Biao Zhang

Biao Zhang

PhD candidate

KAUST

Biography

Biao Zhang is a PhD candidate in Computer Science department at KAUST. He is broadly interested in machine learning, deep learning and 3d vision. His current research interests include point cloud analysis and 3d shape analysis with deep networks. He is advised by Prof. Peter Wonka.

Interests
  • Artificial Intelligence
  • Machine Learning
  • Deep Learning
  • 3D Vision
Education
  • PhD in Computer Science, 2018-

    King Abdullah University of Science and Technology

  • Visiting student, 2017-2018

    King Abdullah University of Science and Technology

  • Visiting student, 2014-2015

    University of Wisconsin-Madison

  • MSc in Mathematics, 2011-2014

    Xian Jiaotong University

  • BSc in Mathematics, 2007-2011

    Xian Jiaotong University

Accomplish­ments

Teaching Assistant of CS323 Deep Learning for Visual Computing
The course provides an introduction to deep learning and specifically to deep learning for visual computing. Example topics that will be discussed are: simple fully connected neural networks, image classification, convolutional neural networks, backpropagation, activation functions, data normalization, data augmentation, normalization layers, training dynamics, network architectures, style transfer, segmentation, object detection, regression, optimization, autoencoder, generative adversarial networks, networks for point cloud processing, clustering, recursive neural networks, graphconvolutional neural networks, adversarial attacks. The course starts at a very basic level. However, previous skills especially programming in Python, Machine Learning, Linear Algebra, Probability, and multi-variate Calculus will be required. Students are expected to learn these skills quickly if they did not have sufficient exposure to them. The evaluation will heavily rely on projects. Therefore programming skills are the most important.
Teaching Assistant of CS390DD Special Topics in Machine Learning
This course provides an overview of deep learning applications in visual computing. We will cover some basics of deep learning (optimization, network architecture, compression, …) as well as selected applications (image recognition, segmentation, image synthesis, object detection, object synthesis, mesh segmentation, point cloud processing, …). The selection of the applications is expected to change with different course offerings and will be adapted to the latest research papers in computer vision and computer graphics.
The ICPC International Collegiate Programming Contest
Bronze Medal

Recent Publications

Find more publications via Google Scholar.

Contact

  • biao.zhang [at] kaust.edu.sa