Fathalla Rihan | Statistical Analysis | Best Scholar Award

Posted on 12/02/202512/02/2025 by ScienceFather

Prof. Fathalla Rihan | Statistical Analysis | Best Scholar Award

United Arab Emirates University | United Arab Emirates

Publication Profile

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Professor Fathalla A. Rihan: A Distinguished Expert in Mathematical Sciences 📚✨

Current Position(s) & Employment History 🏫

Professor of Mathematics (2017–present)
Department of Mathematical Sciences, College of Science, UAE University, UAE 🇦🇪
Professor of Mathematics (2011–present)
Department of Mathematics (on leave), Faculty of Science, Helwan University, Egypt 🇪🇬
Associate Professor (2012–2017)
Department of Mathematical Sciences, College of Science, UAE University, UAE
Assistant Professor (2008–2012)
Department of Mathematical Sciences, College of Science, UAE University, UAE
Associate Professor of Mathematics (2005–2011)
Department of Mathematics, Faculty of Science, Helwan University, Egypt
Honorary Research Fellow (2000–2010)
School of Mathematics, University of Manchester, UK 🇬🇧
Assistant Professor (2000–2005)
Department of Mathematics, Faculty of Science, Helwan University, Egypt
(On leave for Post-Doctoral research in the UK)
Senior Research Fellow (2003–2006)
Salford University, UK, in collaboration with Met Office (Reading University)
Research Fellow (2001–2003)
School of Mathematics, Manchester University, UK
Postgraduate Studentship and Lecturer Assistant (1996–2000)
Department of Mathematics, Manchester University, UK
Lecturer (1992–1996)
Department of Mathematics, Helwan University, Egypt
Instructor (1987–1992)
Department of Mathematics, Faculty of Science, Helwan University, Egypt

Education 🎓

Doctor of Science (DSc) in Mathematics (2019)
National University of Uzbekistan
Dissertation: “Qualitative and Quantitative Features of Delay Differential Equations and Their Applications”
Ph.D. in Mathematics (2000)
University of Manchester, UK
Thesis: “Numerical Treatment of Delay Differential Equations in the Biosciences”
M.Sc. in Numerical Analysis (1992)
Helwan University, Egypt
Thesis: “Spectral and Pseudo-Spectral Method for Solving Partial Differential Equations Using Orthogonal Polynomials”
B.Sc. in Mathematics (1985)
Alexandria University, Egypt, Graduated with Honours

Research Interests On Statistical Analysis🔬

Prof. Fathalla A. Rihan leads two primary research groups:

Numerical Analysis & Mathematical Biology
- Mathematical modeling of phenomena with time-lags (cell division, population dynamics, infectious diseases, etc.)
- Numerical treatments for Ordinary, Partial, and Delay Differential Equations (DDEs), as well as Fractional Order Differential Equations
- Parameter estimation and sensitivity analysis
Data Assimilation & Numerical Weather Prediction (NWP)
- Advanced data assimilation techniques like 3DVar/4D-Var systems
- Impact of Doppler radial velocities on analysis and forecasting

Research Projects 📊

2024–2026: PI, AUA-UAEU Project: “Continuous Runge-Kutta Methods for Pantograph Delay Differential Equations”
2022–2024: PI, ZU-UAEU Project: “Impact of Stochastic Noise on COVID-19 Dynamics in the UAE”
2022: PI, SURE+ 2022 Program: “Mathematical Modeling of COVID-19 in the UAE”
2021–2023: PI, UPAR-UAEU Project: “Quantitative Features of Delay Differential Equations in Biological Systems”
2017–2019: PI, SQU/UAEU Project: “Delay Differential Models of Immune Response with Viral/Bacterial Infections”

Awards & Recognition 🏆

Resignation Award for Publications in Top 5% Journals (2023)
Member of Mohammed Bin Rashid Academy of Scientists (2021–present)
Top 2% World Scientist (Stanford University 2019–2022)
University Excellence Merit Allowance (2019–2020)
College Excellence Award for Service (2019–2020)
Distinguished Research Awards (2017–2019)
College Award for Scholarly Research (2014–2015)

