Luca Zannini | Engineering | Young Researcher Award

Published on by Young Scientists Awards

Young Researcher Award

Luca Zannini
Affiliation University of Modena and Reggio Emilia
Country Italy
Scopus ID 59258265500
Documents 2
Citations 20
h-index 2
Subject Area Engineering
Event International Young Scientists Award
ORCID 0009-0000-6923-2457

Luca Zannini

University of Modena and Reggio Emilia, Italy

Luca Zannini is an emerging researcher affiliated with the University of Modena and Reggio Emilia, Italy, whose academic activities are associated with the field of Engineering. Through scholarly investigations and peer-reviewed publications, the researcher has contributed to the development of technical knowledge within the engineering domain. Research performance indicators, including publication output, citation records, and h-index measurements, provide an overview of scholarly engagement and the influence of published work within the academic community. Such metrics are frequently used to assess research visibility and scientific contribution across disciplines.[1]

Abstract

This academic profile summarizes the scholarly activities, research indicators, and professional achievements of Luca Zannini in the field of Engineering. The profile considers publication records, citation performance, research visibility, and academic contributions. Although the documented publication portfolio remains at an early stage, the available bibliometric indicators demonstrate growing engagement with scientific research and the dissemination of engineering knowledge. Citation activity associated with the researcher’s publications suggests that the work has attracted attention within relevant scholarly communities and contributes to ongoing technical discussions.[1]

Keywords

Engineering, Scientific Research, Academic Publications, Citation Analysis, Young Researcher, Research Impact, Innovation, Technical Studies, Scholarly Communication, International Young Scientists Award.

Introduction

Engineering research plays a fundamental role in advancing technology, industrial development, sustainability, and innovation. Researchers in this discipline contribute to the creation of new methods, systems, and applications that address contemporary technical challenges. Luca Zannini’s academic activities are situated within this broader context of engineering scholarship. Through participation in scientific publication and research dissemination, the researcher contributes to the accumulation and exchange of technical knowledge that supports future scientific and industrial progress.[2]

Research Profile

According to available bibliometric information, Luca Zannini has authored two indexed publications that have collectively received twenty citations. The researcher currently maintains an h-index of 2, indicating that multiple publications have generated measurable scholarly attention. These indicators provide a quantitative perspective on research productivity and academic visibility while also highlighting the early-stage development of a growing research career.[1]

Research Contributions

  • Contribution to engineering-related scientific investigations and scholarly communication.
  • Participation in peer-reviewed research activities and publication processes.
  • Development of technical knowledge through academic collaboration and research dissemination.
  • Support for innovation and evidence-based engineering practices through scientific output.

Publications

The researcher’s publication portfolio consists of peer-reviewed scholarly works indexed within recognized academic databases. These publications serve as a platform for communicating research findings, encouraging scientific discussion, and contributing to the broader engineering literature. Through publication and citation activity, the research outputs demonstrate relevance to ongoing academic and technical investigations.[3]

Research Impact

Research impact is often evaluated through indicators such as citations, publication quality, collaboration networks, and scholarly influence. The citation record associated with Luca Zannini’s publications indicates that the research has been referenced by other academic works, contributing to knowledge exchange within the engineering community. As research activity continues to expand, such indicators may further reflect the growing influence of the researcher’s scientific contributions.[1]

Award Suitability

The Young Researcher Award recognizes promising scholars who demonstrate dedication to scientific advancement and research excellence during the early stages of their careers. Based on the available publication record, citation performance, institutional affiliation, and scholarly engagement, Luca Zannini represents a developing research profile within the field of Engineering. These characteristics align with the objectives of programs that seek to encourage emerging researchers and support continued scientific achievement. Final award consideration remains subject to the evaluation criteria established by the organizing committee of the International Young Scientists Award.[4]

Conclusion

Luca Zannini’s academic profile reflects an emerging presence within Engineering research, supported by peer-reviewed publications, citation activity, and engagement with scientific scholarship. While the documented research portfolio remains at an early stage, available indicators demonstrate meaningful participation in academic research and knowledge dissemination. Continued scholarly activity, publication growth, and interdisciplinary collaboration are expected to strengthen the researcher’s contribution to the engineering field and enhance future academic impact.[1]

References

  1. Elsevier. (n.d.). Scopus author details: Luca Zannini, Author ID 59258265500. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=59258265500
  2. National Academy of Engineering. (n.d.). The role of engineering research in technological advancement.
    https://www.nae.edu
  3. Orcid. (n.d.). Orcid author details. Luca Zannini.
    https://orcid.org/0009-0000-6923-2457
  4. International Young Scientists Award. (n.d.). Award eligibility and recognition criteria.
    https://youngscientistawards.com/

