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 Classification, Molecule Generation via Graph Neural Network and Medical Image Synthesis. He is currently working on GNN for Molecule Generation with Dr. Liang Zhao, Dr. Amarda Shehu and ASL Recognition with Dr. Parth Pathak. He joins MIRACLE Lab in Chinese Academy of Sciences, Institute of Computing Technology, working with Dr. Hu Han and Dr. Kevin Zhou for a research intern starting Aug, 2020 on medical image synthesis.
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!
- Machine Learning for Drug Discovery
- Protein Structure Prediction
- Application of Millimeter-wave Radar
- Structured Data Mining
- Deep Generative Models
- Medical Image Analysis
- Educational Data Science
- 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 & Working Papers
- Controlling the Generation of Molecules via Interpretable Variational Autoencoders, submitted to a bioinformatics journal, Yuanqi Du, Xiaojie Guo, Amarda Shehu, Liang Zhao
- Controllable Molecule Generation via Monotonic Constraints, submitted to RECOMB conference, Yuanqi Du, Xiaojie Guo, Amarda Shehu, Liang Zhao
- Property Controllable Variational Autoencoder via Invertible Mutual Dependence, submitted to a major ML conference, Xiaojie Guo, Yuanqi Du, Liang Zhao
- Deep Learning for Tertiary Structure Reconstruction at Varying Representational Detail, gointg to submit to a bioinformatics journal, Yuanqi Du, Anowarul Kabir, Liang Zhao, Amarda Shehu
- Generative Adversarial Learning of Protein Tertiary Structures, going to submit to a bioinformatics journal, Taseef Rahman, Yuanqi Du, Amarda Shehu
- Improving Student Academic Performance Prediction via Ensemble Learning, Kaiyi Guan, Huzefa Rangwala, Yuanqi Du*