Visitor ships 🌍

Research Visitor (2000–2001): Manchester University, UK
Research Visitor (2001): University of Hertfordshire, UK
Research Visitor (2003–2004): NCAR & Oklahoma Weather Center, USA

Publication Top Notes

Optimal control of glucose-insulin dynamics via delay differential model with fractional-order

- Authors: Fathalla A. Rihan, K. Udhayakumar
- Journal: Alexandria Engineering Journal
- Year: 2025-02 🗓️

Modeling Hybrid Crossover Dynamics of Immuno‐Chemotherapy and Gene Therapy: A Numerical Approach

- Authors: Muner M. Abou Hasan, Seham M. AL‐Mekhlafi, Fathala A. Rihan, Hannah A. Al‐Ali
- Journal: Mathematical Methods in the Applied Sciences
- Year: 2025-02-03 🗓️

Stabilization of bilinear systems with distributed delays using the Banach state space decomposition method

- Authors: Ayoub Cheddour, Abdelhai Elazzouzi, Fathalla A. Rihan
- Journal: IMA Journal of Mathematical Control and Information
- Year: 2024-12-19 🗓️

Continuous Runge–Kutta schemes for pantograph type delay differential equations

- Authors: Fathalla A. Rihan
- Journal: Partial Differential Equations in Applied Mathematics
- Year: 2024-09 🗓️

Fractional order delay differential model of a tumor-immune system with vaccine efficacy: Stability, bifurcation and control

- Authors: Fathalla A. Rihan, K. Udhayakumar
- Journal: Chaos, Solitons & Fractals
- Year: 2023-08 🗓️

Niansheng Tang | Statistical Methods | Best Researcher Award

Posted on 12/02/202512/02/2025 by ScienceFather

Prof Dr. Niansheng Tang | Statistical Methods | Best Researcher Award

Yunan University | China

Publication Profile

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👨‍🏫 Early Academic Pursuits

Prof. Dr. Niansheng Tang is a distinguished scholar affiliated with Yunnan University, China. His academic journey started with a series of significant achievements and certifications, culminating in his specialization in statistical and nonlinear models. His academic foundation includes attending key international training sessions and engaging with vital academic societies that contributed to his development as a respected academic in his field.

💼 Professional Endeavors and Career

Dr. Tang’s career has been characterized by a series of high-level academic positions. From 2000 to 2020, he held various teaching and research roles, including significant appointments at Yunnan University. He has been deeply involved in statistical research, with a focus on nonlinear models, reproductive dispersion, and statistical inference for incomplete data. His roles have also included administrative and leadership positions within academic organizations and societies.

🔬 Research Focus and Contributions

Dr. Tang’s primary research focuses on statistical modeling, particularly in areas like nonlinear regression, incomplete data inference, and applications in social, economic, and biomedical studies. He has been the principal investigator for multiple funded projects from the Natural Science Foundation of China, Yunnan Province, and the National Social Science Foundation of China. His work has contributed to the understanding of complex data analysis and its application in various fields.

🌍 Impact and Influence

Dr. Tang has made significant contributions to the field of statistics, with his work influencing various sectors including social sciences, economics, and biomedical research. He has been involved with several prominent academic journals and has contributed to the dissemination of knowledge in his field. His research has impacted both theoretical and applied aspects of statistical modeling, and his efforts have been acknowledged globally.

📚 Academic Cites and Recognition

Dr. Tang’s research is widely cited, with his work featured in leading international journals. He has received multiple awards for his contributions to statistical theory and its application in diverse fields. His impact in the statistical community is reflected through various accolades, including recognition as a member of several esteemed academic bodies such as the ISI and the IMS.

💻 Technical Skills and Expertise

With expertise in statistical theory and computational methods, Dr. Tang has advanced the understanding of complex data structures through his work on generalized nonlinear models. His technical proficiency extends to research in incomplete data models and the development of inference methods applicable to small sample sizes, particularly in biomedical studies.

