Mohit Kumar Ahuja
Papers
1
Total Citations
9
H-Index
1
About
Mohit Kumar Ahuja is an emerging researcher specializing in deep learning model testing and validation, with a particular focus on vision-based systems and their applications in safety-critical domains. His most notable work, "Testing Deep Learning Models: A First Comparative Study of Multiple Testing Techniques" (2022), represents a significant contribution to the field of AI quality assurance, systematically evaluating and comparing methodologies for testing deep learning systems deployed in high-stakes environments such as autonomous driving, robotic surgery, critical infrastructure surveillance, and air and maritime traffic control. Ahuja's research addresses a pressing challenge in modern AI development — ensuring the reliability and robustness of deep learning models before they are trusted in life-critical scenarios. By conducting one of the first comprehensive comparative analyses of multiple testing techniques, he has helped establish a foundational framework for researchers and practitioners seeking to validate complex AI systems that process images, video, audio, and other intricate signal types. With 9 citations since publication, his work is gaining traction within the software engineering and machine learning communities, positioning him as a promising voice in the intersection of AI testing, safety verification, and computer vision research.
Research Focus
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Top Papers
- 1