ArtIC and its predecessor laboratory have published research achievements at leading conferences in the fields of machine learning, architecture, reconfigurable hardware, and integrated circuits, and have received funding from industry-academia collaborations and large-scale research projects.
Research Experience
Research areas cover deep neural network accelerators, ensemble learning accelerators, image-based object recognition, FPGA-based deep neural networks, and hardware-aware algorithms for neural networks.
Background
Research interests include exploring AI computing architectures; specializes in information processing architecture for the post-Neumann and post-Moore eras.
Miscellany
ArtIC provides an excellent research environment for students and researchers, encouraging those interested in AI information processing to join.