Huilong Gao | Electrical Engineering | Research Excellence Award

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Dr. Huilong Gao | Electrical Engineering | Research Excellence Award

University of Wisconsin–Madison | United States.

Dr. Huilong Gao is a doctoral researcher in electrical and computer engineering specializing in III–V semiconductor optoelectronic devices, with a primary focus on mid-infrared quantum cascade lasers. His research integrates active-region design, optical and electrical modeling, and advanced device simulation using k·p theory and multiphysics tools. He has strong expertise in cleanroom fabrication, including regrowth-compatible processing, deep dry etching, and precision metallization for high-performance laser structures. His work combines device design with comprehensive electrical, optical, and cryogenic characterization to enhance efficiency, power, and reliability. He has contributed to the development of record-high wall-plug-efficiency QCLs and advanced buried heterostructure and DFB laser platforms. His research contributions are recognized through peer-reviewed publications in leading photonics and applied physics journals. His scholarly impact includes 60 citations with an h-index of 5 and an i10-index of 3.

Citation Metrics (Google Scholar)

60

45

30

15

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Citations
60

h-index
5

i10-index
3


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Featured Publications

 

Uwayesu Happy Edwards | Engineering | Excellence in Research Award

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Mr. Uwayesu Happy Edwards | Engineering | Excellence in Research Award

Suzhou university of science and technology | China

Mr. Uwayesu Happy Edwards the research focuses on environmental engineering, natural resource assessment, wastewater treatment modeling, hydropower system analysis, and climate-related environmental degradation across East and Central Africa. Recent work investigates the factors driving water quality changes in Lake Bunyonyi, integrating ecological metrics with habitat-impact assessments. Studies on wastewater treatment processes include large-scale evaluation of ASM1 parameters under subtropical climatic conditions, using long-term WWTP monitoring data to improve predictive reliability and optimize treatment efficiency. Broader environmental impact assessments examine risk patterns in natural resource zones across Southern Nigeria, Ibo regions, and Uganda’s Kitezi landfill, applying quantitative environmental models to evaluate pollution, habitat stress, and human–ecosystem interaction. Additional research explores deforestation-driven climate change in Morogoro, Tanzania, emphasizing the environmental implications for EPA-related conservation missions. Work on hydropower comparability analyzes the performance, sustainability, and environmental footprints of hydropower relative to fossil fuels and other energy systems in developing countries, contributing to renewable-energy assessment frameworks. Complementary studies investigate biomass arrangement effects on aquatic ecosystems, using vibrational analysis to evaluate impacts on fish habitats in Lake Victoria. Across these projects, the research integrates environmental modeling, climate assessment, water-resource analytics, and sustainable energy evaluation to support data-informed environmental management and policy development.

Featured Publications

Uwayesu, H. E., & Mulangila, J. (2025). Factor contributing to change of water in Lake Bunyonyi [Dataset]. Figshare. https://doi.org/10.6084/m9.figshare.30041587

Uwayesu, H. E. (2025). Address of Edwards line of emissions in reducing/positive impact to climate [Dataset]. OSF. https://doi.org/10.17605/osf.io/csz8x

 Uwayesu, H. E. (2025). Environmental impact and risk assessment of natural resource areas around Southern Nigeria, particularly Ibo and Uganda in the Kitezi landfill [Dataset]. Harvard Dataverse. https://doi.org/10.7910/DVN/EJ4Z7E

 Uwayesu, H. E. (2025). Evaluation of ASM1 parameters using large-scale WWTP monitoring data from a subtropical climate in Entebbe [Dataset]. Harvard Dataverse. https://doi.org/10.7910/DVN/BG5VJB

Yunwen Xu | Engineering | Best Researcher Award

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Dr. Yunwen Xu l Engineering
| Best Researcher Award

