Niansheng Tang | Statistical Methods | Best Researcher Award

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

Yunan University | China

Publication Profile

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Orcid

👨‍🏫 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

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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

Salahuddin Mahmud – Data Interpretation – Global Data Innovation Recognition Award 

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Assoc Prof Dr Salahuddin Mahmud - Data Interpretation - Global Data Innovation Recognition Award 

Salahuddin Mahmud - Bangladesh Shishu Hospital & Institute - Bangladesh 

Author Profile

Early Academic Pursuits

Assoc Prof DR. Salahuddin Mahmud began his academic journey with a solid foundation in science, completing his SSC in 1990 and HSC in 1992 from the Education Board, Dhaka, with a focus on the science stream. Following this, he pursued his MBBS from Dhaka University, specializing in Medicine, Surgery, and Gynecology, which he completed in 2000. His commitment to pediatric care led him to achieve an MD in Pediatrics from BSMMU in 2010.

Professional Endeavors

Over the years,  Assoc Prof Dr. Mahmud has held various significant roles at the Bangladesh Shishu Hospital & Institute (BSHI). He started as a Resident Medical Officer in Pediatric Medicine in 2004 and transitioned to the Department of Pediatric Gastroenterology, Hepatology & Nutrition by 2011. Progressing through the ranks, he has served as Assistant Professor and currently holds the position of Associate Professor in the same department.

Additionally, Assoc Prof Dr. Mahmud plays crucial supervisory and academic roles, supervising MD (Pediatrics) residency courses and co-guiding MD thesis projects, enhancing the quality of pediatric care and education in Bangladesh.

Contributions and Research Focus

Assoc Prof Dr. Mahmud's contributions to pediatric gastroenterology, hepatology, and nutrition are commendable. His participation in workshops and conferences like the 9th ISPGHAN Conference in India and the Motility Workshop in New Delhi underscores his commitment to advancing the field. His research and expertise cover areas such as pediatric GI & liver issues, metabolic liver diseases, and enteral & parenteral nutrition, focusing on improving diagnostic and treatment modalities.

Accolades and Recognition

His active involvement and expertise have garnered recognition, both nationally and internationally. He is a life member of the Bangladesh Pediatric Association and holds foreign memberships in prestigious organizations like ISPGHAN, NASPGHAN, and APPSPGHAN, highlighting his standing in the global pediatric community.

Impact and Influence

Assoc Prof Dr. Mahmud's impact extends beyond his clinical and academic roles. As an executive member of BASPGAN, he influences policy and practice in pediatric gastroenterology, hepatology, and nutrition in Bangladesh. His research and teachings shape future pediatricians, ensuring that the next generation is equipped with cutting-edge knowledge and skills.

Legacy and Future Contributions

With a rich legacy of academic achievements, professional endeavors, and contributions to pediatric care and research, Assoc Prof Dr. Salahuddin Mahmud continues to inspire and lead. His future contributions are anticipated to further advance pediatric gastroenterology and hepatology in Bangladesh and beyond. As an associate professor and respected figure in his field, he remains committed to mentoring future professionals, conducting groundbreaking research, and elevating standards of care for pediatric patients.

Notable Publications