Publications

Chenlian Fu, Jennifer Yu, Ruian Shi, Michele Waters, Mitchell Pavlak, Andrea Arfe, Sohrab P. Shah, Alexis Battle, Kenneth L. Kehl, Brian M. Bot, US Cancer AI Alliance (CAIA), Nikolaus Schultz, Quaid Morris, Justin Jee (2026). Longitudinal AI Models Predict Cancer Adverse Events. medRxiv.

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Jennifer Yu, Madison Darmofal, Michele Waters, January Choy, Thinh N. Tran, Chenlian Fu, Leah Morales, Kaicheng U, Ross L. Levine, Nikolaus Schultz, Michael F. Berger, Quaid Morris, Justin Jee (2026). Generalist large language models complement tailor-made predictors for tumor genomics interpretation. bioRxiv.

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Tina Behrouzi, Jennifer Yu, Robin Yang, Adrien Boch, Anna Goldenberg, Sarah M. Goodday, Stephen H. Friend (2026). Benefit of the N-of-1 Approach Versus Aggregate Analysis in Tracking Individual Trajectories During Pregnancy: Comparison of Longitudinal Wearable Observational Studies. JMIR Form Res.

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Jennifer Yu, Madison Darmofal, Michele Waters, January Choy, Thinh N. Tran, Chenlian Fu, Leah Morales, Kaicheng U, Ross L. Levine, Nikolaus Schultz, Michael F. Berger, Quaid Morris, Justin Jee (2026). Large language models for tumor genomic interpretation. In AACR 2026.

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Christopher J. Fong, Kaicheng U, Cheryl Phua, Xuechun Bai, Karl Pichotta, Kathryn Tsai, Anzhi Chen, Meixuan Zhang, Jennifer Yu, Whitney Underwood, Chenlian Fu, Michele Waters, Sanna Goyert, Adam Schoenfeld, Nikolaus Schultz, Justin Jee, Jessica Scott, Luke Pike, Jian Carrot-Zhang (2026). Allostatic load connects tumor genomics, disease trajectory, and pre-diagnosis wearable activity. In AACR 2026.

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Phoebe Chuang, Tina Behrouzi, Jennifer Yu, Robin Yang, K. Stemmler, Sarah M. Goodday, Stephen H. Friend, Anna Goldenberg (2026). CodeWearBook: Retrieval-Grounded Natural-Language Querying of Wearable Health Datasets Using Large Language Models. Under review.

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Rui Zhu, Jennifer Yu, Stephen H. Friend, Sarah M. Goodday, Bo Wang, Anna Goldenberg (2025). Towards a personalized pregnancy experience: Forecasting symptoms using graph neural networks and digital health technologies. In ML4H 2024.

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Ji-Hong Chen, Lijun Liu, Jennifer Yu, Jan D. Huizinga (2024). Evaluating stimulus-based heart rate variability assessment in chronic constipation using a machine learning approach. In MLHC 2024.

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Jennifer Yu, Zhenqin Wu, Aaron Mayer, Alexandro Trevino, James Zou (2024). A Multi-Granularity Approach to Similarity Search in Multiplexed Immunofluorescence Images. In MLCB 2023.

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Jennifer Yu, Tina Behrouzi, Kopal Garg, Anna Goldenberg, Sana Tonekaboni (2023). Dynamic Interpretable Change Point Detection for Physiological Data Analysis. In ML4H 2023.

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Jennifer Yu, Mai Ali, Rui Zhu, Parinita Edke, Anna Goldenberg (2023). Childhood Adversity’s Impact on Dynamic Mental Health During and Post Pregnancy. In DSTNDS 2023.

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Amer Hussain, Zhenyu Zhang, Jennifer Yu, Ruihan Wei, Hamza Arshad, Jinhwan Lew, Cierra Jagan, Yongdong Wang, Ji-Hong Chen, Jan D. Huizinga (2023). Haustral rhythmic motor patterns of the human large bowel revealed by ultrasound. Am J Physiol Gastrointest Liver Physiol.

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Jennifer Yu, Rui Zhu, Parinita Edke (2023). Exploring Model Compression Techniques for Deep Learning based Image Compression Models. IRJMETS.

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Hajar Abedi, Martin Ma, James He, Jennifer Yu, Ahmad Ansariyan, George Shaker (2023). Deep Learning-Based In-Cabin Monitoring and Vehicle Safety System Using a 4-D Imaging Radar Sensor. IEEE Sensors.

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Hajar Abedi, Martin Ma, Jennifer Yu, James He, Ahmad Ansariyan, George Shaker (2022). On the Use of Machine Learning and Deep Learning for Radar- Based Passenger Monitoring. In IEEE AP-S/URSI 2022.

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Jennifer Yu, Duncan Forster, Shraddha Pai (2021). Extending Similarity Network-Based Classifiers to the Non-Coding Genome and Deep Learning. In MLCB 2021.

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