Shanghai Jiao Tong University | China

Dr. Yunwen Xu’s research focuses on advancing intelligent transportation systems, autonomous driving control, and predictive control for complex and embedded systems. Her innovative work integrates graph-based spatial-temporal modeling, data-driven control algorithms, and real-time optimization to enhance vehicle trajectory prediction, traffic signal management, and collaborative control in large-scale dynamic environments. Through over 50 high-impact publications, including 15 in top-tier journals and several ESI highly cited papers, Dr. Xu has significantly contributed to the theoretical and practical foundations of predictive control and intelligent mobility. Her research achievements include developing FPGA-based predictive controllers, robust model predictive frameworks, and reinforcement learning-based control systems for V2X-enabled autonomous vehicles. By leading national and provincial research projects and collaborating internationally with institutions like Purdue University and industrial partners such as Shanghai Electric Wind Power Group, she bridges the gap between academic innovation and industrial application. Her patents and successful technology transfers in microgrid energy management and advanced temperature control demonstrate the translational strength of her research. Recognized with prestigious honors, including the Best Paper Award at the Chinese Process Control Conference and championship at the Autonomous Driving Algorithm Challenge, Dr. Xu continues to pioneer next-generation control and automation technologies that drive the evolution of intelligent, efficient, and sustainable transportation ecosystems.

Profile:  Google Scholar 

Featured Publications

Mujeeb Abiola Abdulrazaq | engineering | Young Scientist Award

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Mr. Mujeeb Abiola Abdulrazaq l engineering
| Young Scientist Award

University of North Carolina at Charlotte | United States

Mr. Mujeeb Abiola’s research focuses on advancing transportation safety and efficiency through data-driven methodologies and emerging technologies. His work extensively employs large-scale traffic and crash data, including millions of federal highway administration records, to investigate the spatiotemporal dynamics of pedestrian crashes and the evolution of crash hotspots. Utilizing advanced statistical and machine learning models, he has developed predictive frameworks that outperform traditional Highway Safety Manual standards, providing robust insights into risk factors and injury severity in both human-driven and autonomous vehicle contexts. His research on connected and autonomous vehicles (CAVs) has led to the development of traffic control algorithms that significantly enhance safety, operational efficiency, and environmental sustainability in freeway work zones. Furthermore, his studies integrate GPU-accelerated data processing, simulation-based optimization, and multi-level heterogeneity modeling to evaluate vulnerable road user behavior and assess dynamic collision risks. Through simulation platforms such as VISSIM and SUMO, combined with Python-based data analysis and GIS applications, his work systematically addresses complex traffic scenarios, including merging, diverging, and weaving segments, while also accounting for seasonal variations and temporal constraints in crash determinants. His contributions include empirical analyses of autonomous vehicle incidents, methodological advancements in microsimulation accuracy, and development of actionable strategies for real-world traffic management, ultimately aiming to improve roadway safety, inform policy, and guide evidence-based planning in modern transportation systems.

Profile:  Google Scholar 

Featured Publications

  • Abdulrazaq, M. A., & Fan, W. D. (2024). Temporal dynamics of pedestrian injury severity: A seasonally constrained random parameters approach. International Journal of Transportation Science and Technology, 9.

  • Abdulrazaq, M. A., & Fan, W. (2025). A priority based multi-level heterogeneity modelling framework for vulnerable road users. Transportmetrica A: Transport Science, 1–34. https://doi.org/10.1080/23249935.2025.2516817

  • Abdulrazaq, M. A., & Fan, W. (2025). Seasonal instability in crash determinants: A partially temporally constrained modeling analysis. SSRN 5341417. https://doi.org/10.2139/ssrn.5341417

Haneen Alamirah | Engineering | Best Researcher Award

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Ms. Haneen Alamirah l Engineering
| Best Researcher Award

