Papers
2
Total Citations
14
H-Index
2
About
Piotr Koniusz is a leading researcher at the intersection of computer vision, machine learning, and graph neural networks (GNNs). His work spans visual categorization, representation learning, and the novel application of AI to environmental science. Koniusz is perhaps best known for pioneering the use of GNNs in ecotoxicology with his highly cited 2024 study, "GRAPE." This work introduced a groundbreaking approach to integrate aquatic toxicity data, offering a powerful, data-driven alternative to traditional in vivo testing for assessing chemical threats to species and ecosystems—a contribution that has already garnered 12 citations and signals a major shift toward computational methods in environmental risk assessment. Earlier, his foundational research on "Novel Image Representations For Visual Categorisation With Bag-of-Words" advanced the core techniques for object and scene recognition, impacting fields from security to media retrieval. With a career defined by bridging theoretical innovation and pressing real-world problems, Koniusz continues to shape how machines see and understand our world, from the pixels in an image to the health of our planet.
Research Focus
Key Achievements
Top Papers
- 1Graph neural networks-enhanced relation prediction for ecotoxicology (GRAPE)12 citations · 2024
- 2Novel Image Representations For Visual Categorisation With Bag-of-Words.2 citations · 2013