Stanley Liang photo

Stanley Liang, PhD

Computational Health Research Branch

Contact Information
Nihbc 38A - Lister Hill/1003l

Expertise and Research Interests:

Dr. Stanley Liang is a postdoctoral research fellow in the Computational Health Research Branch, National Library of Medicine, NIH. He received his PhD degree in Computer Science from York University, Canada in 2022. He also received his Doctor of Medicine from Guangzhou University of Chinese Medicine, China, and Master of Public Health (MPH) from Sun Yat-sen University, China. Throughout his academic career so far, Dr. Liang has published 26 research papers, including 15 papers as first author in peer review journals and IEEE conference proceedings. The research interest of Dr. Liang includes deep learning for medical image processing, generative learning for medical image synthesis with generative adversarial network (GAN), and natural language processing (NLP) for electronic health records, and medical genomics.


Liang Z, Huang JX, Antani S. Image Translation by Ad CycleGAN for COVID-19 X-Ray Images: A New Approach for Controllable GAN. Sensors (Basel). 2022 Dec 8;22(24):9628. DOI: 10.3390/s22249628.

Liang Z, Huang JX. Emergency Department Wait Time Prediction based on Cyclical Features by Deep Neural Networks. AMIA 2022 Clinical Informatics Conference. 2022, May 24-26, Houston, USA, Poster.

Liang Z, Huang JX. CycleGAN with Dynamic Criterion for Malaria Blood Cell Image Synthetization. AMIA 2022 Informatics Summit. 2022, Mar 21-24, Chicago. USA.

Liang Z, Huang JX. Adaptive Cycle-consistent Adversarial Network for Malaria Blood Cell Image Synthetization. IEEE Applied Imagery Pattern Recognition Workshop (AIPR), 2021, Oct 12 -14, Washington DC, USA, pp.1-7. DOI: 10.1109/AIPR52630.2021.9762068.