Sotabase

Career

· PhD Candidate, Computer Science, Stanford University2019–
· Data Scientist Intern, Market Intelligence, Microsoft2017–
· Software Engineer Intern, Bing Predicts, Microsoft2016–
· MS in Computer Science, Stanford University2016–2019
· Software Engineer Intern, Satori (Knowledge Graph), Microsoft2015–
· Bachelor of Science in Computer Science and Mathematics, UC Santa Barbara2012–2016

Publications (52)

CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison
AAAI Conference on Artificial Intelligence · 2019
3,120
cited
CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning
arXiv.org · 2017
3,071
cited
Deep learning for chest radiograph diagnosis: A retrospective comparison of the CheXNeXt algorithm to practicing radiologists
PLoS Medicine · 2018
1,158
cited
Deep-learning-assisted diagnosis for knee magnetic resonance imaging: Development and retrospective validation of MRNet
PLoS Medicine · 2018
651
cited
MURA: Large Dataset for Abnormality Detection in Musculoskeletal Radiographs.
2017
372
cited
Human–machine partnership with artificial intelligence for chest radiograph diagnosis
npj Digital Medicine · 2019
206
cited
PENet—a scalable deep-learning model for automated diagnosis of pulmonary embolism using volumetric CT imaging
npj Digital Medicine · 2020
159
cited
AppendiXNet: Deep Learning for Diagnosis of Appendicitis from A Small Dataset of CT Exams Using Video Pretraining
Scientific Reports · 2020
107
cited
GEO-Bench: Toward Foundation Models for Earth Monitoring
Neural Information Processing Systems · 2023
101
cited
MURA Dataset: Towards Radiologist-Level Abnormality Detection in Musculoskeletal Radiographs
arXiv.org · 2017
84
cited
Gap-filling eddy covariance methane fluxes: Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands
2021
83
cited
Many-Shot In-Context Learning in Multimodal Foundation Models
arXiv.org · 2024
55
cited
Evaluation of a Machine Learning Model Based on Pretreatment Symptoms and Electroencephalographic Features to Predict Outcomes of Antidepressant Treatment in Adults With Depression
JAMA Network Open · 2020
54
cited
CheXpedition: Investigating Generalization Challenges for Translation of Chest X-Ray Algorithms to the Clinical Setting
arXiv.org · 2020
49
cited
ForestNet: Classifying Drivers of Deforestation in Indonesia using Deep Learning on Satellite Imagery
arXiv.org · 2020
48
cited
Incorporating machine learning and social determinants of health indicators into prospective risk adjustment for health plan payments
BMC Public Health · 2020
48
cited
TEOChat: A Large Vision-Language Assistant for Temporal Earth Observation Data
International Conference on Learning Representations · 2024
45
cited
Toward Foundation Models for Earth Monitoring: Proposal for a Climate Change Benchmark
arXiv.org · 2021
35
cited
USat: A Unified Self-Supervised Encoder for Multi-Sensor Satellite Imagery
arXiv.org · 2023
35
cited
Marked crosswalks in US transit-oriented station areas, 2007–2020: A computer vision approach using street view imagery
Environment and Planning B Urban Analytics and City Science · 2022
34
cited
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