
Rachel Cheng
استادیار · Food Microbiology
Virginia Polytechnic Institute and State Universityمعرفی
Rachel Cheng is an Assistant Professor in the Department of Food Science and Technology at Virginia Tech, Blacksburg, VA, where she has conducted research on foodborne pathogens since 2022. Her work bridges fundamental microbiology and practical food safety applications to reduce disease burden.
Education:
- Ph.D. in Food Science, Cornell University (2017)
- B.S. in Food Science, Oregon State University (2012)
- B.S. in Microbiology, Oregon State University (2012)
Research Focus: Dr. Cheng's laboratory investigates Food Microbiology with emphasis on Bacterial Pathogenesis and Food Safety. Key research pillars include toxin-mediated virulence mechanisms, host-pathogen genomic adaptations, and commodity-specific intervention strategies targeting Salmonella and Bacillus cereus. Her team leverages genomic, transcriptomic, and phenotypic approaches to identify pathogen vulnerabilities.
Publication Trends: Analysis of her 15 most recent publications (2022-2025) reveals dominant themes in Salmonella genomics (65%), Bacillus cereus taxonomy (25%), and cross-cutting methodologies like prophage analysis and fimbrial evolution. Her work increasingly integrates epidemiological data with molecular characterization to inform precision food safety interventions.
Scientific Awards: No awards listed in provided materials.
Advising & Funding: Actively recruiting graduate/undergraduate researchers through structured mentorship programs. Her lab's operational funding derives from institutional support and competitive grants targeting food safety innovation, though specific awards aren't detailed. Current projects focus on pathogen genomic surveillance and intervention validation.
Lab Operations: The Cheng Micro Lab maintains a vision of 'A safer food supply for all' through hypothesis-driven research on virulence factors and host adaptation. The team follows strict diversity and inclusion principles while executing genomic sequencing, phenotypic characterization, and intervention testing across multiple food matrices.
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