Yuanqi Du

Yuanqi Du is a senior undergraduate student studying Computer Science at George Mason University. He has broad interests in machine learning and data mining. He worked on Outlier Detection, American Sign Language Recognition (Mili-meter Wave Signals & Kinect), Protein Structure Prediction, Molecule Generation via Graph Neural Network, Deep Graph Learning and Medical Image Analysis. He worked with Prof. Liang Zhao, Prof. Amarda Shehu, Prof. Parth Pathak, Prof. Carlotta Domeniconi while he was at GMU. He worked in the MIRACLE Lab in Chinese Academy of Sciences, Institute of Computing Technology, with Prof. Hu Han and Prof. S. Kevin Zhou for a research intern from Aug to Dec 2020 on medical image analysis. He joined Microsoft Research Asia Machine Learning and Computational Biology group as a research intern in Nov 2020, working on Protein Structure Prediction.

Drop me an email if you’d like to talk about/collaborate on any of the following research topics or other research areas with me. I currently live in Beijing, China, feel free to grab a coffee with me, too!

Check out my CV and a pdf version

Research Interests

  • Graph Mining
  • Deep Generative Models
  • Protein Structure Prediction
  • Machine Learning for Drug Discovery
  • Application of Millimeter-wave Signals

News!

  • 1/21 Paper titled “Property Controllable Variational Autoencoder via Invertible Mutual Dependence”, Xiaojie Guo, Yuanqi Du, Liang Zhao*, accepted in ICLR 2021.
  • 12/20 Serve as a Web Team member for KDD 2021!
  • 12/20 Paper titled “Deep Learning to Segment Pelvic Bones: Large-scale CT Datasets and Baseline Models” conditionally accepted in IPCAI 2021
  • 11/20 Accepted to be a Microsoft Learn Student Ambassador!
  • 11/20 Accepted to AAAI 2021 Student Technical Volunteer Program!
  • 11/20 I am glad to receive a NeurIPS 2020 Travel Award. Excited to attend NeurIPS 2020!
  • 10/20 I am glad to receive the AIJ AIIDE 2020 Attendance Fellowship! Thanks, AIJ! Can’t wait to see the battle between AI agents and human players in strategy games like StarCraft!
  • 09/20 Our DeepASL Dataset is publicly available, the dataset constains ASL single-word signs, sentences and non-manual markers collected from 5 Professional ASL users using an FMCW Signal Sensor
  • 07/20 Paper titled “Interpretable Molecule Generation via Disentanglement Learning” accepted at ACM Conference of Bioinformatics and Computational Biology (BCB) Workshops: Computational Structural Biology Workshop (CSBW) 2020, 8 pages, to appear in the proceedings of ACM BCB 20 soon
  • 07/20 Paper titled “From Interatomic Distances to Protein Tertiary Structures with a Deep Convolutional Neural Network” accepted at ACM Conference of Bioinformatics and Computational Biology (BCB) Workshops: Computational Structural Biology Workshop (CSBW) 2020, 8 pages, to appear in the proceedings of ACM BCB 20 soon

Preprints (under review)

  • Controlling the Generation of Molecules via Interpretable Variational Autoencoders, submitted to a bioinformatics journal, Yuanqi Du, Xiaojie Guo, Amarda Shehu, Liang Zhao*
  • Where is the disease? Semi-supervised pseudo-normality synthesis from an abnormal image, submitted to a major Computer-Assisted Interventions conference, Yuanqi Du, Quan Quan, Han Hu, S. Kevin Zhou*
  • Generative Adversarial Learning of Protein Tertiary Structures, submitted to a bioinformatics journal, Taseef Rahman, Yuanqi Du, Amarda Shehu*
  • CT Film Recovery via Disentangling Geometric Deformation and Photometric Degradation: Simulated Datasets and Deep Models, submitted to a major Computer Vision conference, Quan Quan, Qiyuan Wang, Liu Li, Yuanqi Du, S. Kevin Zhou*