Welcome to IPE Lab
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Innovating at the Intersection of Light, Intelligence, and Computation
Welcome to the Intelligent Photonics & Electronics Laboratory (IPEL), where we develop ultrafast, energy-efficient, and adaptive electronic-photonic systems for next-generation computing and sensing. Our research integrates optoelectronics, neuromorphic architectures, and advanced materials to enable real-time, in-sensor processing, beyond-charge-based memory, and AI-driven photonic computing. By leveraging high-speed event photodetectors, phase-transition dynamics, and novel device architectures, we aim to bridge the gap between optical sensing, intelligent computation, and next-generation AI hardware.
Join us in shaping the future of intelligent photonic systems!
Fully funded positions are available for passionate students interested in cutting-edge research.
The IPE Lab is co-operated alongside the AEEM Lab (Prof. Hyungtak Seo’s group: aeem.ajou.ac.kr), effectively expanding research capabilities in materials, devices, and systems while strengthening support and resources.
Open projects for students
1. 3D Neurophototonic Systems:
This project focuses on the monolithic integration of photodetectors and neuromorphic processing units, enabling direct, in-material optical computing. By combining photonics and neuromorphic electronics, we aim to develop ultrafast, energy-efficient, and adaptive computing architectures for next-generation AI, vision systems, and intelligent edge computing. The research will explore novel material platforms, device architectures, and advanced fabrication techniques to achieve seamless light-driven processing at the hardware level, eliminating the need for separate sensor and processor units.
Key Goals:
Develop a fully integrated 3D neuromorphic photonic system.
Investigate new approaches for in-sensor computing using direct optical inputs.
Achieve real-time, energy-efficient information processing without external computation overhead.
Explore applications in bio-inspired vision systems, event-driven computing, and high-speed AI hardware.
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2. Trackless Memory: Beyond Ion Migration & Charge Trapping
This project aims to redefine memory technology by developing a new class of non-volatile memory that does not rely on ion migration or charge trapping mechanisms. Conventional memory technologies, such as resistive switching (RRAM), flash memory, and ferroelectric memory, rely on physical relocation of ions or charge storage, leading to issues like device degradation, reliability concerns, and scaling limitations.
We seek alternative physical mechanisms for data storage and processing, exploring novel material systems and device architectures that enable stable, high-speed, and energy-efficient memory operation without traditional constraints.
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Key Goals:
Identify and develop a fundamentally new memory mechanism.
Explore material systems beyond conventional oxides and ferroelectrics.
Achieve high-speed, energy-efficient, and highly scalable memory solutions.
Investigate applications in neuromorphic computing, logic-in-memory processing, and future AI hardware.