Daniel Shek | Latent class analysis | Best Researcher Award

Congratulations, Daniel Shek | Best Researcher Award Winner! 🏅🏆

Prof Daniel Shek : Latent class analysis🧑🏻‍🎓

Congratulations to Prof. Daniel T.L. Shek on winning the Best Researcher Award in Latent Class Analysis at the International Research Data Analysis Excellence Awards! This prestigious honor recognizes his outstanding contributions to research methodology and his expertise in advancing the field through innovative applications of latent class analysis. Prof. Shek's dedication to excellence has truly set a benchmark in international research. Well-deserved recognition for a distinguished researcher!

Professional Profiles:

Early Academic Pursuits:

Daniel T.L. Shek began his academic journey by obtaining a Bachelor of Social Sciences (B.Soc.Sc.) with Second Class honors, majoring in Psychology, from The University of Hong Kong (October 1976 – July 1979). He continued his academic pursuits at the same institution, earning a Ph.D. in Psychology from The University of Hong Kong (October 1979 – August 1983).

Professional Endeavors:

Dr. Shek's professional career has been marked by significant contributions to academia and social sciences. His full-time teaching experience commenced as a Demonstrator in the Department of Psychology at The University of Hong Kong (September 1979 – August 1983). Over the years, he held various roles at institutions such as City Polytechnic of Hong Kong and The Chinese University of Hong Kong, where he served as a Lecturer, Senior Lecturer, and ultimately as a Professor I until June 2009. Since July 2009, he has been a key figure at The Hong Kong Polytechnic University, holding the positions of Chair Professor of Applied Social Sciences, Li and Fung Professor in Service Leadership Education, and Associate Vice President (Undergraduate Programme).

Contributions and Research Focus:

Dr. Shek's academic contributions extend beyond teaching to include supervision of numerous post-graduate theses. He has successfully supervised Ph.D., Doctor of Health Science, Doctor of Social Work, M.Phil., and M.S.W. students, with several recipients of the Best Thesis Award at institutions such as The Chinese University of Hong Kong and The Hong Kong Polytechnic University.

Accolades and Recognition:

Daniel T.L. Shek is a recognized figure in the field, holding prestigious titles such as Fellow of The Hong Kong Psychological Society (1998 – Present) and Changjiang Scholar (Changjiang Chair Professor) since 2019. His commitment to community service is evident through roles such as Chairman of the Executive Committee for the Heep Hong Society for Handicapped Children, Vice-Chairman of the Public Policy Research Fund, and Chairman of the Family Council, among others.

Impact and Influence:

As a prolific figure in academia, Dr. Shek has been extensively involved in editorial boards, including serving as the Editor-in-Chief of "Applied Research in Quality of Life" and participating in various other renowned journals. His research interests span diverse areas, including youth development, family studies, and mental health, making a lasting impact on these fields.

Legacy and Future Contributions:

Daniel T.L. Shek's legacy is characterized by a multifaceted career, marked by academic excellence, community service, and editorial contributions. His commitment to quality of life research, mentorship, and community engagement positions him as a significant figure whose contributions will likely continue to shape the landscape of applied social sciences in the years to come.

Notable publication:

Using attention-based neural networks for predicting student learning outcomes in service-learning

Use of instructional videos in leadership education in higher education under COVID-19: A qualitative study

Perceived school climate and adolescent behaviors among Chinese adolescents: Mediating effect of social-emotional learning competencies

Network Analysis of Mental Health Problems in Young People: Reflections on the 5 Ts

Risk Factors and Protective Factors of Internet Addiction in University Students during the Pandemic: Implications for Prevention and Treatment

 

International Research Data Analysis Excellence Awards | Award Winners 2023

Raj kumar Singh

Congratulations, Raj kuma Singh |  Best Researcher  Award  Winner 2023 🏆

Raj kumar Singh : Satellite remote sensing, Machine learning

Raj Kumar Singh's groundbreaking work in the realms of satellite remote sensing and machine learning has earned him the esteemed Young Scientist Award at the International Research Data Analysis Excellence Awards. His innovative approach to leveraging satellite data and cutting-edge machine learning algorithms has not only advanced scientific understanding but has also showcased his commitment to pushing the boundaries of research.This accolade serves as a testament to Singh's dedication, talent, and exceptional capabilities in utilizing technology to unravel complex insights from vast datasets.

Professional profile:

Early Academic Pursuits:

Raj Kumar Singh began his academic journey with a Master of Science (M.Sc.) in Remote Sensing and GIS from Jiwaji University, Gwalior, India, in 2009. His thesis focused on hyperspectral remote sensing-based studies for the extraction of vegetation quality parameters using Hyperion data. This laid the foundation for his future specialization in geoinformatics.

He continued his education with a Master of Technology (M.Tech.) in Remote Sensing and GIS with a specialization in Atmospheric Science from the Indian Institute of Remote Sensing (IIRS-ISRO), Dehradun, India, in 2015. His thesis, titled "Spatial-temporal variability of Aerosol Optical properties and their impact on Aerosol Radiative forcing over Indo-Gangetic plain," showcased his commitment to understanding atmospheric dynamics through remote sensing.

