Shengnan Zhang | Engineering | Best Researcher Award

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Dr. Shengnan Zhang | Engineering | Best Researcher Award

None  at School of Mechatronic Engineering and Automation, Shanghai University

Short Bio

  • shengnan zhang is a Ph.D. researcher at Shanghai University specializing in electromagnetic flowmeters, signal processing, and mathematical modeling for industrial processes. With experience in engineering and automation, she integrates theoretical and applied research to enhance industrial measurement accuracy and efficiency.

Professional Profile

Educational Background

  • shengnan zhang is currently pursuing a Ph.D. in the School of Mechatronic Engineering and Automation at Shanghai University (2021–2024). She earned her master’s degree in Control Science and Engineering (Automation) from Inner Mongolia University of Science and Technology in 2020.

Professional Experience

  • shengnan zhang has gained diverse experience in both industry and academia. She worked as a junior engineer in the Mechanical and Electrical Department at State Grid Xinyuan Chifeng Company, Inner Mongolia (2020–2021). She later transitioned into roles as a Hardware R&D Engineer at JiDan Biotechnology Co., Ltd. and a High School Mathematics Teacher at Nanjing Yunjushi Education Co., Ltd. in 2021.

Research Interests

    • Her research focuses on electromagnetic flowmeters, signal processing, and mathematical modeling of complex industrial processes. She is particularly interested in developing advanced computational techniques for industrial automation and measurement systems.

Author Metrics

  • Currently, shengnan zhang is actively engaged in research and has contributed to scholarly publications in her field. Her work includes studies on signal processing applications in industrial automation and measurement technologies.

Publication Top Noted

  • Study on the Match-Filtering Ability of the Electromagnetic Flowmeter Signals Based on the Generalized Dual-Frequency Walsh Transform
    Flow Measurement and Instrumentation, March 2025
    DOI: 10.1016/j.flowmeasinst.2024.102767
  • Generalized Walsh Transform Sequency-Domain-Based Match Filtering for Electromagnetic Flowmeter Signal Measurement
    IEEE Sensors Journal, April 2024
    DOI: 10.1109/JSEN.2024.3366238
  • A Sequency Match Filtering Algorithm Based on the Generalized Walsh Transform for Processing Rectangular Wave Signals
    Review of Scientific Instruments, February 2024
    DOI: 10.1063/5.0175079
  • Study on Match Filtering Based on Sequency Spectrum Characteristics of the Walsh Transform for Electromagnetic Flowmeter Signal Measurement
    Measurement, February 2024
    DOI: 10.1016/j.measurement.2023.114021

Conclusion

  • Dr. shengnan zhang is a highly qualified researcher with notable contributions to signal processing and industrial measurement systems. Her innovative approaches using Generalized Walsh Transform have the potential to improve electromagnetic flowmeter accuracy significantly. With further collaboration, higher citation impact, and real-world application of her research, she would be an excellent candidate for the Best Researcher Award.

Abdisalam Hassan Muse | Computational Methods | Best Researcher Award

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Assoc Prof Dr. Abdisalam Hassan Muse | Computational Methods | Best Researcher Award 

Assoc Prof Dr. Abdisalam Hassan Muse, Amoud University, Somalia

Assoc. Prof. Dr. Abdisalam Hassan Muse is an accomplished educator and researcher, with a Ph.D. in Statistics from PAUSTI-JKUAT, Kenya. He has over 13 years of experience teaching mathematics, statistics, and data science at both secondary and university levels. Dr. Muse has a strong research focus on Bayesian statistics, econometrics, and data science, with expertise in statistical modeling, machine learning, and time series analysis. His academic work is complemented by active participation in international workshops and trainings in advanced statistical methods.