United Arab Emirates University | United Arab Emirates

Ms. Haneen Alamirah is an accomplished Architectural Engineer and researcher from the United Arab Emirates, specializing in occupant comfort in the built environment and sustainable building design. She holds a Bachelor’s degree in Architectural Engineering from the UAE University, a Master’s degree in Sustainable Critical Infrastructure from Khalifa University, and is currently pursuing her Ph.D. in Architectural Engineering at the UAE University . Her professional experience includes serving as a Graduate Teaching and Research Assistant at both Khalifa University and UAE University, where she has been involved in teaching, mentoring, and conducting advanced research in sustainability and human–environment interaction. Ms. Alamirah’s research contributions focus on the integration of immersive virtual environments for evaluating occupant comfort, adaptive behavior, and personal comfort models in shared spaces. Her scholarly work has been featured in high-impact journals such as Building and Environment and presented at international conferences including the Building Simulation Conference (2023, Shanghai; 2025, Brisbane) and the UAE Graduate Students Research Conference. With 68 citations and an h-index of 1 (Scopus ID: 57288505500), she continues to advance knowledge at the intersection of architecture, sustainability, and digital simulation tools, contributing to more resilient and human-centered design practices.

Profile: Scopus 

Featured Publication 

Alamirah, H. (2023, September). A bibliometric analysis of immersive virtual environment applications for occupant comfort and behavior research. In Proceedings of the Building Simulation Conference 2023 (p. 1397). Shanghai, China. https://doi.org/10.26868/25222708.2023.1397

Sheharyar Khan | Engineering | Young Scientist Award

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Dr. Sheharyar Khan l Engineering
| Young Scientist Award

Shandong University | Pakistan

Dr. Sheharyar Khan is a distinguished computer scientist and software engineer with extensive expertise in software engineering, artificial intelligence, and cybersecurity, specializing in IoMT edge-cloud frameworks and network intrusion detection systems. Currently a Postdoctoral Research Fellow at Shandong University, he leads independent and collaborative research initiatives, designing experiments, analyzing data, and publishing findings in high-impact journals. His doctoral research at Northwestern Polytechnical University focused on optimization-based hybrid offloading frameworks for IoMT in edge-cloud healthcare systems, demonstrating the integration of advanced computing techniques with practical healthcare applications. Dr. Khan has made significant contributions to explainable AI and hybrid ensemble machine learning, as seen in publications such as “HCIVAD: Explainable hybrid voting classifier for network intrusion detection systems” and “Consensus hybrid ensemble machine learning for intrusion detection with explainable AI”. With prior experience as a lecturer and IT specialist, he combines academic rigor with practical software development expertise. Dr. Khan has 104 citations across 10 documents, an h-index of 6, an i10-index of 5, is indexed under Scopus Author ID 57221647889, and holds ORCID 0000-0002-0089-0168, reflecting his impact on the field. Recognized for his analytical skills, innovation, and interdisciplinary research, he continues to advance secure, intelligent, and explainable computing systems for both academic and real-world applications.

Profile: Scopus | Google Scholar | Orcid | Researchgate 

Featured Publications

Khan, S., Liu, S., Pan, L., & Mei, G. (2025). Optimization-based hybrid offloading framework for IoMT in edge-cloud healthcare systems. Future Generation Computer Systems, 108163. https://doi.org/

Ahmed, S. K. M. T. S., Jiangbin, Z., & Khan, S. (2025). HCIVAD: Explainable hybrid voting classifier for network intrusion detection systems. Cluster Computing, 28(343). https://doi.org/

Ahmed, M. T. S., Jiangbin, Z., & Khan, S. (2024). Consensus hybrid ensemble machine learning for intrusion detection with explainable AI. Journal of Network and Computer Applications, 5*. https://doi.org/

Khan, S., Jiangbin, Z., & Ali, H. (2024). Soft computing approaches for dynamic multi-objective evaluation of computational offloading: A literature review. Cluster Computing, 27(9), 12459–12481. https://doi.org/

Heyu Peng | Engineering | Best Researcher Award

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Mr. Heyu Peng | Engineering | Best Researcher Award