Chandan Pandey | Engineering | Young Scientist Award

Published on by Young Scientists Awards

Young Scientist Award

Chandan Pandey
IIT Jodhpur, India
Chandan Pandey
Affiliation IIT Jodhpur
Country India
Scopus ID 56494528900
Documents 233
Citations 8,637
h-index 55
Subject Area Engineering
Event International Young Scientists Award
Google Scholar View Profile

Chandan Pandey of IIT Jodhpur, India. His academic record demonstrates sustained contributions to engineering research through high-impact publications, extensive citation performance, and active participation in scientific advancement. With more than 233 indexed publications, 8,637 citations, and an h-index of 55, his research portfolio reflects notable influence across engineering disciplines and interdisciplinary technological studies.[1]

Abstract

This article presents a concise academic overview of Chandan Pandey and evaluates his suitability for recognition through the International Young Scientists Award. His scholarly activities encompass engineering research, scientific publications, collaborative investigations, and contributions to knowledge dissemination. The measurable indicators of research productivity, including publication output, citation count, and h-index, demonstrate a sustained level of academic engagement and visibility within the global research community.[1]

Keywords

Engineering Research, Scientific Publications, Innovation, Citation Impact, Scopus Author Profile, Academic Recognition, Research Excellence, IIT Jodhpur, Young Scientist Award, Scholarly Contributions.

Introduction

Research excellence is commonly assessed through scholarly productivity, scientific influence, and contributions to advancing knowledge. Chandan Pandey has established a substantial academic profile through publication activity and citation performance. His work reflects engagement with engineering challenges and emerging technological developments while supporting the broader objectives of innovation and scientific progress.[2]

Research Profile

The research profile of Chandan Pandey indicates extensive scholarly activity. According to publicly available academic indexing services, his publication record includes more than two hundred peer-reviewed documents. These publications have received significant citation attention, suggesting that the research has contributed meaningfully to ongoing scientific discussions and technological applications.[1]

  • 233 indexed research documents.
  • 8,637 scholarly citations.
  • h-index of 55.

Research Contributions

The research contributions associated with Chandan Pandey demonstrate participation in areas related to engineering innovation, applied scientific methodologies, and interdisciplinary investigations. His publications have supported the development of scientific understanding and have contributed to research networks through collaboration and dissemination of findings. Such contributions are reflected through citation metrics and continued academic engagement.[3]

Publications

The publication portfolio includes journal articles, conference papers, reviews, and collaborative research outputs indexed by major scholarly databases. The breadth of publications demonstrates sustained academic productivity and ongoing participation in research activities. Selected works are associated with internationally recognized publishers and indexed literature repositories.[1]

Research Impact

Research impact is frequently measured using citations, visibility, and adoption within subsequent studies. The citation count exceeding 8,600 and h-index of 55 indicate substantial scholarly recognition. These indicators suggest that published findings have been referenced by numerous researchers, thereby contributing to the cumulative advancement of engineering knowledge and related scientific fields.[1]

Award Suitability

Based on publicly available academic indicators, Chandan Pandey demonstrates characteristics commonly associated with candidates for scientific recognition programs. His publication record, citation performance, institutional affiliation, and demonstrated research engagement provide evidence of scholarly achievement. These attributes align with the objectives of the International Young Scientists Award, which seeks to acknowledge individuals contributing to scientific advancement and research excellence.[4]

Conclusion

Chandan Pandey’s academic profile reflects sustained research productivity, measurable scholarly influence, and active participation in engineering research. The combination of publication volume, citation impact, and institutional affiliation highlights a record of academic achievement. Within the context of scientific recognition initiatives, these accomplishments support consideration for acknowledgement through international research and innovation award programs.[1]

References

  1. Elsevier. (n.d.). Scopus author details: Chandan Pandey, Author ID 56494528900. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=56494528900
  2. Google Scholar. (n.d.). Scholar profile and citation metrics for Chandan Pandey.
    https://scholar.google.co.in/citations?user=s-7k1QEAAAAJ&hl=en
  3. Pandey, C. et al. (2018). Research publication with DOI indexing.
    DOI: https://doi.org/10.1016/j.nanoen.2018.03.021
  4. International Young Scientists Award. (n.d.). Award objectives and recognition framework.
    https://youngscientistawards.com/

Abirami Karthikeyan | Engineering | Young Scientist Award

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Dr. Abirami Karthikeyan | Engineering | Young Scientist Award

Assistant Professor | SASTRA Deemed University | India.

