Ziwen (Phoebe) Pan
Ziwen (Phoebe) Pan
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PhD Student
PhD Student
Computational Biology and Biomedical Informatics Program
Computational Biology and Biomedical Informatics Program
Yale University
Yale University
I am a PhD student in the Computational Biology and Biomedical Informatics Program at Yale University. My research interests are at the intersection of machine learning, causal inference, and multimodal data integration, with the goal of developing robust and interpretable computational methods for biomedical research and healthcare. I am particularly interested in leveraging statistical learning and computational models to understand complex biological systems, integrate heterogeneous biomedical data, and enable reliable data-driven discoveries.
I am a PhD student in the Computational Biology and Biomedical Informatics Program at Yale University. My research interests are at the intersection of machine learning, causal inference, and multimodal data integration, with the goal of developing robust and interpretable computational methods for biomedical research and healthcare. I am particularly interested in leveraging statistical learning and computational models to understand complex biological systems, integrate heterogeneous biomedical data, and enable reliable data-driven discoveries.
Recent News
Recent News
May 2026: I am excited to announce that I have completed my Bachelor of Science in Applied Mathematics and Statistics, graduating with Highest Honors, at Emory University. I am deeply grateful to my mentor, Prof. Ruoxuan Xiong, for her guidance and support throughout my studies.
May 2026: I am excited to announce that I have completed my Bachelor of Science in Applied Mathematics and Statistics, graduating with Highest Honors, at Emory University. I am deeply grateful to my mentor, Prof. Ruoxuan Xiong, for her guidance and support throughout my studies.
Apr. 2026: Our work “AlgoTrace: Algorithmic Primitives and Compositional Geometry of Reasoning in Language Models” has been accepted to the ICML 2026.
Apr. 2026: Our work “AlgoTrace: Algorithmic Primitives and Compositional Geometry of Reasoning in Language Models” has been accepted to the ICML 2026.
Apr. 2026: Our work “Learning Dynamic Representations and Policies from Multimodal Clinical Time-Series with Informative Missingness” has been accepted to the Findings of ACL 2026.
Apr. 2026: Our work “Learning Dynamic Representations and Policies from Multimodal Clinical Time-Series with Informative Missingness” has been accepted to the Findings of ACL 2026.
Apr. 2026: Our work “DART: Mitigating Harm Drift in Difference-Aware LLMs via Distill-Audit-Repair Training” has been accepted to ACL 2026 Findings.
Apr. 2026: Our work “DART: Mitigating Harm Drift in Difference-Aware LLMs via Distill-Audit-Repair Training” has been accepted to ACL 2026 Findings.
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