Chirag Raman
Papers
2
Total Citations
18
H-Index
2
About
Chirag Raman’s research lies at the intersection of machine learning, surgical data science, and human-robot interaction, with a focus on modeling and measuring human behavior in complex, real-world settings. In his most cited work, a 2025 systematic review, he investigates machine learning applications using non-optical motion tracking in surgery, analyzing over 3,600 records to map objectives, experimental designs, and model effectiveness—a foundational contribution that has already garnered 14 citations. Complementing this, his 2021 study on real-time perception of anthropomorphism in human-robot interaction explores how prosodic cues can help robots adapt to human engagement and emotions, advancing long-term conversational AI. Together, these works demonstrate Raman’s ability to bridge technical rigor with practical impact, addressing critical challenges in surgical motion analysis and socially aware robotics. His research not only synthesizes a rapidly evolving field but also proposes novel measurement frameworks, making him a rising voice in applied machine learning for healthcare and interaction design.
Research Focus
Key Achievements
Top Papers
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