Research

Research themes of the Computer Architecture Research Group

We pursue the realization of "embodied computational intelligence" by integrating three axes: LSI design, robotics, and computing. Our research spans the full stack — from circuits and learning algorithms to real-world robots.

AI for Circuits

Automating IC Design with LLMs

Conventional IC design has required expert designers to spend enormous time writing HDL code and running verification. Our lab introduces Large Language Models (LLMs) into the circuit design process, building a new EDA flow that automates everything from natural-language specification to Verilog code generation and layout design (GDSII generation).

  • Generative AI for EDA
  • LLM
  • Auto Synthesis
AI for Circuits
Circuits for AI

Circuits for AI

High-Efficiency Edge AI Accelerators

As AI models (Transformers, diffusion models) grow in size, general-purpose CPUs/GPUs become bottlenecks in terms of power consumption and throughput. We research domain-specific architectures that execute specific AI algorithms with maximum efficiency — designing optimal PE placement and dataflow control at the silicon level to enable real-time AI inference on edge devices.

  • Domain-Specific Architecture
  • FPGA/ASIC
  • Low-Power VLSI

Systems & Robotics

Robotic Applications of Custom Chips

We deploy AI chips and circuit design methodologies developed in the lab onto real intelligent robots. By running LLM-based imitation learning and complex trajectory generation algorithms in real time on custom hardware (FPGAs / in-house ICs), we build vertically integrated robotic systems where software and hardware are tightly coupled — driving computing research that connects theory to the real world.

  • Imitation Learning
  • Autonomous Robot Control
  • Hardware-in-the-Loop
Systems & Robotics