Aniruddha Sinha

Papers

Total Citations

138

H-Index

About

Aniruddha Sinha’s research lies at the intersection of computer vision, human-computer interaction, and healthcare technology, with a particular focus on leveraging artificial intelligence and machine learning for practical, real-world applications. His early, highly influential work on person identification using skeleton data from the Microsoft Kinect sensor (95 citations) pioneered a non-intrusive, vision-based method for recognizing individuals by analyzing gait patterns, significantly advancing the field of human-robot interaction and biometrics. This foundational contribution demonstrated how low-cost depth sensors could be used for robust, privacy-preserving identification in dynamic environments. More recently, Sinha has turned his expertise toward the medical domain, co-authoring a seminal review on the disruptive potential of AI and machine learning in orthopaedics (43 citations). This work critically examines how intelligent systems can transform surgical planning, diagnostics, and patient outcomes, establishing him as a key voice in the integration of computational methods into clinical practice. His research consistently bridges the gap between algorithmic innovation and societal impact, making him a notable figure in both computer science and translational medicine.