Orcid Profile

Educational Details

Assoc. Prof. Dr. Abdisalam Hassan Muse earned his Ph.D. in Statistics from the Pan African University Institute for Basic Sciences, Technology and Innovation (PAUSTI), hosted at Jomo Kenyatta University of Agriculture and Technology (JKUAT), Nairobi, Kenya (May 2019 – Oct 2022). He also holds two Master’s degrees: an MSc in Climate Change and Environmental Sustainability from Amoud University, Borama, Somalia (September 2018 – Incomplete), and an MSc in Mathematics and Statistics from the same institution (September 2015 – July 2017). His diverse academic foundation also includes a BA in Islamic Studies from Beder International University, Borama, Somalia (September 2013 – July 2016), a BSc in Mathematics and Physics from Amoud University (September 2010 – July 2012), and Diplomas in Islamic Studies (2008–2010) and Education for Mathematics and Physics (2005–2007) from Amoud University and Zaylac Institute of Islamic Studies, respectively. He completed his secondary education at Sheikh Ali Jawhar Secondary School in Borama, Somaliland, earning the Somaliland Certificate of Secondary Education (September 2001 – July 2005).

Professional Experience

Dr. Abdisalam Hassan Muse has over 13 years of experience in education, including two years of postgraduate teaching and supervision and six years of undergraduate university teaching. His teaching expertise spans mathematics, statistics, data science, and the application of technology in statistical experiments. He also has 11 years of secondary teaching experience. Throughout his career, he has demonstrated a strong ability to communicate complex concepts, both in academic and classroom settings. Dr. Muse has actively participated in several international workshops and training programs, focusing on Bayesian statistics, data science, official statistics, disease modeling, and statistical software like R and Python. Additionally, he has experience in research and training related to fragile environments and post-distribution monitoring for aid programs.

Research Interest

Dr. Muse’s research is focused on a variety of statistical fields, including Bayesian statistics, econometrics, survival analysis, official statistics, and demography. His expertise extends to data science, statistical modeling, machine learning, mathematical statistics, and stochastic processes. He has a passion for applying advanced statistical techniques to real-world problems, with a keen interest in environmental statistics, computational statistics, probability distributions, regression modeling, and time series analysis. His skills also encompass areas like Ito calculus, education statistics, and population analysis.

Top Notable Publications

Prevalence and determinants of home delivery among pregnant women in Somaliland: Insights from SLDHS 2020 data
Atención Primaria
2025-02 | Journal Article
DOI: 10.1016/j.aprim.2024.103082
ISSN: 0212-6567
Source: Abdisalam Hassan Muse

Cardiovascular disease prevalence and associated factors in a low-resource setting: A multilevel analysis from Somalia’s first demographic health survey
Current Problems in Cardiology
2024-12 | Journal Article
DOI: 10.1016/j.cpcardiol.2024.102861
Source: Crossref

Prevalence and determinants of hypertension among adults in Somalia using Somalia demographic health survey data, SDHS 2020
Current Problems in Cardiology
2024-11 | Journal Article
DOI: 10.1016/j.cpcardiol.2024.102783
ISSN: 0146-2806
Source: Abdisalam Hassan Muse

Analyzing Unimproved Drinking Water Sources and Their Determinants Using Supervised Machine Learning: Evidence from the Somaliland Demographic Health Survey 2020
Water
2024-10 | Journal Article
DOI: 10.3390/w16202986
Source: Multidisciplinary Digital Publishing Institute

Conclusion

Assoc. Prof. Dr. Abdisalam Hassan Muse is a highly qualified candidate for the Best Researcher Award. His strong educational background, extensive professional experience, and commitment to impactful research make him a standout in the field of statistics and data science. Dr. Muse’s innovative approach, coupled with his dedication to community engagement, positions him as a leading figure in advancing computational methodologies for the betterment of society.

 

Masahiro Nishida | Impact Engineering | Best Researcher Award

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Dr. Masahiro Nishida | Impact Engineering | Best Researcher Award

Orcid Profile

Educational Details

B.E. in Mechanical Engineering (1991): Tokyo Institute of Technology.

M.E. in Mechanical Engineering (1993): Tokyo Institute of Technology.

Ph.D. in Mechanical Engineering (1996): Tokyo Institute of Technology, under the supervision of Professor H. Matsumoto. His thesis was titled “Evaluation Method of Mechanical Properties for Material by Phase-Sensitive Acoustic Microscope”.

