Qinqing Liu

Qinqing Liu

Ph.D. student at University of Connecticut, expert in Machine Learning

I am a Ph.D. student in the Computer Science and Engineering Department, University of Connecticut. My advisor is Prof. Jinbo Bi.

My primary research interests are in deep learning, machine learning and pattern recognition using large-scale datasets, with an emphasis on healthcare informatics, online social networks, cheminformatics and bioinformatics.

Experience

Research Assistant | University of Connecticut

10/2017 - Present

  • Designed deep learning, machine learning methods to improve drug discovery & precision medicine.
  • Constructed the graph convolutional networks on graphs for node embedding and graph embedding.
  • Created various Generative Adversarial Networks (GANs) models on domain mappings, missing imputation, etc.
  • Developed multi-view and multi-task algorithms that automatically detect disorder problems using daily living datasets.
  • Explored contextual embedding of medical concepts from Electronic Health Records (EHRs) with Word2vec.

Co-Investigator | Yale Center for Molecular Discovery, Yale University

10/2018 - Present

  • Designed prominent machine learning methods, especially deep learning, for the early stage of drug design.
  • Designed the molecular graph convolutional networks for learning molecular representations from undirected graphs.
  • Built standard database for protein-drug interactions,

Publications

Edge Attention-based Multi-Relational Graph Convolutional Networks
Chao Shang, Qinqing Liu, Ko-Shin Chen, Jiangwen Sun, Jin Lu, Jinfeng Yi, and Jinbo Bi
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2018, Submitted Code

X Machine Learning(XML) Group

The X Machine Learning (XML) group focuses on machine learning and deep learning algorithms for solving problems involving data with special structure, with an emphasis on healthcare informatics, online social networks and bioinformatics.

Contact

Email: qinqing.liu AT uconn.edu Address: 371 Fairfield Way, Unit 4155, Storrs, Conntecticut 06269