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I am Co-Founder and CTO of LuxiTech , focusing on building brain-inspired large language models. These models are specifically designed to operate with high cognitive capabilities while consuming significantly less power compared to traditional LLMs.

I received the Ph.D degree from the Department of Electrical and Computer Engineering (ECE), University of California, Santa Cruz (UCSC). My research is co-supervised by Prof. Sung-Mo “Steve” Kang at Nanoelectronic Integrated Systems Laboratory and Prof. Jason Eshraghian at Neuromorphic Computing Group, and focuses on neuromorphic computing, spiking neural networks, and their hardware implementation using memristors.

I received my bachelor’s degree from the Experimental Class of Qiming College, a special college for the cultivation of top innovative students at Huazhong University of Science and Technology (HUST). Meanwhile, the degree is also awarded by the School of Artificial Intelligence and Automation (AIA) at HUST.

I also obtained working experience from Synsense, a neuromorphic startup that spun out of the Institute of Neuroinformatics at the University of Zurich and ETH Zurich; and Tetramem, a computing-in-memory startup whose RRAM technologies are based on Yang research group at USC, Nanodevices and Integrated Systems Laboratory at UMass Amherst, and HP labs.

I am passionate about a multidisciplinary approach to the future, including electrical and computer engineering, cognitive science, neuroscience, philosophy, etc. I am also a fan of basketball, skateboarding, snowboarding, ukulele, cats, Chinese calligraphy, and meditation. Feel free to reach out to me!

News

• [Jun. 13, 2024] My interview with STEM4ALL, supported by the United Nations Development Programme (UNDP) and the United Nations International Children’s Emergency Fund (UNICEF), is now available online!
• [Jun. 04, 2024] Paper “Scalable MatMul-free Language Modeling” is available in arXiv.
• [Apr. 08, 2024] Paper “Eagle and Finch: RWKV with matrix-valued states and dynamic recurrence” is available in arXiv.
• [Nov. 24, 2023] Paper “Neuromorphic intermediate representation: a unified instruction set for interoperable brain-inspired computing” is available in arXiv.
• [Oct. 13, 2023] Peng was invited to attend the United Nations event “The 2023 Policy Dialogue on Women in Science: Pathways towards Breaking Barriers in STEM”.
• [Oct. 08, 2023] Paper “RWKV: Reinventing RNNs for the Transformer Era” is accepted by 2023 EMNLP Findings!
• [May. 22, 2023] Paper “RWKV: Reinventing RNNs for the Transformer Era” is available in arXiv.
• [May. 22, 2023] Peng presented the paper “Backpropagating Errors Through Memristive Spiking Neural Networks” at the 2023 IEEE International Symposium on Circuits & Systems (IEEE ISCAS), Monterey, CA.
• [April. 29, 2023] The paper titled “How to Build a Memristive Integrate-and-Fire Neuron for Spiking Neuronal Signal Generation” has been awarded the 2023 IEEE Transaction on Circuits and Systems Darlington Best Paper Award. This paper was led by Prof. Sung-Mo Kang, Prof. Jason Eshraghian, and Prof. Leon O. Chua in a collaboration spanning UC Santa Cruz, UC Berkeley, University of Michigan, TU Dresden, and Syungkyunkwan University.
• [Feb. 22, 2023] 2023 Telluride Workshop on Neuromorphic Cognition Engineering has been announced. Jason and I will be hosting one of the topic areas: Open-source neuromorphic hardware, software, and wetware.
• [Nov. 14, 2022] Paper “Gradient-based Neuromorphic Learning on Dynamical RRAM Arrays” is accepted by IEEE Journal on Emerging and Selected Topics in Circuits and Systems (IEEE JETCAS). It is a JETCAS special issue on Memristive Circuits and Systems for Edge-Computing Applications.
• [Sep. 13, 2022] Peng submitted a Spiking Neural Network Accelerator to tape-out in eFabless / Google SkyWater MPW7 shuttle.
• [Aug. 30, 2022] Congratulations to Prof. Jason Eshraghian for joining the ECE department as a new assistant professor. He leads the Neuromorphic Computing Group and co-advise Peng.
• [Jul. 15, 2022] Peng was awarded “Best New Neuromorph” during the 2022 Telluride Workshop. 
• [Jun. 23, 2022] Peng gave a talk at the Computer Science Department of Santa Clara University invited by Prof. Nam Ling and Prof. Tokunbo Ogunfunmi.
• [May. 31, 2022] Peng presented the paper “A Fully Memristive Spiking Neural Network with Unsupervised Learning” at the 2022 IEEE International Symposium on Circuits & Systems (IEEE ISCAS), Austin, TX.
• [Apr. 25, 2022] Peng has been selected to participate in the 2022 Telluride Workshop on Neuromorphic Cognition Engineering, which is the most famous neuromorphic workshop with a long history since the “neuromorphic” area originated.
• [Mar. 29, 2022] Peng has been selected as a 2022 Science Internship Program research mentor.
• [Feb. 25, 2022] Patent “Splitting normalization method and device, audio feature extractor and chip” has been published.
• [Jan. 14, 2022] Paper “A Fully Memristive Spiking Neural Network with Unsupervised Learning” has been accepted at the 2022 IEEE International Symposium on Circuits & Systems (IEEE ISCAS).
• [Jan. 07, 2022] Patent “Pulse event decision device, method, chip and electronic equipment” has been published.
• [Nov. 18, 2021] Paper “How to Build a Memristive Integrate-and-Fire Model for Spiking Neuronal Signal Generation” has been published in: IEEE Transactions on Circuits and Systems–I: Regular Papers. We are honored to have these international cooperations among Germany, Korea, the University of Michigan, UCB, and UCSC.
• [Oct. 23, 2021] Peng gave a talk on “Memristive Spiking Neural Network for Neuromorphic Computing” at the Integrated Circuit School, Huazhong University of Science and Technology.
• [May. 14, 2021] We received the Faculty Research Grant for “Bio-Inspired Memristive Spiking Neural Network for Machine Learning” research from the Committee on Research of the University of California, Santa Cruz.
• [Mar 30, 2021] Peng has been selected as a 2021 Science Internship Program research mentor.
• [Dec. 29, 2020] Paper “Automatically detecting bregma and lambda points in rodent skull anatomy images” has been published in: PloS one.
• [Sep. 14, 2020] Peng received the 2020 IEEE Nuclear Science Symposium and Medical Imaging Conference trainee grant.
• [Jul. 29, 2020] Paper “Towards Real-Time Machine Learning for Anomaly Detection” has been accepted at the 2020 IEEE Nuclear Science Symposium and Medical Imaging Conference (IEEE NSS/MIC).
• [Mar. 16, 2019] Peng was accepted and graduated from the Graduate Student Leadership Certificate Program of the University of California, Santa Cruz.