ÿ”ฌ..

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:

 

 

Liangliang Sun | Optimization | Best Researcher Award

Published on by Math Scientist

Prof. Liangliang Sun | Optimization | Best Researcher Award

Dean at Northeastern University, China

Prof. Liangliang Sun ๐ŸŒŸ is a distinguished scholar in control theory and intelligent scheduling systems, currently serving at Northeastern University, China ๐Ÿซ. With a robust academic background including a Ph.D. from both Northeastern University and the University of Connecticut ๐ŸŽ“, he has cultivated deep expertise in steelmaking-continuous casting optimization, energy systems, and industrial automation โš™๏ธ. His prolific research spans over 18 high-impact publications ๐Ÿ“š, multiple national-level projects ๐ŸŽฏ, and several patented innovations ๐Ÿ”ฌ. Prof. Sun has earned accolades such as the Xingliao Talent Plan ๐ŸŒŸ and has been a two-time champion ๐Ÿ† in Chinaโ€™s prestigious Challenge Cup competitions. His contributions extend into teaching, editorial responsibilities ๐Ÿ–‹๏ธ, and international collaborations ๐ŸŒ. Known for integrating theory with real-world industrial applications ๐Ÿ”„, he bridges gaps between research and practice seamlessly. As a dynamic thought leader ๐Ÿš€ in control engineering and smart manufacturing, Prof. Sun continues to inspire innovation and academic excellence across global platforms ๐ŸŒ.

Professional Profileย 

Scopus Profile

๐ŸŽ“ Education

Prof. Liangliang Sunโ€™s academic journey is marked by scholarly excellence and international immersion ๐ŸŒ. He earned his Bachelor’s and Master’s degrees in Automation and Control Engineering from Northeastern University, China ๐Ÿ‡จ๐Ÿ‡ณ, laying the groundwork for a solid technical foundation. He later pursued a prestigious dual Ph.D. from Northeastern University and the University of Connecticut ๐Ÿ‡บ๐Ÿ‡ธ, enriching his expertise through cross-cultural academic synergy. His doctoral research focused on intelligent optimization and industrial system control, setting the stage for impactful innovation. This global academic trajectory reflects a deep commitment to advancing modern engineering frontiers ๐Ÿ”ฌ. With early exposure to cutting-edge research environments, Prof. Sun developed a unique ability to integrate Eastern precision with Western analytical frameworks, a blend that defines his distinctive academic persona ๐Ÿ“˜.

๐Ÿข Professional Experience

Prof. Sun has cultivated an impressive professional track record in academic and applied engineering settings ๐Ÿ”ง. Currently a full professor at Northeastern Universityโ€™s School of Information Science and Engineering ๐Ÿซ, he teaches and mentors in systems engineering and automation. His career includes a postdoctoral tenure at the University of Connecticut ๐Ÿ‡บ๐Ÿ‡ธ, where he deepened his research in smart manufacturing. He has led numerous national research projects as Principal Investigator, collaborating with top-tier steel and energy enterprises ๐Ÿญ. Beyond academia, he offers expert consultations on intelligent scheduling, production line efficiency, and energy optimization ๐Ÿ’ก. Prof. Sun also holds leadership roles in editorial boards and technical committees, actively shaping global discourse in control systems and industrial AI ๐Ÿ“Š. His trajectory exemplifies research-driven engineering leadership โš™๏ธ.

๐Ÿ” Research Interest

Prof. Sunโ€™s research orbits around intelligent optimization, industrial control, and smart scheduling algorithms ๐Ÿš€. He explores dynamic production scheduling in steelmaking, aiming to enhance process integration, reduce emissions, and boost system efficiency ๐Ÿ”„. His work leverages artificial intelligence, deep learning, and energy modeling to address complex industrial challenges. With a passion for merging theory with real-world applicability ๐Ÿ› ๏ธ, his investigations span multi-objective optimization, cyber-physical systems, and data-driven control frameworks. He has also ventured into hydrogen-rich energy systems and low-carbon manufacturing pathways ๐ŸŒฑ. His scientific vision aligns seamlessly with the evolving demands of Industry 4.0 and sustainable engineering ๐ŸŒ. Through over 18 peer-reviewed papers, Prof. Sun has contributed significantly to reshaping production intelligence and process automation across diverse industrial landscapes ๐Ÿ“š.

