Sandra Sarrazin | Petroleum Engineering | Best Researcher Award

Published on by Petroleum Engineering

Prof. Dr. Sandra Sarrazin | Petroleum Engineering | Best Researcher Award

Professor at Universidade Federal do Oeste do Pará | Brazil

Prof. Dr. Sandra Layse Ferreira Sarrazin is a distinguished Brazilian biologist and pharmacologist whose scientific career reflects a profound dedication to research in therapeutic innovation, natural product bioprospecting, and public health within the Amazon region. As a researcher and professor at the Federal University of Western Pará, she has led and collaborated on numerous interdisciplinary projects exploring the pharmacological potential of Amazonian biodiversity, with an emphasis on essential oils, phytopharmaceuticals, and antioxidant compounds derived from native plants. Her studies have significantly advanced understanding of toxicogenomic and antimutagenic mechanisms related to environmental exposure, particularly mercury contamination in vulnerable populations such as pregnant women and indigenous communities. Through leadership in projects like the Rede Bionorte and initiatives focused on biotechnology and environmental health, Prof. Dr. Sandra Sarrazin has contributed to integrating research, education, and extension activities that bridge traditional knowledge with modern pharmacological science. Her prolific academic output includes influential publications in internationally recognized journals such as Journal of Ethnopharmacology, Food Chemistry, and Environmental Science & Technology, with citations reflecting her impact in ethnopharmacology and environmental toxicology. Honored for her work on the antimicrobial and antioxidant properties of Amazonian plant species, she continues to mentor emerging scientists and promote sustainable development through science-based health innovations. Prof. Dr. Sandra Sarrazin career embodies a commitment to preserving Amazonian biodiversity while transforming its resources into solutions that enhance health and well-being, reinforcing her status as a leading figure in biopharmaceutical research and an advocate for integrating biotechnology into regional and global health strategies.

Profile: Scopus

Featured Publications

Massing, L. T., Mourão, R. H. V., Sarrazin, S. L. F., Suemitsu, C., Figueiredo, P. L. B., Fernandes, C. P., Maia, J., & Guilherme, S. (2025). Citral chemotype of Pectis elongata essential oil: Nanoemulsification and enhanced antimicrobial properties for food safety.

Silva, D. M. da, Silva, L. A. da, Silva, M. D. da, Pinto, M. E. de O., Lima, V. A. de, Sarrazin, S. L. F., Silva, W. T. P. da, & Oliveira, R. B. de. (2025). Efeitos da suplementação nutricional com substâncias antioxidantes em gestantes expostas ao mercúrio na Amazônia Legal.

Amorin, A. P., Sarrazin, S. L. F., da Silva, L. A., Coelho, T. N., Cunha, A. P., de Lima, V. A., da Silva, D. M., Figueiredo, P. L. B., & de Oliveira, R. B. (2025). Opioid and nitrergic pathways mediate antinociception by Kunth essential oil

Pires, P. G. da S., Sarrazin, S. L. F., Souza, D. J. dos A., Mourão, R. H. V., Massing, L. T., Nunes, H. A. S., Barroso, A. S., & de Oliveira, R. B. (2024). Antiedema and antinociceptive potential of the essential oil of Pectis elongata Kunt (Asteraceae) from the Brazilian Amazon.

Macambira, D. V. de C., Almeida Júnior, J. S. de, Silveira, C. F. de M., Sarrazin, S. L. F., Moraes, T. M. P., da Silva, B. A., Minervino, A. H. H., Moraes, W. P., & Barata, L. E. S. (2024). Antimicrobial activity on Streptococcus mutans and Enterococcus faecalis of Cyperus articulatus ethanolic extracts.

Wente Niu | Petroleum Engineering | Best Researcher Award

Published on by Petroleum Engineering

Dr. Wente Niu | Petroleum Engineering | Best Researcher Award

Lecturer at Yanshan University | China

Dr. Wente Niu is a dedicated academic and researcher serving as a Lecturer at Yanshan University, with a strong foundation in petroleum engineering and artificial intelligence applications. He earned his PhD from the Institute of Porous Flow and Fluid Mechanics at the Chinese Academy of Sciences, where his research explored advanced computational approaches for unconventional oil and gas development. With extensive contributions in AI-driven reservoir modeling, production forecasting, and digital twin technologies, he has positioned himself as an innovator bridging energy engineering with computer science. His expertise has directly contributed to improved reservoir characterization and efficient energy resource utilization.

Profile

Orcid

Education

Dr. Wente Niu completed his PhD at the Institute of Porous Flow and Fluid Mechanics, Chinese Academy of Sciences, specializing in fluid mechanics and subsurface flow. His academic path combined petroleum engineering fundamentals with cutting-edge computational science, enabling him to pioneer machine learning applications in reservoir engineering. His doctoral research focused on the development of AI-based models for unconventional oil and gas, providing a strong technical and theoretical background for future innovations. This foundation prepared him to explore cross-disciplinary research and teaching, while also strengthening collaborations with leading petroleum universities and industry research centers across China.

Experience

Dr. Wente Niu has significant academic and professional experience in petroleum engineering research and teaching. At Yanshan University, he lectures and supervises research integrating artificial intelligence with energy resource engineering. He has successfully completed eight research projects, including two at the national level, and currently leads projects on AI-driven reservoir simulations and digital twin development. He has collaborated with PetroChina and the China National Petroleum Corporation on industry-focused projects that apply AI to shale gas development. His experience spans reservoir characterization, machine learning frameworks, and consultancy, demonstrating his ability to link academic innovation with industrial problem-solving.

Research Interest

Dr. Wente Niu research lies at the intersection of geoscience, engineering, and computer science, with a focus on artificial intelligence applications in unconventional energy resource development. His primary interests include machine learning for subsurface characterization, production forecasting, and optimization in shale gas and tight oil reservoirs. He also explores digital core analysis and digital twin technologies to enhance reservoir simulation accuracy and efficiency. A core aspect of his work involves explainable AI frameworks that increase transparency in predictive modeling. His research advances data-driven methods that improve decision-making, accelerate computations, and promote sustainable resource recovery in petroleum engineering.

Award

Dr. Wente Niu is nominated for the Best Researcher Award in recognition of his outstanding contributions to petroleum engineering research and the integration of artificial intelligence into reservoir engineering. His work has not only advanced academic knowledge but also delivered measurable benefits to the energy industry, particularly in collaboration with CNPC and PetroChina. His achievements demonstrate international recognition. His innovations in explainable AI, digital twin technology, and production optimization highlight his exceptional capability as a researcher and his potential to drive transformative progress in petroleum engineering.

Publication

Dr. Wente Niu has published widely in SCI/SCIE-indexed journals.

Title: Unsupervised Learning-Driven Insights into Shale Gas Reservoirs: Production Prediction and Strategic Applications
Year: 2025

Conclusion

Dr. Wente Niu exemplifies the qualities of an innovative and impactful petroleum engineering researcher. His interdisciplinary expertise bridges artificial intelligence, geoscience, and engineering, creating significant advancements in unconventional resource development. His contributions are recognized through impactful publications, patents, and collaborations with leading energy corporations. His ability to translate theoretical models into practical industry applications underscores his strength as a transformative scholar. With a proven record of research, teaching, and innovation, he stands as a strong candidate for the Best Researcher Award, capable of shaping the future of petroleum engineering through cutting-edge AI-driven approaches.