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TIEQIAO'S HOMEPAGE

Biography

Tieqiao is a second-year Ph.D. student at Oregon State University advised by Prof. Sinisa Todorovic. His interests are in video understanding and representation learning.

From 2020 to 2021, he did an automatic driving internship in the Volkswagen Group during his remote studies. Before that, he received his Bachelor’s degree from an innovative class at University of Jinan in 2020, working under Dr. Sijie Niu’s advice.

Interests

  • Video Understanding
  • Representation Learning

Education

  • Ph.D. in Computer Science, Expected 2025

    Oregon State University

  • BSc in Computer Science, 2020

    University of Jinan

Publication

Weakly-supervised retinal detachment segmentation using deep feature propagation learning in SD-OCT images

In this paper, we propose a weakly supervised learning method for the quantitative analysis of lesion regions in spectral domain optical coherence tomography (SD-OCT) images. The experimental results demonstrate that the proposed method can achieve encouraging segmentation accuracy comparable to strong supervision methods only utilizing image-level labels.
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Quantitative Estimation of Rainfall Rate Intensity Based on Deep Convolutional Neural Network and Radar Reflectivity Factor

We propose a method based on the deep convolutional neural network model VGG and radar reflectivity factor to quantitatively estimation the rainfall rate intensity, which eclipses the performance of the traditional method Z-R relationship.
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