School of Medicine
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Xianghao Zhan
Ph.D. Student in Bioengineering, admitted Autumn 2019
Ph.D. Minor, Biomedical Data Science
Student Employee, DASHBioXianghao Zhan is a 5th -year Ph.D. candidate at Stanford Bioengineering. He obtained his M.S in Bioengineering in 2021 and his M.S in Statistics in 2023 both at Stanford. Before that he got B. Eng. in Control Science and Engineering (Automation) and his B. Art in English Language and Literature with Summa Cum Laude at Chu Kochen Honors College, Zhejiang University, China, in 2019.
Under the guidance of Prof. Oliver Gevaert and Prof. David B. Camarillo, he mainly focuses on the optimization of computational modeling of traumatic brain injury with machine learning and animal modeling based on biomechanical and radiological data. His research interests and projects also extend to the data mining of free-text clinical notes with natural language processing, biomedical data fusion for COVID-19 patient outcome prediction, machine learning reliability quantification with conformal prediction, reliability-based semi-supervised learning, and domain adaptation for biomedical sensory systems (with artificial olfaction systems and surface electromyography systems). He has published 18 peer-reviewed articles as a first/co-first author (IF 131.3) in such journals as NPJ Digital Medicine, IEEE Transactions on Biomedical and Health Informatics, IEEE Transactions on Biomedical Engineering, Journal of Sport and Health Science, with 4 first-author journal articles under review. He has been a peer reviewer for 16 journals including Annals of Biomedical Engineering, Journal of Neurotrauma, Computer methods in biomechanics and biomedical engineering.
In addition to his research, he has two master degrees while pursuing his Ph.D. degree: BIOE 2021 and STATS 2023. He has taken more than 10 data science and machine learning courses at Stanford with course project experiences and technical background with UNet-based image segmentation, BERT, Transformer-XL, DeepSEA, BPNet, VAE/SSVAE, flow model, energy-based model cycle-GAN, CNN-based image classification, LSTM-based clinical event prediction, Bi-LSTM-based neural machine translation, BERT, DCT/DWT/STFT, PCA, DRCA, NFL, convex optimization.
His research is recognized by the field and he was awarded with IET Postgraduate Research Award for an Outstanding Researcher (one awardee across the globe, first Chinese), Siebel Scholar Class of 2024, IET Healthcare Technology William James Award (one awardee across the globe), Stanford Interdisciplinary Graduate Fellowship (highest honor for interdisciplinary Stanford graduates), Pfeiffer Research Foundation Fellow, AMIA Trainee Award (six awardees, the only Chinese), American Society of Neurotrauma Trainee Award (20 awardees, the only Chinese), Chu Kochen Scholarship (12/23,000), Ten most Preeminent Students of Zhejiang University (10/36,000), Chinese National Scholarship (Top 0.2%).
He is dedicated to support underrepresented minorities. He has been a program leader for Stanford Summer Research Program and mentored 3 undergrads from the underrepresented minorities. He has been a research mentor at Foothill College for two years and mentored latino students from local community college. Additionally, he is a sports fan with 13 Stanford Intramural champions (10 volleyball, 3 tennis) and two medals from regional volleyball tournaments. He enjoys the sport passion and team spirits as a captain. -
Weiruo Zhang
Research Engineer, Biomedical Data Science
BioDr. Zhang is currently a Research Engineer at the Department of Biomedical Data Science and the Center for Cancer Systems Biology, Stanford School of Medicine. Dr. Zhang obtained her M.S. and Ph.D. in Electrical Engineering, both from Stanford University. Her Ph.D. studies focused on developing computational algorithms for metabolomics data analysis, in which she received Young Scientist Award from the Metabolomics Society for her algorithm on metabolic network analysis delineating the effects of genetic mutants and drug treatment on the metabolome. Her postdoctoral studies at the Department of Radiology, Stanford School of Medicine, integrated radiomic data and genomic data that identified a prognostic metabolic regulation biomarker for non-small cell lung cancer. Her current research primarily focuses on developing and implementing novel computational methods to integrate and analyze single-cell multi-omics data, such as single-cell RNA sequencing, spatial proteomics and spatial transcriptomics. She has developed algorithms to solve computational challenges of spatial omics data and to identify mediators for cell-cell interactions associated with metastasis that was featured in Stanford Medicine Magazine. Dr. Zhang has authored and co-authored publications including Nature, Cell, Nature Methods etc. Her research aims at bridging multi-omics, imaging, machine learning, artificial intelligence to better understand biology for cancer progression and immunosuppression.
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James Zou
Associate Professor of Biomedical Data Science and, by courtesy, of Computer Science
Current Research and Scholarly InterestsMy group works on both foundations of statistical machine learning and applications in biomedicine and healthcare. We develop new technologies that make ML more accountable to humans, more reliable/robust and reveals core scientific insights.
We want our ML to be impactful and beneficial, and as such, we are deeply motivated by transformative applications in biotech and health. We collaborate with and advise many academic and industry groups.
