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劉響,助理教授

聯系信息

姓名:劉響 辦公電話: +86-10-627-94823 郵箱:發送郵件 傳真號碼:+86-10-6279-4399 地點:清華大學舜德樓中514 教師主頁:

個人簡介

劉響,清華大學工業工程系助理教授。2019年博士畢業于美國密西根大學。研究方向為醫療服務系統工程;包括疾病建模預測、臨床決策優化,醫院運營管理,公共衛生醫療政策。研究方法包括隨機過程控制,動態規劃、優化、數據挖掘和分析。
研究獲2019年生產與運營管理學會(POMS)Wickham Skinner最佳論文獎亞軍,
2018年管理科學與籌學會(INFORMS)制造與服務運營管理分會(MSOM)數據驅動研究挑戰決賽入圍(Data Driven Research Challenge Finalist), 2013年管理科學與籌學會(INFORMS)公共部門運籌學分會(PSOR)最佳論文榮譽獎(PSOR Best Paper Award Honorable Mention)。

劉響老師每年都有計劃招收博士和碩士, 歡迎具有良好數學基礎,擅長編程,并且熱愛學術的同學發送簡歷到:xiang-liu@mail.tsinghua.edu.cn

所獲獎勵

生產與運營管理學會(POMS)Wickham Skinner最佳論文獎亞軍,2019
管理科學與籌學會(INFORMS)制造與服務運營管理分會(MSOM)數據驅動研究挑戰決賽入圍(Data Driven Research Challenge Finalist), 2018
美國泌尿科學會(American Urological Association)年會最佳海報獎,2017
管理科學與籌學會(INFORMS)公共部門運籌學分會(PSOR)最佳論文獎入圍(PSOR Best Paper Award Finalist),2013

教育背景

美國密西根大學,工業工程,博士,2019
美國加州大學伯克利分校,工業工程與運籌學,碩士,2014
美國密西根大學,工業工程,學士(以最高榮譽畢業),2013
上海交通大學,機械工程,學士,2013

工作經歷

2019年10月至今,清華大學,工業工程系,助理教授

講授課程

IOE 202 Operations Modeling,密西根大學

研究興趣

應用:疾病建模預測、臨床決策優化,醫院運營管理,公共衛生醫療政策
方法:隨機過程控制,動態規劃、優化、數據挖掘和分析

論文發表

期刊論文

  1. X. Liu, M. Hu, J. E. Helm, M. S. Lavieri, and T. A. Skolarus, “Missed opportunities in preventing hospital readmissions: Redesigning post-discharge checkup policies,” Production and Operations Management, vol. 27, no. 12, pp. 2226–2250, 2018.
  2. W. Hu, M. S. Lavieri, A. Toriello, and X. Liu, “Strategic health workforce planning,” IIE Transactions, vol. 48, no. 12, pp. 1127–1138, 2016.
  3. P. Kirk, T. A. Skolarus, B. Jacobs, Y. Qin, B. Li, M. Sessine, X. Liu, et al., “Characterizing ‘Bounce-back’ Readmissions After Radical Cystectomy,” BJU International, doi:10.1111/bju.14874, 2019.
  4. A. Lee, X. Liu, et al., “Role of post-acute care on hospital readmission after high-risk surgery,” Journal of Surgical Research, vol. 234, pp. 116–122, 2019.
  5. G.-G. Garcia, M. S. Lavieri, C. Andrews, X. Liu, et al., “Using a Machine Learning Technique Called Kalman Filtering to Forecast Conversion from Ocular Hypertension to Primary Open Angle Glaucoma” Investigative Ophthalmology & Visual Science, vol. 50, no. 9 pp. 2857–2857, 2019.
  6. G.-G. Garcia, K. Nitta, M. S. Lavieri, C. Andrews, X. Liu, et al., “Using Kalman Filtering to Forecast Disease Trajectory for Patients with Normal Tension Glaucoma,” American Journal of Ophthalmology, doi:10.1016/j.ajo.2018.10.012, 2018.
  7. N. Krishnan, X. Liu, et al., “A model to optimize followup care and reduce hospital readmissions after radical cystectomy,” The Journal of Urology, vol. 195, no. 5, pp. 1362– 1367, 2016.
  8. G. J. Schell, M. S. Lavieri, J. E. Helm, X. Liu, et al., “Using filtered forecasting techniques to determine personalized monitoring schedules for patients with open-angle glaucoma,” Ophthalmology, vol. 121, no. 8, pp. 1539–1546, 2014.

會議論文

  1. M. Sessine, T. Borza, A. Weizer, P. Kirk, X. Liu, et al., “MP71-02 reframing readmission reduction incentives after radical cystectomy,” The Journal of Urology, vol. 199, no. 4, e943, 2018.
  2. S. Finley, S. Joshi, T. Borza, X. Liu, et al., “MP04-06 personalized decision support tool to prevent hospital readmission for patients treated with radical cystectomy,” The Journal of Urology, vol. 197, no. 4, e30, 2017.
  3. P. Kirk, X. Liu, et al., “MP71-04 assessing laboratory parameters and readmissions after radical cystectomy,” The Journal of Urology, vol. 199, no. 4, e944, 2018.
  4. M. S. Lavieri, X. Liu, et al., “Using kalman filtering to personalize the monitoring of persons with normal tension glaucoma,” Investigative Ophthalmology & Visual Science, vol. 58, no. 8, pp. 2870–2870, 2017.
  5. N. Krishnan, X. Liu, et al., “PD25-08 a model to optimize follow-up care and reduce hospital readmissions after radical cystectomy,” The Journal of Urology, vol. 193, no. 4, e563, 2015.
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