Raeesa Manjoo-Docrat | Infectious Diseases | Young Researcher Award

Published on by Global Diseases Research

Dr. Raeesa Manjoo-Docrat | Infectious Diseases | Young Researcher Award 

Lecturer | Univeristy of the Witwatersrand | South Africa

Dr. Raeesa Manjoo-Docrat is a developing scholar affiliated with the University of the Witwatersrand, Johannesburg, whose work contributes to the advancement of quantitative epidemiology and public health modelling in South Africa. Her research focuses on the development and application of spatial, age-stratified epidemiological models aimed at understanding disease transmission dynamics within heterogeneous populations. With four peer-reviewed publications and 27 citations, she has established a growing academic footprint supported by an h-index of 2, reflecting the early but significant influence of her work. Her recent open-access article in Heliyon (2025), which applies spatial modelling frameworks to the South African COVID-19 pandemic, exemplifies her commitment to integrating mathematical rigor with real-world public health challenges. Manjoo-Docrat has collaborated with multidisciplinary teams comprising epidemiologists, mathematicians, and public health scientists, enabling her to contribute to robust analytical frameworks and high-quality scientific outputs. These collaborations also highlight her ability to operate effectively within diverse research environments and to engage in evidence-based problem solving that supports both academic and policy-relevant outcomes. Her research sits at the intersection of infectious disease dynamics, health systems planning, and data-driven decision support, positioning her work within a globally relevant domain of applied epidemiology. Beyond academic metrics, her contributions have societal impact by informing approaches to epidemic preparedne  ss, guiding interventions for vulnerable demographic groups, and enhancing understanding of spatial disparities in health outcomes. Through her continued scholarship, Manjoo-Docrat aims to strengthen the integration of mathematical modelling into national and regional public health strategies, ensuring that data-informed insights contribute to improved health resilience and equitable disease control.

Profiles: Scopus | ORCID

Featured Publications

1. Manjoo-Docrat, R., Abdelatif, N., Holloway, J., Dudeni-Tlhone, N., Dresselhaus, C., Mbayise, E., … Makhanya, S. (2025). Spatial age-stratified epidemiological model with applications to South African COVID-19 pandemic. Heliyon, 11(11), e43171. https://doi.org/10.1016/j.heliyon.2025.e43171

2. Dresselhaus, C., Fabris-Rotelli, I., Manjoo-Docrat, R., Brettenny, W., Holloway, J., Thiede, R., Debba, P., & Dudeni-Tlhone, N. (2023). A spatial model with vaccinations for COVID-19 in South Africa. Spatial Statistics, 58, Article 100792. Cited by 2.

3. Manjoo-Docrat, R. (2022). A spatio-stochastic model for the spread of infectious diseases. Journal of Theoretical Biology, 533, 110943.  Cited by 16.

4. Fabris-Rotelli, I., Holloway, J., Kimmie, Z., Archibald, S., Debba, P., Manjoo-Docrat, R., … Potgieter, A. (2022). A Spatial SEIR Model for COVID-19 in South Africa. Journal of Data Science, Statistics, and Visualisation, 2(7), 14–45.  Cited by 5.

Shiping Zhu | Medicine | Best Innovation Award

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Dr. Shiping Zhu | Medicine | Best Innovation Award 

Associate Chief Physician | The First Affiliated Hospital of Jinan University | China

Dr. Shiping Zhu is a highly accomplished materials scientist and polymer engineer whose influential research has significantly advanced the fields of smart materials, ionogels, elastomers, and membrane technologies. Affiliated with The Chinese University of Hong Kong, Shenzhen, he has built an extensive academic record, authoring more than 450 peer-reviewed publications and accumulating over 20,000 citations, reflecting his global impact and sustained scholarly contribution. His work consistently bridges fundamental chemistry with practical engineering, focusing on high-performance polymers, CO₂ capture materials, mechanoresponsive elastomers, and advanced adhesive systems. Recent publications highlight breakthroughs in armored polymer-fluid gels, fracture-resistant stretchable materials, high-loading MOF monoliths for gas separation, and ultra-strong ionogel adhesives—showcasing his leadership in designing materials with exceptional mechanical, environmental, and functional performance. Prof. Zhu’s research group actively collaborates with multidisciplinary teams worldwide, contributing to approximately 400 co-authored studies and driving innovations across chemical engineering, materials science, environmental technology, and energy applications. With an h-index of 76, his scholarly influence spans both theoretical and applied domains, shaping industrial practices in polymer manufacturing, smart adhesive development, impact-resistant materials, and sustainable separation technologies. His work on CO₂ capture frameworks and advanced reactor engineering supports global efforts toward carbon neutrality, while his innovations in adaptable and energy-dissipating elastomers have relevance in robotics, wearable electronics, and safety engineering. Prof. Zhu is also recognized for pioneering structural methodologies in ionogel design, mechanochromic materials, and touch-responsive polymer networks that enable next-generation sensing, damping, and protective systems. Through his sustained research excellence, extensive collaborations, and high-impact publications, Prof. Shiping Zhu continues to advance the scientific foundations and practical applications of modern polymer science, contributing meaningfully to technological progress and societal benefit.

