World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
37
Citations
5174
World Ranking
10852
National Ranking
4517

Overview

Yiyu Shi is affiliated with the University of Notre Dame in the United States. Their research spans multiple interdisciplinary fields, primarily situated in computer science, medicine, and engineering. This cross-disciplinary approach is reflected in the range of topics and publication venues associated with their work.

The main fields of study covered by Yiyu Shi's publications include:

  • Computer Science
  • Medicine
  • Engineering

Within these fields, they have contributed extensively to several subfields such as:

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering
  • Radiology, Nuclear Medicine and Imaging
  • Biomedical Engineering

The research topics frequently addressed by Yiyu Shi further illustrate their expertise in both computational and medical domains. These include:

  • Advanced Neural Network Applications
  • Advanced Memory and Neural Computing
  • Ferroelectric and Negative Capacitance Devices
  • Quantum Computing Algorithms and Architecture
  • Domain Adaptation and Few-Shot Learning
  • Radiomics and Machine Learning in Medical Imaging
  • Medical Image Segmentation Techniques

Their recent papers demonstrate a focus on hardware-software integration, neural architectures, and medical image analysis. Selected publications include:

  • "Hardware/Software Co-Exploration of Neural Architectures" (2020) in IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
  • "Device-Circuit-Architecture Co-Exploration for Computing-in-Memory Neural Accelerators" (2020) in IEEE Transactions on Computers
  • "Standing on the Shoulders of Giants: Hardware and Neural Architecture Co-Search With Hot Start" (2020) in IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
  • "ImageCAS: A large-scale dataset and benchmark for coronary artery segmentation based on computed tomography angiography images" (2023) in Computerized Medical Imaging and Graphics
  • "The importance of resource awareness in artificial intelligence for healthcare" (2023) in Nature Machine Intelligence

Yiyu Shi has collaborated extensively with several other researchers, reflecting sustained partnerships in their field of work. Frequent co-authors include:

  • Jingtong Hu
  • Xiaowei Xu
  • Dewen Zeng
  • Weiwen Jiang
  • Meiping Huang

Their work has appeared prominently in venues including:

  • arXiv (Cornell University)
  • IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
  • Medical Image Analysis
  • Nature Machine Intelligence
  • 2021 IEEE/ACM International Conference On Computer Aided Design (ICCAD)

Best Publications

  • Scaling for edge inference of deep neural networks

    Xiaowei Xu;Yukun Ding;Sharon Xiaobo Hu;Michael Niemier

  • Hardware/Software Co-Exploration of Neural Architectures

    Weiwen Jiang;Lei Yang;Edwin Hsing-Mean Sha;Qingfeng Zhuge

  • Accuracy vs. Efficiency: Achieving Both through FPGA-Implementation Aware Neural Architecture Search

    Weiwen Jiang;Xinyi Zhang;Edwin H.-M. Sha;Lei Yang

  • Co-Exploration of Neural Architectures and Heterogeneous ASIC Accelerator Designs Targeting Multiple Tasks

    Lei Yang;Zheyu Yan;Meng Li;Hyoukjun Kwon

  • Quantization of Fully Convolutional Networks for Accurate Biomedical Image Segmentation

    Xiaowei Xu;Qing Lu;Lin Yang;Sharon Hu

  • Semi-supervised Contrastive Learning for Label-Efficient Medical Image Segmentation.

    Xinrong Hu;Dewen Zeng;Xiaowei Xu;Yiyu Shi

  • Thermal via allocation for 3D ICs considering temporally and spatially variant thermal power

    Hao Yu;Yiyu Shi;Lei He;Tanay Karnik

  • On Neural Architecture Search for Resource-Constrained Hardware Platforms.

    Qing Lu;Weiwen Jiang;Xiaowei Xu;Yiyu Shi

  • Device-Circuit-Architecture Co-Exploration for Computing-in-Memory Neural Accelerators

    Weiwen Jiang;Qiuwen Lou;Zheyu Yan;Lei Yang

  • Thermal-aware cell and through-silicon-via co-placement for 3D ICs

    Jason Cong;Guojie Luo;Yiyu Shi

  • Standing on the Shoulders of Giants: Hardware and Neural Architecture Co-Search With Hot Start

    Weiwen Jiang;Lei Yang;Sakyasingha Dasgupta;Jingtong Hu

  • ImageCAS: A large-scale dataset and benchmark for coronary artery segmentation based on computed tomography angiography images

    Unknown

  • Positional Contrastive Learning for Volumetric Medical Image Segmentation

    Dewen Zeng;Yawen Wu;Xinrong Hu;Xiaowei Xu

  • A universal state-of-charge algorithm for batteries

    Bingjun Xiao;Yiyu Shi;Lei He

  • DAC-SDC Low Power Object Detection Challenge for UAV Applications

    Xiaowei Xu;Xinyi Zhang;Bei Yu;Xiaobo Sharon Hu

  • On the Efficacy of Through-Silicon-Via Inductors

    Umamaheswara Rao Tida;Rongbo Yang;Cheng Zhuo;Yiyu Shi

  • An Analytical Placement Framework for 3-D ICs and Its Extension on Thermal Awareness

    Guojie Luo;Yiyu Shi;J. Cong

  • Whole Heart and Great Vessel Segmentation in Congenital Heart Disease Using Deep Neural Networks and Graph Matching

    Xiaowei Xu;Tianchen Wang;Yiyu Shi;Haiyun Yuan

  • Distributed contrastive learning for medical image segmentation

    Unknown

  • Demand-Side Management of Domestic Electric Water Heaters Using Approximate Dynamic Programming

    Khalid Al-jabery;Zhezhao Xu;Wenjian Yu;Donald C. Wunsch

  • When Single Event Upset Meets Deep Neural Networks: Observations, Explorations, and Remedies

    Zheyu Yan;Yiyu Shi;Wang Liao;Masanori Hashimoto

  • Measurement and Evaluation of Power Analysis Attacks on Asynchronous S-Box

    Jun Wu;Yiyu Shi;Minsu Choi

  • From Layout to System: Early Stage Power Delivery and Architecture Co-Exploration

    Cheng Zhuo;Kassan Unda;Yiyu Shi;Wei-Kai Shih

  • Real-Time Adversarial Attacks

    Yuan Gong;Boyang Li;Christian Poellabauer;Yiyu Shi

  • Achieving Super-Linear Speedup across Multi-FPGA for Real-Time DNN Inference

    Weiwen Jiang;Edwin H.-M. Sha;Xinyi Zhang;Lei Yang

  • Federated Contrastive Learning for Volumetric Medical Image Segmentation.

    Yawen Wu;Dewen Zeng;Zhepeng Wang;Yiyu Shi

  • DAC-SDC Low Power Object Detection Challenge for UAV Applications

    Xiaowei Xu;Xinyi Zhang;Bei Yu;X. Sharon Hu

Frequent Co-Authors

Jinjun Xiong
Jinjun Xiong University at Buffalo, State University of New York
Jingtong Hu
Jingtong Hu University of Pittsburgh
Lei He
Lei He University of California, Los Angeles
Tsung-Yi Ho
Tsung-Yi Ho Chinese University of Hong Kong
Xiaobo Sharon Hu
Xiaobo Sharon Hu University of Notre Dame
Ulf Schlichtmann
Ulf Schlichtmann Technical University of Munich
Meng Jiang
Meng Jiang University of Notre Dame
Vladimir Zolotov
Vladimir Zolotov IBM (United States)
Edwin H.-M. Sha
Edwin H.-M. Sha East China Normal University
Sung Kyu Lim
Sung Kyu Lim Georgia Institute of Technology

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