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researcher

Shiqi Zhao

4 papers hereh-index 9347 citations27 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author3

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • eess.SP3
  • cs.NE1
same name
  • Shiqi Zhao — 10 papers, h 9
  • Shiqi Zhao — 2 papers, h 1
  • Shiqi Zhao — 2 papers
  • Shiqi Zhao — 1 paper
  • Shiqi Zhao — 1 paper, h 1
  • Shiqi Zhao — 1 paper, h 3

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20212025
most citedAn End-to-End Deep Learning Approach for Epileptic Seizure Prediction

84 citations · 123 across the 3 of their papers we have counts for

collaborators

4 papers

eess.SP2025

Neuro-MoBRE: Exploring Multi-subject Multi-task Intracranial Decoding via Explicit Heterogeneity Resolving

Di Wu, Yifei Jia, Siyuan Li +3

Neurophysiological decoding, fundamental to advancing brain-computer interface (BCI) technologies, has significantly benefited from recent advances in deep learning. However, exist…

eess.SP2022★ 39 cited

Binary Single-dimensional Convolutional Neural Network for Seizure Prediction

Shiqi Zhao, Jie Yang, Yankun Xu +1

Nowadays, several deep learning methods are proposed to tackle the challenge of epileptic seizure prediction. However, these methods still cannot be implemented as part of implanta…

eess.SP2021★ 84 cited

An End-to-End Deep Learning Approach for Epileptic Seizure Prediction

Yankun Xu, Jie Yang, Shiqi Zhao +2

An accurate seizure prediction system enables early warnings before seizure onset of epileptic patients. It is extremely important for drug-refractory patients. Conventional seizur…

cs.NE2021

A New Neuromorphic Computing Approach for Epileptic Seizure Prediction

Fengshi Tian, Jie Yang, Shiqi Zhao +1

Several high specificity and sensitivity seizure prediction methods with convolutional neural networks (CNNs) are reported. However, CNNs are computationally expensive and power hu…

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