🎓 Teaching Experience

Throughout his career, Dr. Tang has played an important role in mentoring and educating the next generation of statisticians. He has taught various courses at Yunnan University and has supervised numerous graduate students. His teaching style combines theoretical knowledge with practical application, making him a highly regarded educator.

🏛️ Legacy and Future Contributions

Dr. Tang’s legacy in the field of statistics is built on his groundbreaking research, dedication to education, and service to academic societies. Moving forward, he aims to continue influencing the development of statistical methodologies and applying them to emerging areas such as big data analysis and artificial intelligence. His future contributions will likely continue to shape both academic and practical advancements in his field.

🔍 Ongoing Research and Projects

Dr. Tang’s recent and ongoing projects focus on the statistical analysis of reproductive dispersion models, social sciences, and biomedical research. His work continues to garner support from national funding bodies and academic institutions, ensuring the continued impact of his research.

Publication Top Notes

Federated Learning based on Kernel Local Differential Privacy and Low Gradient Sampling

- Authors: Yi Chen, Dan Chen, Niansheng Tang
- Journal: IEEE Access 📡
- Year: 2025 🗓️

The impact of green digital economy on carbon emission efficiency of financial industry: evidence from 284 cities in China

- Authors: Zhichuan Zhu, Yuxin Wan, Niansheng Tang
- Journal: Environment, Development and Sustainability 🌍💡
- Year: 2025 🗓️

Tuning-free sparse clustering via alternating hard-thresholding

- Authors: Wei Dong, Chen Xu, Jinhan Xie, Niansheng Tang
- Journal: Journal of Multivariate Analysis 📊
- Year: 2024 🗓️

Variational Bayesian approach for analyzing interval-censored data under the proportional hazards model

- Authors: Wenting Liu, Huiqiong Li, Niansheng Tang, Jun Lyu
- Journal: Computational Statistics and Data Analysis 💻📉
- Year: 2024 🗓️

Semiparametric Bayesian approach to assess non-inferiority with assay sensitivity in a three-arm trial with normally distributed endpoints

- Authors: Niansheng Tang, Fan Liang, Depeng Jiang
- Journal: Computational Statistics 💻📊
- Year: 2024 🗓️

Naiwei Lu | Data Analysis | Best Researcher Award

Posted on 17/01/202517/01/2025 by ScienceFather

Assoc Prof Dr. Naiwei Lu | Data Analysis | Best Researcher Award

Changsha University of Science of Technology, China

Author Profiles

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👨‍🏫 Associate Prof. Dr. Naiwei Lu

Assoc. Prof. Dr. Naiwei Lu is an Associate Professor in Civil Engineering at Changsha University of Science and Technology (CSUST), China. His research primarily focuses on reliability and safety in bridge engineering. He has a strong background in system reliability evaluation, fatigue analysis, and structural health monitoring, which he applies to the engineering and maintenance of long-span bridges. Dr. Lu is an active member of various international research communities and has been involved in multiple national and international projects.

🎓 Education Background

Dr. Naiwei Lu earned his Ph.D. in Civil Engineering from Changsha University of Science and Technology (CSUST) in 2015, under the supervision of Prof. Yang Liu. Prior to that, he completed his Master’s degree in Civil Engineering in 2011 and his Bachelor’s degree in Bridge Engineering in 2008, all at CSUST, Changsha, China. His academic journey laid a strong foundation for his expertise in bridge engineering and reliability analysis.

💼 Employment and Research Experience

Dr. Lu’s academic career began in 2015 when he became a Postdoctoral Researcher at Southeast University in Nanjing, China, where he worked under Prof. Mohammad Noori. He also held a Postdoctoral Researcher position at Leibniz University Hannover, Germany, working with Prof. Michael Beer. Since 2020, Dr. Lu has been serving as an Associate Professor at CSUST, where he also previously worked as a Lecturer from 2017 to 2019. His diverse academic and international experiences contribute to his deep expertise in bridge engineering.

