Sina Radmard
University of British Columbia, JDSU (Canada), Monash University
Papers
11
Total Citations
94
H-Index
6
About
Sina Radmard’s research lies at the intersection of robotics, computer vision, and human-robot interaction, with a focus on enabling robots to operate effectively in dynamic, unstructured environments. His major contributions center on active visual target search and occlusion resolution for high-dimensional robotic systems, developing algorithms that allow robots to “look behind” occluders and reacquire lost targets in real time using particle filters and approximate Bayesian filtering. This work, published in venues like ICRA and IROS, has been cited over 90 times, with his most influential papers addressing active search in high-dimensional systems (17 citations) and interface design for telepresence robots (16 citations). Radmard has also advanced robot learning from demonstration, using polynomial optimization for motion planning in visual servoing. More recently, he has applied his expertise to socially impactful domains, developing VR simulators and digital twins for service robots in long-term care facilities, particularly during COVID-19. His notable achievements include pioneering methods for resolving visual occlusions in eye-in-hand systems and designing user interfaces that simplify telepresence robot control, making him a key figure in bridging theoretical robotics with real-world assistive technologies.
Research Focus
Key Achievements
Top Papers
- 1Active target search for high dimensional robotic systems17 citations · 2015
- 2Interface design and usability analysis for a robotic telepresence platform16 citations · 2015
- 3Optimized vision-based robot motion planning from multiple demonstrations13 citations · 2017
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- 7Approximate Recursive Bayesian Filtering methods for robot visual search4 citations · 2011
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- 10Overcoming unknown occlusions in eye-in-hand visual search3 citations · 2013