Emerging Computing Lab
Welcome to Emerging Computing Lab
At Emerging Computing Lab, we explore the forefront of digital computation, specializing in cutting-edge digital neuromorphic processor design and digital deep learning accelerator design.
Our research bridges the gap between biological inspiration and advanced engineering, crafting processors that emulate the efficiency and adaptability of the human brain. By developing innovative architectures and algorithms, we aim to revolutionize real-time processing and energy efficiency for next-generation applications.
In the realm of deep learning accelerators, we focus on optimizing performance, scalability, and power consumption to meet the demands of modern AI workloads. From compact, high-speed designs for edge devices to robust solutions for data centers, our work pushes the boundaries of what's possible in artificial intelligence hardware.
Join us as we shape the future of intelligent systems and redefine the limits of digital processing
Recruiting!
We have open positions for postdocs who are experts in event-data processing algorithms.
PhD., MS., and Undergraduate Research positions available (Department of Semiconductor Engineering or Materials Science and Engineering). If you are interested in our lab, please feel free to contact Prof. Jeong (dooseokj at hanyang.ac.kr).
이벤트 데이터 처리 알고리즘을 전공한 박사후과정 연구원을 모집합니다. 관심있는 해당전공 연구자는 CV를 동봉한 이메일을 보내주시기 바랍니다.
디지털 딥러닝 연산가속기 설계를 전공할 AI반도체대학원 박사/석사과정학생을 모집합니다. 연구계획을 동봉한 이메일을 보내주시기 바랍니다.
News
[24/11/19] Changmin's paper "IterNorm: Fast Iterative Normalization" got accepted as a regular paper in DATE 2025.
[24/2/21] DongHyung's new paper "Theoretical understanding of gradients of spike functions as boolean
functions" just appeared in Complex & Intelligent Systems.
[24/8/22] DongHyung received his PhD today. Congrats!
Recent publications
Theoretical understanding of gradients of spike functions as boolean functions, DongHyung Yoo, Doo Seok Jeong*, Complex & Intelligent Systems 2024 [paper][code].
Experimental Deonstration of combination-encoding content-addressable memory of 0.75 bits/switch utilizing Hf-Zr-O ferroelectric tunnel junctions, Manh-Cuong Nguyen, Jiwon You, Yonguk Sim, Rino Choi, Doo Seok Jeong*, Daewoong Kwon*, Materials Horizons 2024 [paper].
Optimal data distribution in FeFET-based computing-in-memory macros, Yonguk Sim, Choongseok Song, Eun Chan Park, Jongwook Jeon, Daewoong Kwon, Doo Seok Jeong, ISCAS 2024 [paper].
Hardware for deep learning acceleration, Choongseok Song, Changmin Ye, Yonguk Sim, Doo Seok Jeong*, Advanced Intelligent Systems 2024, 2300762.[paper]
Purely self-rectifying memristor-based passive crossbar array for artificial neural network accelerators, Kanghyeok Jeon, Jin Joo Ryu, Seongil Im, Hyun Kyu Seo, Taeyong Eom, Hyunsu Ju*, Min Kyu Yang*, Doo Seok Jeong*, Gun Hwan Kim*, Nature Communications 2024, 15, 129.[paper]