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Hun-Seok Kim
Hun-Seok KimAssistant ProfessorElectrical Engineering and Computer Science
(734) 764-7630 2417G EECS1301 Beal AvenueAnn Arbor, MI 48109-2122


Research Interests

  • Theory, System, Algorithm and Hardware Architecture for Digital Communication, Deep Learning, Signal Processing, and Embedded Systems
  • IoT; 5G MIMO-OFDM; High performance wireless communication systems; Ultra-low power wireless communication systems; Ultra-reliable low latency communication;
  • Software-Defined Radio; Deep Neural Networks, Computer Vision; Image/audio Processing; Software-Defined Network;
  • Integrated Circuits and VLSI architecture for Ultra-Low Power / Ultra High Performance Systems

Research Grants & Awards

  • Principal Investigator, Ford, “Device Authentication Using the Unique Characteristics of the Transmitted Signal”
  • Co-Principal  Investigator, NSF, “IIBR Multidisciplinary: mSAIL (Michigan Small Animal Integrated Logger): a milligram-scale, multi-modal sensor and analytics monitoring platform”
  • Co-Principal  Investigator, Arm, “Context-Aware Multi-Sensor Fusion System and SoC”
  • Principal  Investigator, Samsung, “Machine Learning Algorithms and Architectures for Autonomous Robotics Sensor Fusion”
  • Co-Principal  Investigator, Sony Electronics, “Ultra Low Power intelligent imaging sensors for the Internet of Things”
  • Co-Principal  Investigator, Facebook, “Context-Aware Multi-Sensor Fusion System and SoC”
  • Co-Principal  Investigator, National Geographic Society, “M3 Monarch Migration Study”
  • Co-Principal  Investigator, NSF, “Elucidating the relationship between motor cortex neural firing rates and dextrous finger movement EMG for use in brain-computer interfaces”
  • Principal  Investigator, DARPA Young Faculty Award (YFA) 2018, “Hyper-Dimensional Modulation for Robust Low-Latency Low-Power IoT Networks”
  • Co-Principal Investigator, DARPA – Electronics Resurgence Initiative – DSSoC, “Domain-Focused Advanced Software-Reconfigurable Heterogeneous System on Chip (DASH-SoC)”
  • Co-Principal Investigator, DARPA – Electronics Resurgence Initiative – SDH, “Transmuter: A Reconfigurable Computer”
  • Co-Principal Investigator, NIH BRAIN R21, “100μm Scale Single Unit Neural Recording Probe Using IR-Based Powering and Communication”
  • Co-Principal Investigator, University of Michigan Exercise & Sport Science Initiative (ESSI), “Projection Based Augmented Reality System for Inclusive Recreational Sports and Performance Tracking”
  • Co-Principal Investigator, Army Research Office, “Intelligent collaborative wireless networks enabled by heterogeneous software-defined radios”
  • Principal Investigator, NIST Public Safety Innovation Accelerator Research , “Decimeter Accurate, Long Range Non-Line-of-Sight RF Localization Solution for Public Safety Applications”
  • Principal Investigator, Samsung Global Research Outreach, “Machine Learning Algorithms and Architectures for Autonomous Robotics Sensor Fusion”
  • Principal Investigator, Samsung Global Research Outreach, “Energy-Optimized Wireless Communication for Power-Constrained Millimeter-Scale IoT Platforms”
  • Principal Investigator, Samsung Global Research Outreach, “An ultra-low power, 360-degrees immersive image processor for energy-constrained mobile platforms”
  • Co-Principal Investigator, National Science Foundation ECCS #1507192, “Back-Channel Communication Embedded in Standard Compliant Wireless Packets”.
  • Co-Principal Investigator, DARPA BAA-15-14, “Near Zero-Power, Continuous Acoustic Sensing Microsystem using Active Integrated Circuits and Digital Signal Processing”.
  • Co-Principal Investigator, Intel, “Ultra-Low Power Versatile Wireless Communication Solutions for IoT”.

On-Going Projects

OFDM-guided Deep Joint Source ChannelCoding for Wireless Multipath Fading Channels

HTNN: Deep Learning in Heterogeneous TransformDomains with Sparse-Orthogonal Weights

Signal Processing and Wireless Communication via Machine Learning and Deep Neural Networks

Ultra-low power WiFi / Bluetooth Low Energy (BLE) back-channel communication systems


Ultra low-power, non-line-of-sight RF localization for energy-autonomous wireless sensor nodes


Low-power computer vision and machine learning hardware accelerators for mobile platforms


Ultra-low power near-field / far-field wireless communication for millimeter-scale sensor nodes


Low power, software defined radio architecture for IoT communications


Ultra-low power machine learning deep neural network systems for event detection and classification