 

Professional Experience

Prof. Nishida began his career as a Research Associate in the Department of Mechanical Science at Tokyo Institute of Technology from 1996 to 1997. He then joined Nagoya Institute of Technology as a Research Associate in 1997, working under Professor K. Tanaka. He progressed to Lecturer (2001-2004), Associate Professor (2004-2018), and has been a full Professor since 2018. In addition to his academic roles, he has served as the General Manager of the Quality Innovation Techno-Center at Nagoya Institute of Technology since 2022. He has also been a visiting researcher at Luleå University of Technology, Sweden, in 2009.

Research Interest

Prof. Masahiro Nishida’s research focuses on the dynamic behavior of materials under extreme conditions, with particular emphasis on hypervelocity impacts and advanced material properties. His work on hypervelocity impact explores the performance of materials like metals and plastics used in space debris bumpers, carbon fiber-reinforced plastics, and components produced through additive manufacturing. In the field of dynamic strength of advanced materials, he investigates the mechanical properties of recycled aluminum alloys, additive manufacturing materials, and biodegradable plastics using the split Hopkinson pressure bar (SHPB) technique, which allows for high-strain-rate testing. Additionally, his research into the dynamics of heterogeneous materials involves studying the behavior of aggregated soft particles and understanding how contact forces propagate within these assemblies. This combination of experimental and computational approaches provides valuable insights into the resilience and performance of materials in extreme environments.

Top Notable Publications

Effects of electron beam irradiation on hypervelocity impact behavior of carbon fiber reinforced plastic plates
Journal: Journal of Composite Materials
Published: December 2021
DOI: 10.1177/00219983211037049
Citations: Data not provided through Scopus.

Effects of the shapes and addition amounts of crosslinking reagents on the properties of poly‐3‐hydroxybutyrate/poly(caprolactone) blends
Journal: Journal of Applied Polymer Science
Published: June 2021
DOI: 10.1002/app.51210
Citations: Data not provided through Scopus.

Effect of chain extender on morphology and tensile properties of poly(l-lactic acid)/poly(butylene succinate-co-l-lactate) blends
Journal: Materials Today Communications
Published: March 2021
DOI: 10.1016/j.mtcomm.2020.101852
Citations: Data not provided through Scopus.

Correlative analysis between morphology and mechanical properties of poly-3-hydroxybutyrate (PHB) blended with polycaprolactone (PCL) using solid-state NMR
Journal: Polymer Testing
Published: November 2020
DOI: 10.1016/j.polymertesting.2020.106780
Citations: Data not provided through Scopus.

Correlative analysis between solid-state NMR and morphology for blends of poly(lactic acid) and poly(butylene adipate-co-butylene terephthalate)
Journal: Polymer
Published: 2020
DOI: 10.1016/j.polymer.2020.122591
Citations: Data not provided through Scopus.

Effects of deformation rate on tensile properties of ramie fiber/PLA/PBAT composites
Conference: ECCM 2018 – 18th European Conference on Composite Materials
Published: 2020
EID: 2-s2.0-85084162322
Citations: Data not provided through Scopus.

Effects of gamma ray irradiation on penetration hole in and fragment size from carbon fiber reinforced composite plates in hypervelocity impacts
Journal: Composites Part B: Engineering
Published: July 2019
DOI: 10.1016/j.compositesb.2019.04.007
Citations: Data not provided through Scopus.

Influence of impact angle on size distribution of fragments in hypervelocity impacts
Journal: International Journal of Impact Engineering
Published: June 2019
DOI: 10.1016/j.ijimpeng.2019.02.006
Citations: Data not provided through Scopus.

Conclusion

Prof. Masahiro Nishida is a highly qualified candidate for the Best Researcher Award. His strong educational background, extensive research experience, leadership roles, and cutting-edge research in dynamic material properties and hypervelocity impact make him a prominent figure in mechanical engineering. His research aligns well with current industrial needs, particularly in aerospace, sustainability, and material innovation, further enhancing his candidacy for such an award.