💰 Research Funding

Dr. Lu has been the Principal Investigator (PI) of several funded research projects, including the National Science Funding in China for research on structural health monitoring of suspension bridges and the fatigue reliability evaluation of steel bridge decks. He has received significant funding support for his work in system reliability and dynamic analysis, with total funding exceeding ¥1 million for his various research initiatives. These projects aim to develop advanced methods for assessing the reliability and safety of long-span bridges.

🔍 Research Interests

Dr. Lu’s research spans several cutting-edge topics in structural engineering. His main research interests include system reliability evaluation of long-span bridges using intelligent algorithms 🤖, fatigue reliability of stay cables and orthotropic steel bridge decks 🌉, and probabilistic modeling using data from structural health monitoring 📊. He is also focused on intelligent maintenance and management of in-service bridges ⚙️, as well as uncertainty quantification in structural engineering 🛠️.

📚 Teaching Experience

As an educator, Dr. Lu teaches undergraduate courses such as Principle of Structural Design (in both Chinese and English) and Building Information Modeling (BIM) Technology (in Chinese). He has supervised 24 undergraduate students and 4 postgraduate students between 2017 and 2020, guiding them in various aspects of civil engineering, particularly related to bridge design, maintenance, and reliability.

🏗️ Engineering Activities

In addition to his academic role, Dr. Lu is a Registered Construction Engineer and a Registered Inspection Engineer in Municipal Engineering and Bridge & Tunnel Engineering, respectively. His engineering activities include overseeing the structural safety of long-span bridges during construction 🏗️, conducting structural health monitoring of suspension bridges 🌉, and contributing to the detection and reinforcement of aging bridges 🛠️. He has also been involved in the advance geological forecasting and monitoring of tunnels during construction, working on over five extra-long tunnels.

Dr. Naiwei Lu’s work integrates advanced intelligent algorithms, data-driven methods, and structural health monitoring to enhance the safety, reliability, and longevity of bridges and infrastructure systems. His research and engineering expertise continue to make significant contributions to the field of civil engineering.

📖Top Noted Publications

Structural damage diagnosis of a cable-stayed bridge based on VGG-19 networks and Markov transition field: numerical and experimental study

Authors: Naiwei Lu, Zengyifan Liu, Jian Cui, Lian Hu, Xiangyuan Xiao, Yiru Liu

Journal: Smart Materials and Structures

Year: 2025

Coupling effect of cracks and pore defects on fatigue performance of U-rib welds

Authors: Yuan Luo, Xiaofan Liu, Fanghuai Chen, Haiping Zhang, Xinhui Xiao, Naiwei Lu

Journal: Structures

Year: 2025

A Time–Frequency-Based Data-Driven Approach for Structural Damage Identification and Its Application to a Cable-Stayed Bridge Specimen

Authors: Naiwei Lu, Yiru Liu, Jian Cui, Xiangyuan Xiao, Yuan Luo, Mohammad Noori

Journal: Sensors

Year: 2024

A Novel Method of Bridge Deflection Prediction Using Probabilistic Deep Learning and Measured Data

Authors: Xinhui Xiao, Zepeng Wang, Haiping Zhang, Yuan Luo, Fanghuai Chen, Yang Deng, Naiwei Lu, Ying Chen

Journal: Sensors

Year: 2024

Experimental and numerical investigation on penetrating cracks growth of rib-to-deck welded connections in orthotropic steel bridge decks

Authors: Zitong Wang, Jun He, Naiwei Lu, Yang Liu, Xinfeng Yin, Haohui Xin

Journal: Structures

Year: 2024

Fatigue Reliability Assessment for Orthotropic Steel Decks: Considering Multicrack Coupling Effects