Profiles: Scopus | Google Scholar | ORCID

Featured Publications

1. Qian, Y., Qiu, X., & Zhu, S. (2015). Lignin: A nature-inspired sun blocker for broad-spectrum sunscreens. Green Chemistry, 17(1), 320–324. Cited by: 541

2. Zhu, H., Yang, X., Cranston, E., & Zhu, S. (2016). Flexible and porous nanocellulose aerogels with high loadings of metal-organic framework particles for separations applications. Green Chemistry, —. Cited by: 474

3. Feng, W., Zhu, S., Ishihara, K., & Brash, J. L. (2005). Adsorption of fibrinogen and lysozyme on silicon grafted with poly(2-methacryloyloxyethyl phosphorylcholine) via surface-initiated atom transfer radical polymerization. Langmuir, 21(13), 5980–5987. Cited by: 447

4. Pan, H., Li, Y., Wu, Y., Liu, P., Ong, B. S., Zhu, S., & Xu, G. (2007). Low-temperature, solution-processed, high-mobility polymer semiconductors for thin-film transistors. Journal of the American Chemical Society, 129(14), 4112–4113. Cited by: 441

5. Feng, W., Brash, J. L., & Zhu, S. (2006). Non-biofouling materials prepared by atom transfer radical polymerization grafting of 2-methacryloyloxyethyl phosphorylcholine: Separate effects of graft density and chain length. Biomaterials, 27(6), 847–855. Cited by: 400

Dr. Shiping Zhu’s pioneering contributions to advanced polymers, ionogels, and functional materials are transforming next-generation manufacturing, environmental sustainability, and high-performance industrial applications. His work bridges fundamental polymer science with real-world impact, enabling safer, smarter, and more resilient materials for global technological advancement.

Amos Kipkorir Langat | Infectious Disease | Best Researcher Award

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Assist. Prof. Dr. Amos Kipkorir Langat | Infectious Disease | Best Researcher Award 

Senior Research Fellow | Jomo Kenyatta University of Agriculture and Techno | Kenya

Dr. Amos Kipkorir Langat, Ph.D., is a highly accomplished statistician, academic, and economist with expertise in Bayesian analysis, machine learning, spatial statistics, and public health modeling. He earned his Ph.D. in Mathematics (Statistics) from the Pan African University Institute for Basic Sciences, Technology and Innovation, his MSc. in Applied Statistics from Jomo Kenyatta University of Agriculture and Technology (JKUAT), and his BSc. in Economics and Mathematics from Kabarak University. Currently, he serves as a Lecturer at JKUAT and Senior Economist at the County Government of Bomet, with previous teaching roles at Maasai Mara and Kabarak Universities. His research spans statistical modeling of infectious diseases, HIV risk factors, maternal health, survival and time series analysis, and measurement error models. He has supervised MSc. and Ph.D. students across Africa, authored over 30 peer-reviewed publications, and contributed to journals such as Scientific African, Asian Journal of Probability and Statistics, and Annals of Medicine & Surgery. Dr. Langat has secured prestigious awards including the AU Ph.D. Scholarship and SICSS research funding, and he actively contributes as a reviewer and conference organizer. His technical expertise includes proficiency in R, Python, STATA, SAS, SPSS, WinBUGS/OpenBUGS, and advanced econometric tools. A member of the Royal Statistical Society, ISCB, IBS, and the Kenya National Statistical Society, he also demonstrates a strong commitment to community service through educational leadership roles. Dr. Langat exemplifies a dedicated scholar, mentor, and researcher advancing applied statistics in public health and beyond

Profile: Google Scholar | Scopus | Orcid

Featured Publications

1. Langat, A., Orwa, G., & Koima, J. (2017). Cancer cases in Kenya; forecasting incidents using Box & Jenkins ARIMA model. Biomedical Statistics and Informatics, 2(2), 37–48. Cited by: 21

2. Benki-Nugent, S. F., Martopullo, I., Laboso, T., Tamasha, N., Wamalwa, D. C., … [and others]. (2019). High plasma soluble CD163 during infancy is a marker for neurocognitive outcomes in early-treated HIV-infected children. JAIDS Journal of Acquired Immune Deficiency Syndromes, 81(1), 102–109. Cited by: 14

3. Mutinda, J. K., & Langat, A. K. (2024). Stock price prediction using combined GARCH-AI models. Scientific African, 26, e02374. Cited by: 10

4. Mutinda, J. K., & Langat, A. K. (2024). Modeling the impact of air pollution and meteorological variables on COVID-19 transmission in Western Cape, South Africa. International Journal of Mathematics and Mathematical Sciences, 2024(1), 1591016. Cited by: 5

5. Mutinda, J. K., & Langat, A. K. (2024). Capital asset pricing model: A renewed application on S&P 500 index. Asian Journal of Economics, Business and Accounting, 24(6), 226–239. Cited by: 4