Sotabase

Career

· MS in Computer Science, Stanford University2023–2024
· Machine Learning Engineer, Valar Labs2023–
· Visiting AI Research Fellow, Harvard Medical School2021–2022
· Research Assistant, Stanford Artificial Intelligence Laboratory (SAIL)2021–2021
· Intern, Trustworthy AI2021–2021
· Bachelor of Science in Computer Science, Stanford University2020–2024
· Researcher, Stanford University School of Medicine2020–2021
· Intern, Emerson Automation Solutions2019–2019
· Intern, The University of Texas Medical Branch2019–2019
· Technical Writer, Towards Data Science2019–2021
· High School Diploma, Carnegie Vanguard High School2016–2020

Publications (12)

Expert-level detection of pathologies from unannotated chest X-ray images via self-supervised learning
Nature Biomedical Engineering · 2022
407
cited
Development of an artificial intelligence-derived histologic signature associated with adjuvant gemcitabine treatment outcomes in pancreatic cancer
Cell Reports Medicine · 2023
15
cited
Development of artificial intelligence–derived histological biomarkers for first-line treatment selection in metastatic pancreatic ductal adenocarcinoma (mPDAC).
Journal of Clinical Oncology · 2023
2
cited
Gemcitabine response prediction in the adjuvant treatment of resected pancreatic ductal adenocarcinoma using an AI histopathology platform.
Journal of Clinical Oncology · 2022
2
cited
1773P Prediction of neoadjuvant chemotherapy response in muscle-invasive bladder cancer: A machine learning approach
Annals of Oncology · 2022
1
cited
Abstract A043: Validation of an artificial intelligence derived histological biomarker for gemcitabine response in resected pancreatic ductal adenocarcinoma (PDAC)
Cancer Research · 2022
1
cited
43/#512 Assessing robustness of an artificial intelligence derived histological biomarker across different sites of disease and in serial sections in tubo-ovarian high-grade serous carcinoma
Featured Printed Posters (Poster Rounds with the Professors) · 2022
44/#219 Predicting response to platinum-based chemotherapy for tubo-ovarian high-grade serous carcinoma using an artificial intelligence histopathology platform
Featured Printed Posters (Poster Rounds with the Professors) · 2022
AI-based pathologic biomarker for pathologic downstaging in patients with muscle-invasive bladder cancer undergoing cystectomy after neoadjuvant nivolumab, gemcitabine, and cisplatin: BLAAST-1 Trial.
Journal of Clinical Oncology · 2023
Corrigendum to “1773P Prediction of chemotherapy response in muscle-invasive bladder cancer: A machine learning approach”
Annals of Oncology · 2023
Enabling Interpretable Histopathology Representation Learning via Multimodal Language Guided Self-Supervision
2023
PD30-03 PREDICTING RESPONSE TO INTRAVESICAL BCG IN HIGH RISK NON-MUSCLE INVASIVE BLADDER CANCER USING AN ARTIFICIAL INTELLIGENCE-POWERED PATHOLOGY ASSAY: DEVELOPMENT AND VALIDATION IN AN INTERNATIONAL 12 CENTER COHORT
Journal of Urology · 2024
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Ekin Tiu | Researcher Profile | Sotabase | Sotabase