Xi’an Jiaotong University | China

Heyu Peng is an emerging researcher in the field of nuclear science and technology, currently pursuing his doctoral studies at the School of Nuclear Science and Technology, Xi’an Jiaotong University, China, since March . His research primarily focuses on the development and application of advanced computational methods in nuclear engineering, particularly Monte Carlo particle-transport simulations and coupled deterministic–stochastic modeling approaches. He has contributed to significant advancements in the refinement of nuclear simulation tools, demonstrating his expertise in improving accuracy, efficiency, and applicability for nuclear reactor analysis and radiation transport problems. he co-authored a paper published in IEEE Transactions on Nuclear Science that presented a coupled deterministic and Monte Carlo method for modeling and simulating self-powered neutron detectors, a study that addressed critical aspects of detector response modeling and its implications for nuclear instrumentation and monitoring. More recently, a cutting-edge computational tool designed to enhance nuclear reactor physics simulations and broaden its utility in research and practical applications. Through these publications, Peng has established himself as a promising researcher contributing to the advancement of computational nuclear science. His work reflects a strong commitment to bridging theoretical development with real-world applications, offering tools and methodologies that can improve safety, efficiency, and innovation in nuclear energy systems. As a doctoral candidate, Peng continues to expand his research profile, collaborating with experts in the field and contributing to interdisciplinary efforts in nuclear engineering. His growing academic contributions highlight his potential to become a leading researcher in nuclear science, with a focus on computational methods that can shape the future of nuclear technology and its safe, sustainable applications.

Profile: Orcid

Featured Publications

  • He, Q., Zheng, Q., Li, J., Huang, Z., Huang, J., Qin, S., Shu, H., Peng, H., Yang, X., Shen, J., et al. (2024). Overview of the new capabilities in the Monte-Carlo particle-transport code NECP-MCX V2.0. EPJ Nuclear Sciences & Technologies.

  • Zhou, Y., Cao, L., He, Q., Feng, Z., & Peng, H. (2022). A coupled deterministic and Monte-Carlo method for modeling and simulation of self-powered neutron detector. IEEE Transactions on Nuclear Science.

 

Mohammad Hasan Parvaneh | Electrical Engineering | Young Scientist Award

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Dr. Mohammad Hasan Parvaneh | Electrical Engineering | Young Scientist Award

Engineer, West Regional Electric Company, Iran

Mohammad Hasan Parvaneh is a skilled electrical engineer specializing in power systems, smart grid technologies, and solar energy. Based in Kermanshah, Iran, he has a strong background in both theoretical and practical aspects of electrical engineering, particularly in the design and optimization of energy systems. With years of experience in the field, Mohammad has worked on numerous high-profile projects, contributing to the development and operation of electrical power networks and substations. He is currently a Senior Expert at West Regional Electric Company and has earned recognition for his research and contributions to the field. 🌟⚡️

Publication Profile

Google Scholar

Education

Mohammad Hasan Parvaneh holds a Master of Science in Electrical Engineering with a focus on Power Systems from Bu-Ali Sina University, Iran (2011–2014), where he achieved a GPA of 17.20/20. His thesis on “A robust hybrid method based on fuzzy logic for maximum power point tracking of photovoltaic systems” was supervised by Dr. Mohammad Hasan Moradi. He also holds a Bachelor of Science in Electrical Engineering (Electronic) from Razi University, Iran, with a GPA of 16.30/20. 🎓🔌

Experience

Mohammad has extensive professional experience in the electrical power sector. He is currently working as a Senior Expert at West Regional Electric Company, where he supervises the development, construction, installation, testing, and commissioning of high-voltage substations. Prior to this, he served as an Instrument Expert at Kermanshah Polymer Petrochemical Company and a Senior Expert at West Azerbaijan Electricity Power Distribution, overseeing power distribution networks and fault management. ⚙️🔧

Awards and Honors

Throughout his career, Mohammad has received several honors, including being recognized as the best researcher in Kermanshah Province by Razi University and the Kermanshah Governorate. Additionally, he has received high academic recognition for his excellence in courses such as Electrical Circuits, Control Systems, Neural Networks, and more, achieving impressive grades of 17–18 out of 20. 🏆📚

Research Focus

Mohammad’s research interests lie in electrical power systems, smart grid technologies, and renewable energy, with a particular focus on solar energy. He has published a number of papers and is actively involved in advancing technologies for maximum power point tracking in photovoltaic systems and optimizing power allocation in electrical grids. His ongoing research aims to improve the efficiency and reliability of energy systems, with applications in isolated microgrids and renewable energy integration. 🔋☀️