๐Ÿ… Awards and Honors

Prof. Liangliang Sun has garnered prestigious awards that reflect his academic leadership and innovation excellence ๐Ÿ†. Heโ€™s a dual Champion of the National Challenge Cup, a rare feat highlighting his creativity and technical mastery early on ๐Ÿง . He is a selected recipient of the Xingliao Talent Plan, the “Hundred and Ten Thousand Talents Project”, and the Young Top Talent in Liaoning Province ๐ŸŒŸ. Recognized nationally and provincially, he exemplifies the profile of a high-impact scholar pushing disciplinary boundaries ๐Ÿšง. His awarded projects from the National Natural Science Foundation of China (NSFC) underline the national trust in his research potential ๐Ÿงช. These honors demonstrate his sustained excellence in advancing automation, energy intelligence, and industrial digitization. Each accolade fortifies his status as a distinguished researcher ๐Ÿ’ผ.

๐Ÿงฉ Conclusion

Prof. Liangliang Sun represents a remarkable blend of intellectual rigor, innovation, and practical relevance ๐ŸŽฏ. With interdisciplinary strength across automation, AI, and energy systems, he bridges theoretical research with industrial transformation ๐ŸŒ. His impactful publications, pioneering projects, and patented inventions underscore a career built on thoughtful innovation and global relevance ๐Ÿ’ก. He leads with purpose, engages in collaborative discovery, and mentors the next generation of scientific leaders ๐Ÿ‘จโ€๐Ÿซ. Prof. Sunโ€™s contributions enhance the technological landscape and redefine the future of smart manufacturing and sustainable engineering ๐Ÿ”‹. As a thought leader, he continues to shape high-impact solutions for complex industrial ecosystems, leaving a lasting imprint on global engineering science ๐ŸŒŸ. His career is a testament to vision, resilience, and relentless pursuit of excellence ๐Ÿ”.

Publications Top Notes

๐Ÿ“˜ Title: A learning-enhanced ant colony optimization algorithm for integrated planning and scheduling in hot rolling production lines under uncertainty
Authors: S. Jiang, L. He, L. Cao, L. Sun, G. Peng
Year: 2025
Citations: 1
Source: Swarm and Evolutionary Computation

๐Ÿ“˜ Title: A Self-adaptive two stage iterative greedy algorithm based job scales for energy-efficient distributed permutation flowshop scheduling problem
Authors: Y. Yu, Q. Zhong, L. Sun, X. Jing, Z. Wang
Year: 2025
Source: Swarm and Evolutionary Computation

๐Ÿ“˜ Title: Research on steelmaking-continuous casting cast batch planning based on an improved surrogate absolute-value Lagrangian relaxation framework
Authors: C. Li, L. Sun
Year: 2025
Source: International Journal of Automation and Control

๐Ÿ“˜ Title: An Online Learning-Based mACO Approach for Hot Rolling Scheduling Problems Involving Dynamic Order Arrivals
Authors: S. Jiang, Q. Liu, L. Cao, L. Sun
Year: 2025
Source: IEEE Transactions on Automation Science and Engineering

๐Ÿ“˜ Title: A robust optimization approach for steeling-continuous casting charge batch planning with uncertain slab weight
Authors: C. Li, L. Sun
Year: 2024
Citations: 1
Source: Journal of Process Control

๐Ÿ“˜ Title: Optimal control of three-dimensional unsteady partial differential equations with convection term in continuous casting
Authors: Y. Yu, Y. Wang, X. Pang, L. Sun
Year: 2024
Citations: 1
Source: Computers and Mathematics with Applications

๐Ÿ“˜ Title: Optimal Scheduling Works for Two Employees with Ordered Criteria
Authors: N.M. Matsveichuk, Y.N. Sotskov, L. Sun
Year: 2024
Source: WSEAS Transactions on Business and Economics