Pengxia Zhou | Physics | Best Researcher Award

Prof. Dr. Pengxia Zhou | Physics | Best Researcher Award

Associate professor at Nantong University, China

Zhou Pengxia (Zhou Pengxia) ๐ŸŽ“, born on October 24, 1977 ๐ŸŽ‚, is a dedicated physicist and educator at the School of Physical Science and Technology, Nantong University ๐Ÿ‡จ๐Ÿ‡ณ. With over two decades of experience, she has contributed significantly to condensed matter physics and multiferroic materials research โš›๏ธ. She earned her Ph.D. from Nanjing University and conducted postdoctoral research at leading institutions in Singapore ๐ŸŒ. As the principal investigator of an NSFC-funded project, she explores octahedral rotations in perovskite superlattices ๐Ÿงช. Her work bridges teaching and innovation, advancing the frontiers of physics through both academia and international collaboration ๐ŸŒŸ.

Professional Profile:

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๐Ÿ”น Education and Experienceย 

๐Ÿ“˜ Education:

  • ๐ŸŽ“ 1997โ€“2001: Bachelor’s Degree in Physics โ€“ Yanbei Normal College

  • ๐Ÿ“š 2001โ€“2004: Masterโ€™s Degree in Condensed Matter Physics โ€“ Yangzhou University

  • ๐Ÿง  2011โ€“2015: Doctorโ€™s Degree in Physics โ€“ Nanjing University

๐Ÿง‘โ€๐Ÿซ Professional Experience:

  • ๐Ÿซ 2004โ€“Present: Lecturer โ€“ Nantong University

  • ๐ŸŒ 2017.10โ€“2018.02: Visiting Scholar โ€“ Singapore University of Technology and Design

  • ๐ŸŒ 2018.09โ€“2019.08: Research Fellow โ€“ National University of Singapore

๐Ÿ”น Professional Developmentย 

Dr. Zhou Pengxiaโ€™s professional journey reflects her passion for physics and global academic growth ๐ŸŒ๐Ÿ“ˆ. She has participated in international collaborations in Singapore, enriching her research and teaching perspectives ๐Ÿ‡ธ๐Ÿ‡ฌ๐Ÿ”ฌ. At Nantong University, she not only teaches but also mentors students in advanced materials science ๐ŸŽ“๐Ÿงช. Her participation in cutting-edge research on perovskite superlattices and multiferroicity has positioned her as a recognized contributor in her field โš›๏ธ. Through continual learning, overseas exchanges, and scientific leadership, Dr. Zhou remains committed to academic excellence and innovation in physical science education and research ๐Ÿ“˜๐ŸŒŸ.

๐Ÿ”น Research Focusย 

Dr. Zhou Pengxia’s research is centered around condensed matter physics with a specific emphasis on multiferroic materials and perovskite superlattices ๐Ÿงฒโšก. She investigates how octahedral rotation affects multiferroicity, exploring mechanisms to enhance functional properties of complex oxides ๐Ÿงช๐Ÿงฌ. Her work contributes to the understanding and engineering of materials that exhibit both ferroelectric and magnetic properties โ€“ critical for next-generation electronic devices ๐Ÿ’ป๐Ÿ”‹. With a focus on crystal structures and symmetry interactions, her research bridges fundamental science and potential applications in sensors, memory devices, and spintronics ๐ŸŒ๐Ÿ”ง. Zhou’s interdisciplinary approach adds great value to material innovation ๐Ÿ”๐Ÿง .

๐Ÿ”น Awards and Honorsย 

๐Ÿ† Awards & Honors:

  • ๐ŸŒŸ Principal Investigator โ€“ National Natural Science Foundation of China (2017โ€“2019) for research on perovskite superlattices

  • ๐ŸŽ“ Invited Research Fellow โ€“ National University of Singapore (2018โ€“2019)

  • ๐ŸŒ International Collaboration Grant โ€“ Singapore University of Technology and Design (2017โ€“2018)

Publication Top Notes

1. Employing interpretable multi-output machine learning to predict stable perovskites in photovoltaics

Journal: Materials Today Communications, 2025
DOI: 10.1016/j.mtcomm.2025.112552
Summary:
This study leverages interpretable multi-output machine learning models to predict thermodynamically stable perovskite materials for photovoltaic applications. The key innovation lies in the simultaneous prediction of multiple material properties (e.g., stability, band gap, defect tolerance) using models that offer transparency into decision-making (e.g., SHAP values, decision trees). This work contributes to faster and explainable discovery of efficient perovskites for solar cell design.

