Research Interests

  • Broad Research Areas: Reconfigurable computing, Neuromorphic computing, Hardware-software codesign, Microarchitecture, and Compiler

Internet of things is a great vision where everything embeds a tiny computer so that we can listen to them and even talk to them if they have the capacity to understand and act on our words. Undoubtedly there are many challenges to this, but a crucial one is how to make things very energy-efficient and error-tolerant. In the Reconfigurable and Neuromorphic Computing Lab (RNCL) at UNIST we are deeply interested in this question of how to make things efficient and resilient, and are exploring solutions across different boundaries (eg., hardware vs software, digital vs analog vs stochastic) encompassing multiple levels of abstraction from application specification to circuit-level design. We push the limit of energy-efficient computing by designing innovative processor architectures and compilers optimized for today's and tomorrow's emerging applications (e.g., computer vision, recognition, synthesis) with a special focus on parallelism, heterogeneity, reconfigurability, and energy-accuracy trade-off.

Research Topics

  • Reconfigurable architectures and application mapping

  • Multi- and many-core architectures, and accelerators (e.g., general-purpose graphics processing units and reconfigurable processors)

  • Application- and domain-specific processors, and compilers

  • Neuromorphic computing and processors for deep learning


  • IEEE - Institute of Electrical and Electronics Engineers

  • ACM - Association for Computing Machinery


Jongeun Lee at Pisa, Italy