Xishuang Dong

Assistant Professor



Dr. Xishuang Dong is a member of CRI Center for Computational Systems Biology and CREDIT, and Assistant Professor at Department of Electrical and Computer Engineering at Prairie View A&M University (PVAMU). He received B.S. degree in computer science and technique at Harbin University of Science and Technology, M.S. degree in computer software and theory at Harbin Engineering University, and Ph.D. in computer application at Harbin Institute of Technology. His 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 Single-Shot Object Detection for Table Detection in Scanned Documents

Medical Data Augmentation via ChatGPT: A Case Study on Medication Identification and Medication Event Classification

Systematic Comparative Analysis of Pre-trained Large Language Models on Contextualized Medication Event Extraction

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


Dr. Dong awarded NSF ExpandAI Capacity Building pliot grant (CAP)

Dr. Dong leads a team from PVAMU and AAMU to win NSF IUSE grant

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