Silvina Fadda | Environment | Best Researcher Award

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Dr. Silvina Fadda | Environment | Best Researcher Award

Dr. Silvina Fadda | Environment | Senior Researcher at CERELA | Argentina

Dr. Silvina Fadda is a highly accomplished female scientist specializing in food microbiology and biochemistry, currently serving as a Research Scientist at CERELA under the National Scientific and Technical Research Council (CONICET) in Argentina. Dr. Silvina Fadda earned her Doctorate in Biochemistry from the Universidad Nacional de Tucumán, where she developed extensive expertise in microbial physiology, fermentation systems, and the characterization of lactic acid bacteria relevant to food safety and preservation. Throughout her professional career, she has focused on studying beneficial and bioprotective microorganisms, particularly lactic acid bacteria and their metabolic, proteomic, and adaptive responses under food processing conditions. Her research interests include microbial ecology in meat processing environments, the antagonistic activity of probiotic strains against foodborne pathogens, and molecular techniques for assessing microbial adaptation and stress tolerance. Dr. Silvina Fadda possesses strong research skills in proteomics, molecular microbiology, bacterial strain characterization, fermentation technology, and the development of microbial-based food safety strategies. She has collaborated on internationally coordinated research projects aimed at improving safe food production practices and developing sustainable microbial biopreservation methods. Her scholarly contributions are reflected in her publications in high-impact, Scopus-indexed journals and her continued role as a reviewer for reputable journals in food chemistry, food microbiology, and biofilm research. Dr. Silvina Fadda has received recognition for her scientific contributions through her longstanding research appointment at CONICET, along with participation in scientific committees and professional networks that advance food microbiology research. Her work demonstrates leadership in laboratory-based research, interdisciplinary collaboration, and mentoring early career researchers. In conclusion, Dr. Silvina Fadda exemplifies professional excellence, scientific rigor, and an ongoing commitment to improving global food safety through microbiological innovation, making her a commendable academic and a strong contributor to both scientific research and community knowledge.

Academic Profile: ORCID | Scopus

Featured Publications:

  1. Cisneros, L., Baillo, A. A., Ploper, D., Valacco, M. P., Moreno, S., Yantorno, O., Fusco, V., & Fadda, S. (2025). Foodborne lactic acid bacteria inactivate planktonic and sessile Escherichia coli O157:H7 in a meat processing environment: A physiological and proteomic study. Foods. Citations: 5

  2. Terán, L. C., Orihuel, A., Bentencourt, E., Raya, R., & Fadda, S. (2023). Role of curing agents in the adaptive response of the bioprotective Latilactobacillus curvatus CRL 705 from a physiologic and proteomic perspective. Bacteria. Citations: 12

  3. Sandoval-Mosqueda, I. L., Llorente-Bousquets, A., Soto, C., Mercado Márquez, C., Fadda, S., & Del Río García, J. C. (2023). Ligilactobacillus murinus strains isolated from mice intestinal tract: Molecular characterization and antagonistic activity against food-borne pathogens. Microorganisms. Citations: 18

  4. Terán, L. C., Orihuel, A., Bentencourt, E., Raya, R., & Fadda, S. (2023). Role of curing agents in the adaptive response of the bioprotective Latilactobacillus Curvatus CRL 705 from a physiologic and proteomic perspective (Preprint). Citations: 3

 

 

Bo Zhang | Environmental Science | Best Research Article Award

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Mr. Bo Zhang | Environmental Science | Best Research Article Award

Mr. Bo Zhang | Environmental Science | Associate Professor at Northwestern Polytechnical University | China

Mr. Bo Zhang is an accomplished researcher whose career reflects a distinguished trajectory in the fields of remote sensing, geoinformation science, and artificial intelligence applications for environmental monitoring, and he has consistently demonstrated excellence through impactful research contributions and global collaborations. Educated with a doctoral degree in Remote Sensing from a leading academic institution, Mr. Bo Zhang has established a solid academic foundation that underpins his expertise in applying advanced computational methods to real-world environmental challenges. His professional experience includes multiple collaborative projects with internationally recognized scholars from institutions such as Tsinghua University, Southeast University, Technical University of Munich, University of Hong Kong, and others, through which he has advanced the use of deep learning techniques, satellite image downscaling, and GIS-based data integration for earth observation and climate-related studies. Mr. Bo Zhang’s research interests lie primarily in satellite remote sensing, super-resolution reconstruction of geospatial datasets, atmospheric and environmental data analysis, epidemiological mapping, and the integration of machine learning for improved predictive accuracy in public health and ecological monitoring, reflecting an interdisciplinary approach that combines computing, earth science, and applied technology. His research skills span deep learning model development, neural network applications for image processing, spatial epidemiology analysis, super-resolution algorithms, and the integration of volunteered geographic information into traditional mapping platforms, enabling him to contribute both theoretically and practically to geospatial sciences.

Academic Profile: ORCID | Scopus | Google Scholar

Featured Publications:

  • Zhu, B., Liu, J., Fu, Y., Zhang, B., & Mao, Y. (2018). Spatio-temporal epidemiology of viral hepatitis in China (2003–2015): Implications for prevention and control policies. International Journal of Environmental Research and Public Health, 15(4), 661. Citations: 73.

  • Pan, D., Zhang, M., & Zhang, B. (2021). A generic FCN-based approach for the road-network extraction from VHR remote sensing images—Using OpenStreetMap as benchmarks. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. Citations: 59.

  • Zhang, B., Zhang, M., Kang, J., Hong, D., Xu, J., & Zhu, X. (2019). Estimation of PMx concentrations from Landsat 8 OLI images based on a multilayer perceptron neural network. Remote Sensing, 11(6), 646. Citations: 29.

  • Zhang, B., Xiong, W., Ma, M., Wang, M., Wang, D., Huang, X., Yu, L., Zhang, Q., … (2022). Super-resolution reconstruction of a 3 arc-second global DEM dataset. Science Bulletin, 67(24), 2526–2530. Citations: 25.