Authors: Jing Liu, Yang Liu, Guodong Wang, Naiwei Lu, Jian Cui, Honghao Wang

Journal: Metals

Year: 2024

Wenhai Shi | Predictive Modeling Innovations | Best Researcher Award

Posted on 09/12/202409/12/2024 by ScienceFather

Prof. Wenhai Shi | Energy and Utilities Analytics | Best Researcher Award

Professor at Chang’an University, China

👨‍🎓Author Profiles

🎓 Early Academic Pursuits

Prof. Wenhai Shi’s academic journey is marked by a steadfast dedication to environmental sciences. He earned a Ph.D. in Soil Science (2015-2018) from the University of Chinese Academy of Sciences, Yangling, China, focusing on critical ecological processes. Prior to this, he completed his M.S. in Water Conservancy Engineering (2011-2014) at Guangxi University, Nanning, and a B.S. in Water Resources and Hydropower Engineering (2004-2008) from Xi’an University of Technology. His rigorous academic foundation laid the groundwork for his impactful career in hydrology and soil science.

💼 Professional Endeavors

Prof. Shi has built a robust professional portfolio through progressive academic and industry roles. Currently an Associate Professor at the School of Water and Environment, Chang’an University, Xi’an, he has held positions as a Lecturer and Assistant Professor in esteemed institutions, alongside early-career roles as a Laboratory Technician and Reservoir Dispatcher. These experiences have sharpened his expertise in managing large-scale water resource systems and developing ecohydrological solutions.

🌍 Contributions and Research Focus

Prof. Shi’s research addresses critical environmental challenges, including multi-scale ecohydrological processes, land surface soil and water dynamics, and the nutrient cycle in Earth’s critical zones. He is particularly renowned for investigating soil erosion mechanisms and advancing water conservation techniques. His projects, supported by prestigious bodies like the National Natural Science Foundation of China, focus on organic and inorganic carbon dynamics, hydrological simulation, and water cycle evolution in fragile ecosystems like the Loess Plateau.

🌟 Impact and Influence

Through his contributions, Prof. Shi has significantly influenced both academic and practical domains. As a reviewer for prominent international journals such as Land, Hydrology, and Remote Sensing, he ensures the dissemination of high-quality scientific knowledge. His research has enhanced understanding of hydrological systems and informed policies on sustainable water and soil management.

📚 Academic Cites

Prof. Shi is an active member of leading academic societies, including the China Soil Society and the China Society of Soil and Water Conservation, where he contributes to advancing scientific discourse. As a peer review expert for the National Natural Science Foundation of China and the Ministry of Education, his expertise shapes the future of soil and hydrology research in China and beyond.

💻 Technical Skills

With a diverse skill set, Prof. Shi excels in hydrological modeling, ecohydrological simulations, and spatial variability analysis. His technical acumen is complemented by his proficiency in research tools, project management, and data-driven decision-making in environmental sciences.

🏫 Teaching Experience

An accomplished educator, Prof. Shi has developed and taught both undergraduate and postgraduate courses, such as Soil Mechanics, Modern Hydrology, and Soil and Water Conservation. His innovative teaching methods inspire students to engage deeply with critical environmental issues. Notably, he led his students to secure the National First Prize in the 7th National College Students Water Conservancy Innovation Design Competition.

🌟 Legacy and Future Contributions

Prof. Shi’s accolades, including being recognized as a Young Academic Backbone under the Chang’an Scholars Talent Support Program, underscore his lasting contributions to academia and society. He continues to lead impactful research, mentor the next generation of environmental scientists, and innovate in teaching. Prof. Shi’s vision for the future includes enhancing sustainable practices and advancing ecohydrological resilience globally.

📖Top Noted Publications

An improved method that incorporates the estimated runoff for peak discharge prediction on the Chinese Loess Plateau

- Authors: Shi, W.; Wang, M.; Li, D.; Li, X.; Sun, M.
- Journal: International Soil and Water Conservation Research
- Year: 2023

Effects of Crop Rotation and Topography on Soil Erosion and Nutrient Loss under Natural Rainfall Conditions on the Chinese Loess Plateau

- Authors: Li, C.; Shi, W.; Huang, M.
- Journal: Land
- Year: 2023

An improved MUSLE model incorporating the estimated runoff and peak discharge predicted sediment yield at the watershed scale on the Chinese Loess Plateau