Publications

A new hybrid method based on fuzzy logic for maximum power point tracking of photovoltaic systems
Energy Reports, 6 (2020): 1619-1632.
DOI: 10.1016/j.egyr.2020.06.010

A mutated salp swarm algorithm for optimum allocation of active and reactive power sources in radial distribution systems
Applied Soft Computing, 85 (2019): 105833.
DOI: 10.1016/j.asoc.2019.105833

Photovoltaic Systems: Advances in Research and Applications
Book in Print

The advantages of capacitor bank placement and demand response program execution on the optimal operation of isolated microgrids
Electric Power System Research Journal (Under Review) 🔍📄

Nasreddine Belbachir | Electrical Engineering | Young Scientist Award

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 Dr. Nasreddine Belbachir | Electrical Engineering | Young Scientist Award

👨‍🏫Profile Summary

Nasreddine Belbachir received a B.Sc. degree in Electrical Engineering from the University of Relizane, Algeria, in 2013, and a M.Sc. degree in Electrical Engineering and Renewable Energy from the University of Mostaganem, Algeria, in 2015. Recently received a Ph.D. degree in Electrical Engineering and Renewable Energy from the University of Mostaganem, Algeria. His research interests include the optimal integration of renewable energy in distribution grids, electric vehicles, power systems protection, PV parameters optimization. Also, he works as an electrical engineer for more than 8 years in the oil and gas industry at Sonatrach, Algeria. Holding a research Index H= 7 with more than 110 citations.

🌐 Professional Profiles

🎓 Education

B.Sc. in Electrical Engineering, University of Relizane, Algeria, 2013, M.Sc. in Electrical Engineering and Renewable Energy, University of Mostaganem, Algeria, 2015, Ph.D. in Electrical Engineering and Renewable Energy, University of Mostaganem, Algeria, 2022

💼 Experience

Electrical Engineer at Sonatrach, Algeria (2015-2022), Temporary Teacher of Power Systems at University of Mostaganem, Algeria (2020-2022), Electrical & Instrumentation Engineer at Sonatrach, TRC/RTO (2022-present)

🔧 Training

2 years of professional training as an Electrical Engineer at Sonatrach – Ourhoud, 4 months of theoretical training at the Algerian Petroleum Institute (IAP), Short-term trainings in HSE, Risk Assessment, First Aid, Electrical Security, Electrical Maintenance, ATEX, Defensive Driving

💻 Skills

Proficiency in MATLAB, LabVIEW, Adobe products, Microsoft products, Homer Pro, PVSyst, ETAP, Data Stream, GMO, SAP, and AutoCAD, Excellent analytical, problem-solving, and communication skills, Strong understanding of electrical theory, logic control, and HSE, Wide knowledge in Oil & Gas processes, security, and maintenance, Strong academic research background with participation in international conferences and publications in reputable journals

Research Focus:

The research focus of N. Belbachir centers on the optimal integration of renewable energy sources, particularly photovoltaic distributed generation (PVDG), into electrical distribution systems. Employing metaheuristic optimization algorithms and considering various factors such as seasonal uncertainties, load demand, and overcurrent relay characteristics, Belbachir investigates the efficient allocation and sizing of PVDG and related systems like battery energy storage and distribution static var compensators. By addressing these challenges, Belbachir’s work contributes to enhancing the reliability, efficiency, and sustainability of distribution networks, ultimately facilitating the transition towards a greener and more resilient energy infrastructure.

