Research Directions

The Neuromorphic Device Lab studies device concepts that connect semiconductor materials, memory physics, sensing, and energy-efficient computing. Our work emphasizes experimentally grounded device characterization and application-aware neuromorphic functions.

Retinomorphic device concept

Retinomorphic Vision Sensors

We develop bio-inspired optoelectronic devices and sensor concepts for dynamic machine vision, visual memory, and energy-efficient front-end processing.

Related work: Nano Research 2025; Advanced Intelligent Systems 2021; Advanced Intelligent Systems 2020.

Memory device characterization

CBRAM and RRAM Devices

We investigate conductive-bridge and resistive switching devices for high-density memory, selectors, synaptic functions, and in-processor integration.

Related work: ACS Applied Electronic Materials 2024; Applied Physics Letters 2023; IEEE Electron Device Letters 2023.

Neuromorphic device illustration

Neuromorphic Memory Devices

We study memory and transistor structures that emulate synaptic and neuronal behavior, including plasticity, leaky integration, and device-level learning functions.

Related work: Nanoscale Horizons 2023; IEEE Electron Device Letters 2022; ACS Applied Materials & Interfaces 2020.

NTU EEE

High-k Reliability And Trap Dynamics

We characterize charge trapping, gate dielectric reliability, hot-carrier effects, and nanoscale variability in advanced transistor and memory devices.

Related work: IEEE Transactions on Electron Devices; IEEE Electron Device Letters; Journal of Applied Physics.

Methods And Capabilities

  • Electrical characterization of memory, selector, and transistor devices
  • Reliability testing and trap dynamics analysis
  • Device physics interpretation for neuromorphic and sensing functions
  • Collaboration with industrial and academic partners on emerging semiconductor devices

See Publications for the full publication list, People for current members, and Join Us for student and collaboration opportunities.