Siyi Tang

siyitang at stanford dot edu

I am a PhD student in Electrical Engineering at Stanford University advised by Prof. Daniel Rubin. My research interests lie in the intersection of machine learning and medicine. I develop machine learning methods for medical applications by leveraging the important characteristics in medical data. I work closely with clinical experts from the Stanford School of Medicine to better understand the clinical needs.

Since April 2021, I have been co-organizing the Stanford MedAI Group Exchange Sessions, a weekly seminar series that discusses most recent advances in medical AI research. Check out our YouTube Channel!

I received my Bachelor's Degree in Electrical Engineering (Highest Distinction Honors) from National University of Singapore, where I was fortunate to be advised by Prof. Nitish Thakor and Prof. Thomas Yeo.

CV  /  GitHub  /  Google Scholar  /  LinkedIn

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News

  • 2022-04: I presented our work on deep-learning-based multimodal fusion for atrial fibrillation outcome prediction at Heart Rhythm 2022. The abstract has received the Highest Scoring Abstract in Digital Health Award!

  • 2022-01: Our paper on self-supervised graph neural network for EEG seizure analysis has been accepted to ICLR 2022!

  • 2021-12: I obtained my MS Degree!

  • 2021-04: Our paper on data valuation for chest X-rays is now out on Scientific Reports.

  • 2021-02: I will be joining the medical AI team at Salesforce Research for a summer internship!

  • 2020-12: I presented our work on transfer and meta-learning for EEG analysis at AES 2020.

  • 2020-06: Our paper on Autism Spectrum Disorder subtyping with a Bayesian model is now out on Biological Psychiatry.

  • 2020-01: I passed my PhD qualifying exam and advanced to PhD candidacy!

Selected Publications

Multimodal Spatiotemporal Graph Neural Networks for Improved Prediction of 30-Day All-Cause Hospital Readmission


Siyi Tang*, Amara Tariq*, Jared Dunnmon, Umesh Sharma, Praneetha Elugunti, Daniel Rubin, Bhavik N. Patel, Imon Banerjee
arXiv, 2022
preprint / code /

Self-Supervised Graph Neural Networks for Improved Electroencephalographic Seizure Analysis


Siyi Tang, Jared Dunnmon, Khaled Saab, Xuan Zhang, Qianying Huang, Florian Dubost, Daniel Rubin, Christopher Lee-Messer
International Conference on Learning Representations, 2022
paper / code /

Data Valuation for Medical Imaging Using Shapley Value and Application to a Large-Scale Chest X-Ray Dataset


Siyi Tang, Amirata Ghorbani, Rikiya Yamashita, Sameer Rehman, Jared A Dunnmon, James Zou, Daniel L Rubin
Scientific Reports, 2021
paper /

Comparison of Segmentation-Free and Segmentation-Dependent Computer-Aided Diagnosis of Breast Masses on a Public Mammography Dataset


Rebecca S Lee, Jared A Dunnmon, Ann He, Siyi Tang, Christopher Ré, Daniel L Rubin
Journal of Biomedical Informatics, 2021
paper /

Reconciling dimensional and categorical models of autism heterogeneity: a brain connectomics and behavioral study


Siyi Tang*, Nanbo Sun*, Dorothea L Floris, Xiuming Zhang, Adriana Di Martino, BT Thomas Yeo
Biological psychiatry, 2020
paper / code /

Somatosensory-motor dysconnectivity spans multiple transdiagnostic dimensions of psychopathology


Valeria Kebets, Avram J Holmes, Csaba Orban, Siyi Tang, Jingwei Li, Nanbo Sun, Ru Kong, Russell A Poldrack, BT Thomas Yeo
Biological psychiatry, 2019
paper /


Conference Presentations

Machine Learning-Enabled Multimodal Fusion of Intra-Atrial and Body Surface Signals in Prediction of Atrial Fibrillation Ablation Outcomes (Highest Scoring Abstract in Digital Health)


Siyi Tang, Orod Razeghi, Ridhima Kapoor, Mahmood Alhusseini, Muhammad Fazal, Albert Rogers, Miguel Rodrigo Bort, Paul Clopton, Paul Wang, Daniel Rubin, Sanjiv Narayan, Tina Baykaner
Heart Rhythm, 2022

Self-Supervised Graph Neural Networks for Improved Electroencephalographic Seizure Analysis


Siyi Tang, Jared Dunnmon, Khaled Saab, Xuan Zhang, Qianying Huang, Florian Dubost, Daniel Rubin, Christopher Lee-Messer
International Conference on Learning Representations, 2022

From Adults to Neonates: Transfer and Meta-learning Approaches for Knowledge Generalization in Deep Networks for Electroencephalographic Analysis


Siyi Tang, Daniel L Rubin, Chris Lee-Messer
American Epilepsy Society (AES) Annual Meeting, 2020

Latent ASD Factors with Dissociable Functional Connectivity Patterns and Behavioral Symptoms


Siyi Tang*, Nanbo Sun*, Dorothea L Floris, Xiuming Zhang, Adriana Di Martino, BT Thomas Yeo
Organization for Human Brain Mapping (OHBM) Annual Meeting, 2018

Live demonstration: Real-time orientation estimation and grasping of household objects for upper limb prostheses with a dynamic vision sensor (Honorable Mention Award)


Siyi Tang, Rohan Ghosh, Nitish V Thakor, Sunil L Kukreja
2016 IEEE Biomedical Circuits and Systems Conference (BioCAS), 2016


Teaching

About Me

My Chinese name is 汤斯怡. I grew up in a beutiful city, Zhang Zhou, in Fujian Province of China. I lived in Singapore for 7+ years before coming to Stanford.

Besides research, I also enjoy photography, cooking and baking, violin and traveling around the world. You can find some of my photography works here.


Design and source code from Jon Barron's and Leonid Keselman's websites