Papers
3
Total Citations
63
H-Index
3
About
Deepak Kumar Sharma is a researcher at the forefront of human-computer interaction and artificial intelligence, with a focus on bridging the gap between humans and autonomous systems. His work centers on gesture recognition, multimodal action understanding, and knowledge graph construction, particularly for low-resource languages. Sharma’s most cited paper, “Hand Gesture Recognition for Human Computer Interaction and Its Applications in Virtual Reality” (2019, 31 citations), introduces novel methods for intuitive control in virtual environments, enabling more natural user interfaces. Building on this, his 2022 study on “Ambient intelligence-based multimodal human action recognition for autonomous systems” (27 citations) advances the ability of robots and smart environments to interpret complex human behaviors through multiple sensory inputs. More recently, Sharma has tackled the challenge of knowledge representation in underserved languages with his 2023 work “HKG: A Novel Approach for Low Resource Indic Languages to Automatic Knowledge Graph Construction” (5 citations), proposing a semantic network framework to enhance question answering and recommendation systems. His contributions are vital for developing more intelligent, responsive technologies that can operate seamlessly in diverse linguistic and interactional contexts, making him a key figure in ambient intelligence and inclusive AI.
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