Kanishk Barhanpurkar
Papers
3
Total Citations
104
H-Index
3
About
Kanishk Barhanpurkar is a researcher at the forefront of applying computational intelligence to critical societal and industrial challenges. His work spans three key areas: cybersecurity for the Industrial Internet of Things (IIoT), AI-driven mental health diagnostics, and intelligent automation for manufacturing. In his highly cited 2021 study on the Dark Web Network, Barhanpurkar pioneered a computational intelligence framework for vulnerability analysis in IIoT platforms, earning 43 citations for addressing a pressing cybersecurity gap. He also made a significant contribution to geriatric healthcare by developing an AI robotic system that leverages the Nelder–Mead optimization method for depression detection in elderly people—a paper cited 34 times for its novel integration of robotics and machine learning. Additionally, his research on robotic process automation (27 citations) demonstrates how AI and ML can simultaneously boost productivity and product quality in industrial settings. Barhanpurkar’s work is notable for its practical, cross-domain impact, bridging theoretical algorithms with real-world applications in security, healthcare, and manufacturing.
Research Focus
Key Achievements
Top Papers
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