Christopher Teti
Papers
1
Total Citations
5
H-Index
1
About
Christopher Teti is a researcher focused on the intersection of artificial intelligence, autonomous systems, and behavioral cloning. His work examines how deep neural networks replicate human driving behaviors in autonomous steering tasks, with a particular emphasis on safety and reliability. Teti’s most-cited paper, “A controlled investigation of behaviorally-cloned deep neural network behaviors in an autonomous steering task” (2021), has garnered 5 citations and provides critical insights into the limitations and vulnerabilities of imitation learning in self-driving vehicles. By systematically analyzing how cloned networks deviate from intended behaviors, Teti contributes to the development of more robust and interpretable AI systems. His research is foundational for understanding the risks of over-reliance on behavioral cloning in real-world autonomous navigation. Teti’s work is especially relevant for students and engineers seeking to bridge the gap between machine learning theory and practical deployment in safety-critical domains.
Research Focus
Key Achievements
Top Papers
- 1