Xishuang Dong

Assistant Professor



I am a Postdoc of CRI Center for Computational Systems Biology at Department of Electrical and Computer Engineering at Prairie View A&M University (PVAMU). I was an Assistant Professor in the School of Computer Informatics at Xinyang Normal University, China, from 07/2014 to 10/2017. I received B.S. degree in computer science and technique (sub-field of computer engineering) at Harbin University of Science and Technology, M.S. degree in computer software and theory (sub-field of computer engineering) at Harbin Engineering University, and Ph.D. in computer application (sub-field of computer engineering) at Harbin Institute of Technology.

My research interests include: 1) machine learning based computational systems biology; (2) biomedical information processing; (3) deep learning for big data analysis; (4) natural language processing.

Recent Papers

Semi-supervised bidirectional RNN for misinformation detection

Calibrated bagging deep learning for image semantic segmentation: A case study on COVID-19 chest X-ray image

Performance Evaluation of Data Augmentation for Object Detection in XView Dataset

Integrating Human-in-the-loop into Swarm Learning for Decentralized Fake News Detection

Semi-supervised Deep Learning for Cell Type Identification from Single-Cell Transcriptomic Data

Efficient Privacy Preserving Edge Computing Framework for Image Classification

Semi-supervised Learning for COVID-19 Image Classification via ResNet

Robust Face Mask Detection using Deep Learning on IoT Devices

Data Driven Network Monitoring and Intrusion Detection using Machine Learning

Inference Performance Comparison of Convolutional Neural Networks on Edge Devices

Two-Path Deep Semisupervised Learning for Timely Fake News Detection

Ensemble Deep Learning on Time-Series Representation of Tweets for Rumor Detection in Social Media

Effective covid-19 screening using chest radiography images via deep learning

Recurrent Neural Network Based Feature Selection for High Dimensional and Low Sample Size Micro-array Data

Probing glioblastoma and its microenvironment using single-nucleus and single-cell sequencing

Deep learning for named entity recognition on Chinese electronic medical records: Combining deep transfer learning with multitask bi-directional LSTM RNN

A multitask bi-directional RNN model for named entity recognition on electronic medical records


CCSB Student Lucy Nwosu featured in Student Researcher Spotlight

Undergraduate Student Research Funding

Drs Anna Joy and Dumitru Iacobas have been promoted to research faculty

CCSB became a part of Half-Million Dollar Grant