- Authors: Shi, W.; Chen, T.; Yang, J.; Lou, Q.; Liu, M.
- Journal: Journal of Hydrology
- Year: 2022

Revised runoff curve number for runoff prediction in the Loess Plateau of China

- Authors: Shi, W.; Wang, N.; Wang, M.; Li, D.
- Journal: Hydrological Processes
- Year: 2021

Predictions of soil and nutrient losses using a modified SWAT model in a large hilly-gully watershed of the Chinese Loess Plateau

- Authors: Shi, W.; Huang, M.
- Journal: International Soil and Water Conservation Research
- Year: 2021

Yanjie Zhu | Algorithm Development | Best Researcher Award

Posted on 30/11/202430/11/2024 by ScienceFather

Prof. Yanjie Zhu | Algorithm Development | Best Researcher Award

Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, China

👨‍🎓Professional Profiles

🔬 Summary

Prof. Yanjie Zhu is a renowned expert in fast magnetic resonance imaging (MRI) and its applications in medical diagnostics. He specializes in developing innovative imaging techniques through machine learning, deep learning, and model-driven methods. As a Professor at the Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, he leads cutting-edge research projects focused on cardiovascular imaging, brain health, and intelligent diagnostic tools.

🎓 Education

Prof. Zhu earned his Ph.D. in Circuits and Systems from the Shanghai Institute of Technical Physics, Chinese Academy of Sciences, China (2006-2011). He also holds a B.S. in Electronic Engineering and Information Science from the University of Science and Technology of China, Hefei (2002-2006).

🏫 Professional Experience

Prof. Zhu has a distinguished academic career at the Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, where he progressed from Assistant Professor (2011-2015) to Associate Professor (2015-2020), and is currently a Professor (2020-present). Additionally, he served as a Visiting Scholar (2017-2018) at Harvard Medical School and Beth Israel Deaconess Medical Center, Boston, MA, under the guidance of Reza Nezafat.

📚 Academic Contributions

Prof. Zhu has published several impactful papers in the field of MRI and medical imaging. Notable works include:

“Online reconstruction of fast dynamic MR imaging using deep low-rank plus sparse network,” IEEE CBMS, 2022.
“k-space based reconstruction method for wave encoded bSSFP sequence,” CECIT, 2021.
“Quantification of pectinate muscles inside left atrial appendage from CT images using fractal analysis,” ICMIPE, 2021.
Myocardial Edema Imaging – A Comparison of Three Techniques, ISMRM 2018 (Power Pitch, Magna Cum Laude Merit Award).

🔍 Research Interests

Prof. Zhu’s research interests revolve around model-driven fast MRI techniques, generative model-based adaptive MRI methods, and diffusion tensor and edema imaging for myocardial and brain tissue. He is also focused on intelligent diagnosis for the early detection of stroke-related plaques and other cardiovascular conditions.

💻 Technical Skills

Prof. Zhu is highly skilled in MRI imaging techniques, including fast MRI, cardiac MRI, and brain MRI. He also excels in deep learning and AI-based image reconstruction methods, along with proficiency in medical imaging software and model-driven approaches. His expertise in data analysis and computational methods has contributed to advancing medical applications.

👨‍🏫 Teaching Experience

Throughout his career, Prof. Zhu has mentored and taught graduate students and professionals in the fields of MRI technology, medical imaging, and computational healthcare methods. His research-driven approach has helped develop comprehensive educational materials that support the training of professionals in advanced imaging systems.

📖Top Noted Publications

RS-MOCO: A deep learning-based topology-preserving image registration method for cardiac T1 mapping

Authors: Chiyi Huang, Longwei Sun, Dong Liang, Haifeng Liang, Hongwu Zeng, Yanjie Zhu
Journal: Computers in Biology and Medicine
Year: 2024

High-Frequency Space Diffusion Model for Accelerated MRI

Authors: Chentao Cao, Zhuo-Xu Cui, Yue Wang, Shaonan Liu, Taijin Chen, Hairong Zheng, Dong Liang, Yanjie Zhu
Journal: IEEE Transactions on Medical Imaging
Year: 2024

