Dongsuk Lim
Papers
1
Total Citations
9
H-Index
1
About
Dongsuk Lim is a researcher at the forefront of embedded and cyber-physical systems, with a primary focus on enabling high-performance deep neural network (DNN) execution on resource-constrained edge devices and collaborative robots. His most cited work, "Characterizing the Execution of Deep Neural Networks on Collaborative Robots and Edge Devices" (2019, 9 citations), tackles a critical bottleneck in modern robotics and IoT: the challenge of running computationally intensive DNNs on platforms with limited processing power and energy budgets. By systematically analyzing performance trade-offs, Lim provides foundational insights into how DNNs can be effectively deployed for real-time perception and decision-making at the edge, rather than relying solely on cloud computing. This contribution is vital for advancing autonomous systems, from industrial cobots to smart sensors. His research bridges the gap between algorithmic complexity and hardware constraints, offering practical pathways for more intelligent, responsive, and autonomous edge devices. Lim’s work is essential reading for students and engineers seeking to understand the practical deployment of AI in the physical world.
Research Focus
Key Achievements
Top Papers
- 1