Raj Kumar Singh completed his academic journey with a Doctor of Philosophy (Ph.D.) in Geoinformatics and Agroforestry from the Indian Institute of Technology Kharagpur (IIT-KGP) in 2023. His doctoral thesis, "Agroforestry Interventions for Improved Crop Management Using Geospatial Technology," demonstrated his expertise in applying geospatial techniques to agriculture.

Professional Endeavors:

Raj Kumar Singh has accumulated 14 years of professional experience, primarily focusing on satellite remote sensing and its applications in agriculture and agroforestry. He has worked with various national and international organizations, including ISRO, JNU, ICARDA, and currently leads geospatial activities at World Agroforestry (CIFOR-ICRAF) in New Delhi.

His roles include being a Geoinformatics Scientist at World Agroforestry, ICARF, where he leads and plans geoinformatics activities, contributes to technical exchanges, project reports, and proposals, and develops advanced remote sensing and geoinformatics applications for agroforestry. He has also led the development of a mobile app for site-specific agroforestry suitability.

Raj Kumar Singh served as a Remote Sensing Specialist at the International Centre for Agricultural Research in the Dry Areas (ICARDA) in New Delhi, where he characterized rice fallows, assessed long-term trends of crop fallows, and developed pulse crop suitability maps using advanced decision-making techniques.

He has also worked as a Research Fellow at Jawaharlal Nehru University (JNU) in New Delhi, focusing on geomorphological and geological mapping, and as a Junior Research Fellow at the Regional Remote Sensing Centre (RRSC)-East, Indian Space Research Organization (ISRO), Kolkata, where he mapped tea growing areas and conducted detailed site suitability analysis for tea plantations.

Additionally, Raj Kumar Singh served as a GIS Engineer at Magus Infocom Pvt. Ltd. in Noida, Delhi-NCR, contributing to spatial database creation for urban infrastructure using satellite and ground-based data.

Contributions and Research Focus:

Raj Kumar Singh's research encompasses biomass estimation, species distribution, and ecological modeling using geospatial data analytics, machine learning, and image processing software. He has hands-on experience with hyperspectral and SAR data, leading teams in the development of tools and applications for agroforestry suitability and carbon estimation.

His expertise extends to cloud-based platforms such as Google Earth Engine (GEE) and programming languages like Python and R. He has actively contributed to the development of geospatial decision layers, mobile applications, and dashboards for real-time monitoring and analysis.

Raj Kumar Singh has been actively involved in projects with organizations like USAID, NRSC, ISRO, ICAR, Tea Board, and Survey of India, showcasing his versatility in addressing diverse geospatial challenges.

Accolades and Recognition:

Raj Kumar Singh has received recognition for his work through memberships in professional bodies such as the Indian Society of Remote Sensing (ISRS) and the Indian Society of Agroforestry. He serves as a reviewer for reputable journals in the field, including the Journal of Environment and Management, Environmental Monitoring and Assessment, Remote Sensing, and Tropical Ecology.

His commitment to advancing knowledge is evident through his participation in numerous professional training programs, including those focused on Google Earth Engine, Web GIS Technology, Earth Observation for Carbon Cycle Studies, and Machine Learning.

Impact and Influence:

Raj Kumar Singh's work has had a significant impact on the field of geoinformatics, particularly in the application of remote sensing to agriculture and agroforestry. His research outputs, including over 15 peer-reviewed publications and presentations at national and international conferences, contribute to the body of knowledge in the domain.

As a leader at World Agroforestry, he has influenced the development of innovative tools, platforms, and applications for site-specific agroforestry interventions and biomass estimation. His work on mobile apps and decision support tools has facilitated practical applications of geospatial technology in the field.

Legacy and Future Contributions:

Raj Kumar Singh's legacy lies in his comprehensive contributions to the integration of geoinformatics into agricultural and agroforestry practices. His focus on sustainable solutions, capacity building through training, and active participation in collaborative projects positions him as a thought leader in the geospatial community.

Looking forward, Raj Kumar Singh is likely to continue shaping the future of geoinformatics by leveraging emerging technologies, such as machine learning and cloud-based platforms. His commitment to research, training, and the practical application of geospatial solutions ensures a lasting impact on the field.

Notable publication:

Decentralized proximal gradient algorithms with linear convergence rates

A linearly convergent proximal gradient algorithm for decentralized optimization

Linear convergence of primal–dual gradient methods and their performance in distributed optimization

On the influence of bias-correction on distributed stochastic optimization

Distributed coupled multiagent stochastic optimization

A proximal diffusion strategy for multiagent optimization with sparse affine constraints

A unified and refined convergence analysis for non-convex decentralized learning

Removing data heterogeneity influence enhances network topology dependence of decentralized sgd

Citation:

A total of 447  citations for his publications, demonstrating the impact and recognition of his research within the academic community.

Citations              447

h-index  10           10

i10-index             10