Yun Zhao

Contact

  • ✉ Email: yunzhao20 NOSPAM AT meta DOT com

Biography

Dr. Yun Zhao is a research scientist at Meta Platforms, Inc. (formerly known as Facebook, Inc.) at Menlo Park, California, United States. He received his PhD degree in the Department of Computer Science, University of California, Santa Barbara in April, 2021. His Ph.D. advisor is Prof. Linda Petzold. Before that, he received his B.E. degree and M.E. degree from Zhejiang University and Tsinghua University, respectively. His Masters academic advisor is Prof. Zhisheng Niu. He was the recipient of the Best Paper Award in the 9th Workshop on Data Mining in Biomedical Informatics and Healthcare (DMBIH’21), and the Best Student Paper Award in the 13th ACM Conference on Bioinformatics, Computational Biology, and Health Information (BCB’22). His research interests include machine learning, recommendation system and data mining.

Research

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Publons

Publications

  1. Yuqing Wang, Yun Zhao, Linda Petzold, "An empirical study on the robustness of the segment anything model (sam),” in submission, 2023. PDF
  2. Yuqing Wang, Yun Zhao, Linda Petzold, "Are Large Language Models Ready for Healthcare? A Comparative Study on Clinical Language Understanding,” in Machine Learning for Healthcare Conference, PMLR, 2023. PDF
  3. Yu Deng, Lei Liu, Hongmei Jiang, Yifan Peng, Yishu Wei, Zhiyang Zhou, Yizhen Zhong, Yun Zhao, Xiaoyun Yang, Jingzhi Yu, Zhiyong Lu, Abel Kho, Hongyan Ning, Norrina B. Allen, John Wilkins, Kiang Liu, Donald Lloyd-Jones, Lihui Zhao, "Comparison of State-Of-The-Art Neural Network Survival Models With The Pooled Cohort Equations for Cardiovascular Disease Risk Prediction,” in BMC Medical Research Methodology, 2023. PDF
  4. Haotian Xia, Rhys Tracy, Yun Zhao, Erwan Fraisse, Yuan-Fang Wang, Linda Petzold, "VREN: Volleyball Rally Dataset with Expression Notation Language” in IEEE International Conference on Knowledge Graph (ICKG), 337 - 346, 2022. PDF
  5. Zhuowei Cheng, Franklin Ly, Tyler Santander, Elyes Turki, Yun Zhao, Jamie Yoo, Kian Lonergan, Jordan Gray, Christopher H Li, Henry Yang, Michael Miller, Paul Hansma, Linda Petzold, "Preliminary study: quantification of chronic pain from physiological data,” in Pain Reports, 2022. PDF
  6. Yuqing Wang, Yun Zhao and Linda Petzold, "Predicting the Need for Blood Transfusion in Intensive Care Units with Reinforcement Learning,” in ACM-BCB 2022 , Chicago, IL, USA, Aug. 2022. PDF (Recipient of the Best Student Paper Award)
  7. Yuqing Wang*, Yun Zhao* and Linda Petzold, "Integrating Physiological Time Series and Clinical Notes with Transformer for Early Prediction of Sepsis,” in ICDM 2022 , New York, USA, Jul. 2022. PDF
  8. Yuqing Wang, Yun Zhao and Linda Petzold, "Enhancing Transformer Efficiency for Multivariate Time Series Classification,” in ICDM 2022 , New York, USA, Jul. 2022. PDF
  9. Yun Zhao*, Yuqing Wang*, Junfeng Liu, Haotian Xia, Zhenni Xu, Qinghang Hong, Zhiyang Zhou, Linda Petzold, "Empirical Quantitative Analysis of COVID-19 Forecasting Models,” in ICDM Workshop 2021 , Auckland, New Zealand, Dec. 2021. PDF (Recipient of the Best Paper Award)
  10. Yun Zhao, "Data Mining in Neuroscience and Healthcare,” PhD Thesis, UC Santa Barbara, 2021. PDF
  11. Xinlu Zhang*, Yun Zhao*, Rachael Callcut and Linda Petzold, "Multiple Organ Failure Prediction with Classifier-Guided Generative Adversarial Imputation Networks,” in BIOKDD 2021 , Virtual, Aug. 2021. PDF
  12. Yun Zhao, Qinghang Hong, Xinlu Zhang, Yu Deng, Yuqing Wang and Linda Petzold, "BERTSurv: BERT-Based Survival Models for Predicting Outcomes of Trauma Patients,” in ICDM 2021 , New York, USA, Jul. 2021. PDF
  13. Yuqing Wang*, Yun Zhao*, Rachael Callcut and Linda Petzold, "Empirical Analysis of Machine Learning Configurations for Prediction of Multiple Organ Failure in Trauma Patients,” in ICDM 2021 , New York, USA, Jul. 2021. PDF
  14. Yun Zhao, Franklin Ly, Qinghang Hong, Zhuowei Cheng, Tyler Santander, Henry T. Yang, Paul K. Hansma, and Linda Petzold, "How Much Does It Hurt: A Deep Learning Framework for Chronic Pain Score Assessment,” in DMBIH 2020 , Sorrento, Italy, Nov. 2020. PDF
  15. Yun Zhao, Richard Jiang, Zhenni Xu, Elmer Guzman, Paul K. Hansma and Linda Petzold, “Scalable Bayesian Functional Connectivity Inference for Multi-Electrode Array Recordings,” in BIOKDD 2020 , San Diego, USA, Aug. 2020. PDF
  16. Yun Zhao, Elmer Guzman, Morgane Audouard, Zhuowei Cheng, Paul K. Hansma, Kenneth S. Kosik, and Linda Petzold, “A Deep Learning Framework for Classification of in vitro Multi-Electrode Array Recordings,” in ICDM 2019 , New York, USA, Jul. 2019. PDF
  17. Yun Zhao, “An Auxiliary Classifier Generative Adversarial Framework for Relation Extraction,” Sep. 2019. PDF
  18. Yun Zhao, Sheng Zhou, and Zhisheng Niu, “Energy-Efficient Task Offloading for Multiuser Mobile Cloud Computing,” in IEEE ICCC 2015 , Shenzhen, China, Nov. 2015. PDF
  19. Tianchu Zhao, Sheng Zhou, Xueying Guo, Yun Zhao, and Zhisheng Niu, “A Cooperative Scheduling Scheme of Local Cloud and Internet Cloud for Delay-Aware Mobile Cloud Computing,” in IEEE Globecom Workshop 2015 , San Diego, CA, USA, Dec. 2015. PDF
  20. Yangtian Yan, Bangcheng Sun, Yun Zhao, Zhenhui Huang, Hui Yang, and Jian Song, “A Bi-directional Visible Light Communication System Based on DTMB-A,” in IEEE VTC 2016 ,Nanjing, China, May, 2016. PDF
  21. Tianchu Zhao, Sheng Zhou, Xueying Guo, Yun Zhao, and Zhisheng Niu, “Pricing policy and computational resource provisioning for delay-aware mobile edge computing,” in IEEE ICCC 2016 , Xi’an , China, Jul. 2016. PDF
  22. Xinyi Zhang, Shiliang Tang, Yun Zhao,Gang Wang, Haitao Zheng and Ben Y. Zhao, “Cold Hard E-Cash: Friends and Vendors in the Venmo Digital Payments System,” in ICWSM 2017 .PDF
  23. Yun Zhao, “Energy-efficient Resource Allocation in Mobile Cloud Computing,” Master Thesis. PDF
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