Google Scholar Metrics 2019 :
  • All Time:
    • Citations: 119 📖
    • h-index: 9 📊
    • i10-index: 9 🔍
  • Since 2018:
    • Citations: 119 📖
    • h-index: 9 📊
    • i10-index: 9 🔍

📚Top Noted Publication

  1. Simultaneous optimal integration of photovoltaic distributed generation and battery energy storage system in active distribution network using chaotic grey wolf optimization
    • Authors: N Belbachir, M Zellagui, S Settoul, CZ El-Bayeh, B Bekkouche
    • Journal: Электротехника и электромеханика
    • Pages: 52-61
    • Year: 2021
    • Citations: 20

 

  1. Optimal allocation of RDG in distribution system considering the seasonal uncertainties of load demand and solar-wind generation systems
    • Authors: M Zellagui, N Belbachir, CZ El-Bayeh
    • Conference: IEEE EUROCON 2021-19th International Conference on Smart Technologies
    • Pages: 471-477
    • Year: 2021
    • Citations: 18

 

  1. Optimal integration of photovoltaic distributed generation in electrical distribution network using hybrid modified PSO algorithms
    • Authors: N Belbachir, M Zellagui, A Lasmari, CZ El-Bayeh, B Bekkouche
    • Journal: Indonesian Journal of Electrical Engineering and Computer Science
    • Volume: 24
    • Issue: 1
    • Pages: 50-60
    • Year: 2021
    • Citations: 17

 

  1. Optimal PV sources integration in distribution system and its impacts on overcurrent relay based time-current-voltage tripping characteristic
    • Authors: N Belbachir, M Zellagui, A Lasmari, CZ El-Bayeh, B Bekkouche
    • Conference: 2021 12th International Symposium on Advanced Topics in Electrical
    • Pages: 15
    • Year: 2021
    • Citations: 15

 

  1. Arithmetic optimization algorithm for optimal installation of DSTATCOM into distribution system based on various voltage stability indices
    • Authors: M Zellagui, A Lasmari, S Settoul, CZ El-Bayeh, R Chenni, N Belbachir
    • Conference: 2021 9th International Conference on Modern Power Systems (MPS)
    • Pages: 1-6
    • Year: 2021
    • Citations: 11

 

  1. Multi-objective optimal renewable distributed generator integration in distribution systems using grasshopper optimization algorithm considering overcurrent relay indices
    • Authors: N Belbachir, M Zellagui, S Settoul, CZ El-Bayeh
    • Conference: 2021 9th International Conference on Modern Power Systems (MPS)
    • Pages: 1-6
    • Year: 2021
    • Citations: 11

 

  1. Multi-objective optimal allocation of hybrid photovoltaic distributed generators and distribution static var compensators in radial distribution systems using various …
    • Authors: M Zellagui, N Belbachir, RA El-Sehiemy, CZ El-Bayeh
    • Journal: Journal of Electrical Systems
    • Volume: 18
    • Issue: 1
    • Year: 2022
    • Citations: 10

 

  1. Multi dimension-based optimal allocation of uncertain renewable distributed generation outputs with seasonal source-load power uncertainties in electrical distribution network …
    • Authors: N Belbachir, M Zellagui, S Settoul, CZ El-Bayeh, RA El-Sehiemy
    • Journal: Energies
    • Volume: 16
    • Issue: 4
    • Pages: 1595
    • Year: 2023
    • Citations: 8
  1. Optimal location and sizing of multiple distributed generators in radial distribution network using metaheuristic optimization algorithms
    • Authors: N Belbachir, M Zellagui, B Bekkouche
    • Journal: Facta Universitatis, Series: Electronics and Energetics
    • Volume: 35
    • Issue: 2
    • Pages: 229-242
    • Year: 2022

 

  1. Photosynthetic and cellular responses in plants under saline conditions
    • Authors: KBM Ahmed, S Singh, Y Sadiq, MMA Khan, M Uddin, M Naeem, T Aftab
    • Book: Frontiers in Plant-Soil Interaction
    • Pages: 293-365
    • Year: 2021

 

  1. Application hybrid chaotic maps and adaptive acceleration coefficients PSO algorithm for optimal integration photovoltaic distributed generation problem in distribution energy …
    • Authors: M Zellagui, N Belbachir, A Lasmari, B Bekkouche, CZ El-Bayeh
    • Book: Control Applications in Modern Power Systems: Select Proceedings of EPREC
    • Pages: 5
    • Year: 2022