Sundas Rafat Mulkana
Papers
1
Total Citations
2
H-Index
1
About
Sundas Rafat Mulkana is a leading voice in the field of safe human-robot collaboration, with a primary focus on developing trustworthy autonomous systems. Her research centers on the intersection of reinforcement learning (RL) and collaborative robotics, specifically addressing the critical challenge of ensuring safety in dynamic, human-filled environments. In her seminal 2024 work, "Safe Reinforcement Learning for Collaborative Robots in Dynamic Human Environments," Mulkana tackles the fundamental unpredictability of autonomous robots in real-world settings—a key barrier to their widespread adoption. By integrating safety constraints directly into the RL training process, she proposes frameworks that allow robots to learn complex tasks while proactively mitigating risks of injury to human coworkers. This contribution is vital for advancing Industry 5.0, where humans and robots work side-by-side. While her most-cited paper has garnered 2 citations, its recent publication signals a rapidly growing influence, and her work is already shaping discussions on safety-critical AI. Mulkana’s research is not only technically rigorous but also deeply human-centered, aiming to unlock the full potential of collaborative robotics without compromising human well-being.
Research Focus
Key Achievements
Top Papers
- 1