SPIRiT-Diffusion: Self-Consistency Driven Diffusion Model for Accelerated MRI

Authors: Zhuo-Xu Cui, Chentao Cao, Yue Wang, Sen Jia, Jing Cheng, Xin Liu, Hairong Zheng, Dong Liang, Yanjie Zhu
Journal: IEEE Transactions on Medical Imaging
Year: 2024

A Two-Stage Generative Model with CycleGAN and Joint Diffusion for MRI-based Brain Tumor Detection

Authors: Wenxin Wang, Zhuo-Xu Cui, Guanxun Cheng, Chentao Cao, Xi Xu, Ziwei Liu, Haifeng Wang, Yulong Qi, Dong Liang, Yanjie Zhu
Journal: IEEE Journal of Biomedical and Health Informatics
Year: 2024

High efficiency free-breathing 3D thoracic aorta vessel wall imaging using self-gating image reconstruction

Authors: Caiyun Shi, Congcong Liu, Shi Su, Haifeng Wang, Xin Liu, Hairong Zheng, Dong Liang, Yanjie Zhu
Journal: Magnetic Resonance Imaging
Year: 2024

Physics-Driven Deep Learning Methods for Fast Quantitative Magnetic Resonance Imaging

Authors: Yanjie Zhu, Jing Cheng, Zhuo-Xu Cui, et.al.
Journal: IEEE Signal Processing Magazine
Year: 2023

Haixia Mao | Data Science | Best Researcher Award

Posted on 25/11/202425/11/2024 by ScienceFather

Dr. Haixia Mao | Data Science | Best Researcher Award

Shenzhen Polytechnic University, China

👨‍🎓Professional Profile

Scopus Profile

👩‍🏫 Summary

Dr. Haixia Mao is an Associate Professor at the School of Automobile and Transportation at Shenzhen Polytechnic University, China. She holds a Ph.D. in Geographic Information System (GIS) and Remote Sensing from the Hong Kong Polytechnic University. Her research focuses on GIS-T, big data analytics, and analyzing urban mobility patterns, using spatial-temporal data from transportation systems to improve urban planning and human behavior modeling.

🎓 Education

Dr. Mao earned her Ph.D. in GIS and Remote Sensing from the Hong Kong Polytechnic University in 2010. She also completed her M.S. in GIS at Wuhan University in 2004 and her B.S. in Photogrammetry and Remote Sensing from Wuhan University.

💼 Professional Experience

Dr. Mao currently serves as an Associate Professor at Shenzhen Polytechnic University (since 2012), where she has contributed to the development of transportation-related GIS courses. Previously, she worked as a Postdoctoral Researcher at the Hong Kong Polytechnic University from 2014 to 2016, furthering her expertise in urban computing and GIS.

📚 Research Interests

Her research encompasses GIS-T (Geographic Information Systems for Transportation), big data analytics, remote sensing, deep learning, and urban planning. She investigates the mobility patterns of citizens through traffic data (including taxis, buses, and metro) and leverages spatial-temporal data to enhance urban infrastructure and predict human behavior.

🏅 Academic Contributions

Dr. Mao has authored over 20 peer-reviewed journal articles and conference papers. She has also been awarded a patent for a caching system with a new cache placement method. She has received research grants for spatial-temporal data analytics in transportation and has actively contributed to major projects in urban computing.

💻 Technical Skills

Dr. Mao’s technical expertise spans GIS, remote sensing, big data analytics, deep learning, and spatial-temporal data analysis. She integrates these advanced techniques to solve complex transportation and urban planning challenges.

📚 Teaching Experience

Dr. Mao has taught several courses since 2012 at Shenzhen Polytechnic University, including GIS for Transportation, Traffic Engineering Cartography, and Traffic Information Processing. She has a long-standing dedication to educating future professionals in the field of urban planning and transportation technology.

