Zhihua Xiao

Ph.D. student in Electronic and Computer Engineering, HKUST

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Lab page: SQML

Research Center: ACCESS

Mail: zxiaoam@connect.ust.hk

Google Scholar: ehEym28AAAAJ

I’m a Ph.D. candidate in Electronics and Computer Engineering at The Hong Kong University of Science and Technology. Working in the Spintronic Qquantum Materials Laboritory (SQML), Under the supervision of Prof. Qiming SHAO. Meanwhile, I’m also working at AI Chip Center for Emerging Smart Systems (ACCESS). My research primarily focuses on the frontier of hardware-software co-design schemes for in-memory computing using emerging non-volatile technologies.

Current research interests

  • Software-hardware codesign
    Aimed to implement novel algorithms or accelerate existing algorithms using emerging devices.
  • Unified neuromorphic in-memory computing
    Combining the advantages of artificial neural networks and spiking neural networks by designing unified neuromorphic in-memory computing hardware.
  • Computer architecture and device modeling
    Benchmarking the performance of novel architectures and devices requires assistance from reliable modeling of the system and the devices.

For a deeper insight into my research, please refer to my Google Scholar.

If you wish to discuss with me, feel free to contact me via email.

selected publications

  1. Device Variation-Aware Adaptive Quantization for MRAM-based Accurate In-Memory Computing Without On-chip Training
    Zhihua Xiao, Vinayak Bharat Naik , Shun Kong Cheung , Jia Hao Lim , Jae-Hyun Kwon , Zheyu Ren , Zhongrui Wang , and Qiming Shao
    In 2022 International Electron Devices Meeting (IEDM) , 2022
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    3 Google Scholar citations
  2. MTI.png
    Cryogenic in-memory computing using tunable chiral edge states
    Yuting Liu , Albert Lee , Kun Qian , Peng Zhang , Haoran He , Zheyu Ren , Shun Kong Cheung , Yaoyin Li , Xu Zhang , Zichao Ma , and  others
    arXiv preprint arXiv:2209.09443, 2022
    arXiv
    3 Google Scholar citations
  3. BNN.png
    Energy-efficient machine learning accelerator for binary neural networks
    Wei Mao , Zhihua Xiao, Peng Xu , Hongwei Ren , Dingbang Liu , Shirui Zhao , Fengwei An , and Hao Yu
    In Proceedings of the 2020 on Great Lakes Symposium on VLSI , 2020
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    12 Google Scholar citations
  4. A multi-class objects detection coprocessor with dual feature space and weighted softmax
    Zhihua Xiao, Peng Xu , Xianglong Wang , Lei Chen , and Fengwei An
    IEEE Transactions on Circuits and Systems II: Express Briefs, 2020
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    11 Google Scholar citations