Dr. Abirami Karthikeyan is a researcher specializing in RF and microwave systems with a strong focus on non-invasive microwave sensors for Industrial IoT and biomedical applications. Her work advances smart sensing, metasurface-enhanced resonators, and near-field radio-frequency techniques for food, agriculture, and healthcare industries. She has published in high-impact journals and contributed to multiple conferences, book chapters, and patent innovations in microwave sensing. Her research includes integrated sensing-communication systems, 5G/6G antenna design, and intelligent RF systems for precision monitoring. She has secured competitive funding and earned notable awards for her research excellence and innovation. Her projects emphasize practical, application-driven microwave solutions supported by strong simulation, prototyping, and measurement expertise. She actively collaborates on interdisciplinary sensor development bridging electromagnetics, IoT, and smart industrial technologies. her published 10 research documents that have received 10 citations, resulting in an h-index of 2.

Citation Metrics (Scopus)

20

15

10

5

0

Citations
10
Documents
10

h-index
2


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Featured Publications

 

Heba Afify | Engineering | Editorial Board Member

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Dr. Heba Afify | Engineering | Editorial Board Member

Cairo | Egypt

Dr. Heba Afify research explores the molecular landscape of the BLIS subtype of triple-negative breast cancer through comprehensive bioinformatics analysis aimed at identifying immune-related hub genes with critical roles in tumor progression, immune evasion, and potential therapeutic responsiveness. Using integrated datasets and computational pipelines, the study performs differential gene expression profiling, network construction, and enrichment analyses to map immune-modulated pathways underlying the aggressive behavior of the BLIS subtype. Key immune hub genes are screened through protein–protein interaction networks, functional annotation, and pathway enrichment to uncover targets with relevance to cytokine signaling, chemokine interactions, and immune cell infiltration. The work further evaluates correlations between these hub genes and components of the tumor immune microenvironment, including associations with immunoregulatory checkpoints, inflammatory mediators, and effector immune cells. By combining multi-level computational evidence, the study highlights genes that may serve as biomarkers for diagnosis, prognosis, or targeted immunotherapy in patients with this difficult-to-treat cancer subtype. The analysis contributes to a deeper understanding of immunogenomic features driving BLIS-TNBC and offers a foundational framework for precision oncology strategies, emphasizing how immune-focused gene signatures can guide future translational research and therapeutic innovations in breast cancer management.

Featured Publications

Adel, H., Abdel Wahed, M., & Afify, H. M. (2025). Bioinformatics analysis for immune hub genes in BLIS subtype of triple-negative breast cancer. Egyptian Journal of Medical Human Genetics. https://doi.org/10.1186/s43042-025-00745-0

Afify, H. M., Mohammed, K. K., & Hassanien, A. E. (2025). Stress detection based EEG under varying cognitive tasks using convolution neural network. Neural Computing and Applications, Advance online publication. https://doi.org/10.1007/s00521-024-10737-7

Afify, H. M., Mohammed, K. K., & Hassanien, A. E. (2024). Insight into automatic image diagnosis of ear conditions based on optimized deep learning approach. Annals of Biomedical Engineering. https://doi.org/10.1007/s10439-023-03422-8

Waleed Algriree | Engineering | Editorial Board Member

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Dr. Waleed Algriree | Engineering | Editorial Board Member

Putra university malaysia | Malaysia

Dr. Waleed Algriree research contributions focus extensively on advanced communication systems, particularly the development and optimization of next-generation wireless and satellite technologies. Core work includes enhancing 5G detection performance through hybrid filtering techniques, low-complexity MIMO architectures, and multi-user spectrum sensing approaches designed to support cognitive radio environments. Significant studies investigate waveform detection using windowed cosine-Hamming filters, hybrid detection frameworks, and comparative evaluations of M-ary modulation impacts on signal identification accuracy. Additional research explores OFDM performance improvement through PAPR reduction using 2D inverse discrete Fourier transforms, as well as analytical derivations related to SLM clipping levels, complexity, and bit-loss characteristics. Contributions extend to the design of novel detection schemes employing discrete cosine transforms with QPSK modulation for cognitive radio systems, along with multi-user CR-5G network models that enhance spectral efficiency and sensing reliability across various waveform structures. Work in satellite and mobile communication further supports improved signal processing, system optimization, and robust network performance. Results published in reputable journals and conferences demonstrate strong emphasis on algorithmic efficiency, spectral utilization, advanced filter design, and practical applicability in sustainable, high-capacity communication infrastructures. These studies collectively advance the evolution of intelligent, adaptive, and efficient wireless communication technologies.

Featured Publication

Algriree, W. K. H. (Year). Advancing healthcare through piezoresistive pressure sensors: A comprehensive review of biomedical applications and performance metrics.

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

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.