2. A first-principles study on the multiferroicity of semi-modified Xโ‚‚M (X = C, Si; M = F, Cl) monolayers

Journal: Physical Chemistry Chemical Physics, 2023
DOI: 10.1039/D2CP04575C
Summary:
This DFT-based study explores multiferroic behavior in 2D monolayers composed of Xโ‚‚M (X = C, Si; M = F, Cl), highlighting their coexisting ferroelectric and magnetic properties. The findings suggest semi-modified 2D materials could serve as candidates for spintronic and memory devices, due to their tunable multiferroic characteristics.

3. Theoretical investigation of the magnetic and optical properties in a transition metal-doped GaTeCl monolayer

Journal: Physical Chemistry Chemical Physics, 2023
DOI: 10.1039/D3CP02313C
Summary:
This study investigates how doping GaTeCl monolayers with transition metals (e.g., Mn, Fe, Co) affects their magnetic and optical behavior. Using DFT, the authors show enhanced magneto-optical properties, suggesting that doped GaTeCl systems are promising for optoelectronic and spintronic devices.

4. Magnetism and hybrid improper ferroelectricity in LaMOโ‚ƒ/YMOโ‚ƒ superlattices

Journal: Phys. Chem. Chem. Phys., 2019
Author: Pengxia Zhou
Summary:
This work presents a theoretical analysis of LaMOโ‚ƒ/YMOโ‚ƒ (M, Y = transition metals) superlattices, showing hybrid improper ferroelectricity arising from coupling between octahedral tilting and rotations, along with magnetic ordering. The results support the design of multifunctional oxide heterostructures combining electric and magnetic orderings.

5. The excitonic photoluminescence mechanism and lasing action in band-gap-tunable CdSโ‚โˆ’โ‚“Seโ‚“ nanostructures

Journal: Nanoscale, 2016
Author: Pengxia Zhou
Summary:
This paper discusses CdSโ‚โˆ’โ‚“Seโ‚“ nanostructures with tunable band gaps. The team demonstrates strong excitonic photoluminescence and low-threshold lasing, linking optical properties to composition and quantum confinement. It provides a foundational understanding for nanoscale optoelectronic and laser devices.

6. Ferroelectricity driven magnetism at domain walls in LaAlOโ‚ƒ/PbTiOโ‚ƒ superlattices

Journal: Scientific Reports, 2015
Author: Pengxia Zhou
Summary:
This study reveals that in LaAlOโ‚ƒ/PbTiOโ‚ƒ superlattices, ferroelectric domain walls can induce localized magnetic moments due to lattice distortions and charge redistributions. This domain-wall magnetism introduces the potential for non-volatile magnetic memory controlled by ferroelectric domains.

Conclusion:

Dr. Zhou Pengxia is a suitable candidate for a Best Researcher Award, particularly in the fields of condensed matter physics and material science. Her leadership in nationally funded research, international collaboration experience, and long-standing academic service reflect a researcher committed to scientific advancement and knowledge dissemination. While her publication record and citation metrics were not provided, her PI role on an NSFC project suggests peer recognition and scholarly maturity.

Abdisalam Hassan Muse | Computational Methods | Best Researcher Award

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

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 โ€“ Oct 2022). He also holds two Master’s degrees: an MSc in Climate Change and Environmental Sustainability from Amoud University, Borama, Somalia (September 2018 โ€“ Incomplete), and an MSc in Mathematics and Statistics from the same institution (September 2015 โ€“ July 2017). His diverse academic foundation also includes a BA in Islamic Studies from Beder International University, Borama, Somalia (September 2013 โ€“ July 2016), a BSc in Mathematics and Physics from Amoud University (September 2010 โ€“ July 2012), and Diplomas in Islamic Studies (2008โ€“2010) and Education for Mathematics and Physics (2005โ€“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 โ€“ 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. Museโ€™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
Atenciรณn 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.