📖Top Noted Publications

Multiple sclerosis lesions segmentation based on 3D voxel enhancement and 3D alpha matting

Authors: Sun, Y., Zhang, Y., Wang, X., Zeng, Z., Mao, H.
Journal: Chinese Journal of Medical Physics
Year: 2022

Customer attractiveness evaluation and classification of urban commercial centers by crowd intelligence

Authors: Mao, H., Fan, X., Guan, J., Wang, Y., Xu, C.
Journal: Computers in Human Behavior
Year: 2019

When Taxi Meets Bus: Night bus stop planning over large-scale traffic data

Authors: Xiao, L., Fan, X., Mao, H., Lu, P., Luo, S.
Conference: Proceedings – 2016 7th International Conference on Cloud Computing and Big Data, CCBD 2016
Year: 2017

Characterizing On-Bus WiFi passenger behaviors by approximate search and cluster analysis

Authors: Jiang, M., Fan, X., Zhang, F., Mao, H., Liu, R.
Conference: Proceedings – 2016 7th International Conference on Cloud Computing and Big Data, CCBD 2016
Year: 2017

Efficient visibility analysis for massive observers

Authors: Wang, W., Tang, B., Fan, X., Yang, H., Zhu, M.
Conference: Procedia Computer Science
Year: 2017

Web access patterns enhancing data access performance of cooperative caching in IMANETs

Authors: Fan, X., Cao, J., Mao, H., Zhao, Y., Xu, C.
Conference: Proceedings – IEEE International Conference on Mobile Data Management
Year: 2016

Theresa Kühle | Data Analysis | Best Researcher Award

Posted on 20/11/202420/11/2024 by ScienceFather

Mrs. Theresa Kühle | Data Analysis | Best Researcher Award

Mrs. Theresa Kühle at Universität Münster, Germany

👨‍🎓Professional Profile

Orcid Profile

🌟 Summary

Theresa Kühle is a dedicated medical student at the University of Münster, Germany, with a strong focus on pediatric cardiology, prenatal medicine, and psychosomatic disorders. Passionate about research and clinical practice, she has presented at several medical congresses and published research in the field of fetal heart failure. As a Cusanuswerk scholarship recipient, she is committed to advancing in her medical career with international experience.

🎓 Education

Since 2019, Theresa has been studying medicine at the University of Münster, Germany. She also gained international medical experience at the Universidad de Valladolid, Spain, in 2023. Theresa completed her Abitur at Gymnasium Schloss Neuhaus, Paderborn, in 2018, with an outstanding grade of 1.0.

💼 Professional Experience

Theresa has gained extensive practical experience in hospitals and medical settings. Since 2024, she has been working as an OP student in the Department of Gynaecology and Obstetrics at St. Franziskus-Hospital in Münster. She also gained clinical experience in pediatrics, cardiology, neurology, urology, and psychosomatic medicine at the University Hospital Münster. In addition, she has been a tutor for a sonography course at her university since 2024.

📑 Academic Citations

In 2024, Theresa presented posters at the 65th DGGG Congress in Berlin and the 47th Tri-Nation Meeting in Salzburg. She has also published a research paper on “Dyssynchronous fetal heart failure in maternal diabetes” with Prof. Dr. Ralf Schmitz, highlighting her active involvement in medical research.

🛠️ Technical Skills

Theresa possesses advanced skills in sonography, as evidenced by her role as a tutor in the ultrasound course at the University of Münster. She has a deep understanding of prenatal diagnostics, particularly in echocardiography and M-mode software. In addition, she is fluent in English (C1/C2), Spanish (B2.2), and French (B2), with proficiency in Latin.

👩‍🏫 Teaching Experience

Theresa has enriched her teaching portfolio by serving as a tutor for the sonography course at the University of Münster since 2024. She has also gained hands-on teaching experience in psychosomatic treatments, pediatrics, and psychotherapeutic practices during her medical training.

🔬 Research Interests

Her research focuses on pediatric cardiology, particularly congenital heart defects, and prenatal medicine, with a specific interest in fetal heart failure caused by maternal diabetes. Additionally, Theresa is passionate about psychosomatic medicine and psychological health treatments for children and adolescents.

📖Top Noted Publication