Pavel Zun
Papers
1
Total Citations
7
H-Index
1
About
Pavel Zun is an emerging researcher at the intersection of food safety, environmental science, and artificial intelligence. His primary research focuses on microplastic contamination in food systems, where he investigates both the sources of contamination and the most effective methods for detection. Zun’s most-cited work, a 2025 review titled “Microplastic contamination and detection in food systems: a review of machine learning, traditional methods, and other relevant factors,” has already garnered 7 citations, signaling its timely relevance. In this paper, he provides a comprehensive synthesis of conventional detection techniques—such as spectroscopy and microscopy—alongside cutting-edge machine learning approaches, offering a roadmap for more accurate, scalable monitoring. By bridging the gap between traditional analytical chemistry and modern computational tools, Zun’s contribution helps researchers and regulators understand how AI can enhance the speed and precision of microplastic identification in complex food matrices. His work is particularly notable for its interdisciplinary scope, addressing a growing public health concern while highlighting the potential of data-driven solutions. As microplastic pollution continues to attract global attention, Zun’s research positions him as a key voice in developing smarter, more efficient detection strategies for safer food systems.
Research Focus
Key Achievements
Top Papers
- 1