李京山博士现为清华大学工业工程系Gavriel Salvendy讲席教授、系主任，是IEEE会士和IISE会士。曾任美国威斯康星大学麦迪逊分校工业与系统工程系终身正教授（至2021年9月）。他的主要研究领域包括系统建模、分析和控制，并应用在生产、服务和医疗领域，做出了许多重要的原创性工作，发表了大量经同行评议的期刊和会议论文，著有2本教材，编纂了7本丛书。李京山教授曾获得美国国家科学基金会早期职业奖、IEEE机器人与自动化学会早期职业奖、多项国际顶级期刊与会议大奖和最佳教材奖，以及威斯康星大学多项荣誉奖项。曾任多个国际顶级年会主席和著名期刊资深编辑，曾参与组织过多个旗舰国际会议，获得过诸多来自政府部门、工业界和医疗机构的研究经费。

2000：博士，密西根大学安娜堡分校电机工程与计算机科学系

1992：硕士，中国科学院自动化所

1989：学士，清华大学自动化系

智能制造与智慧医疗服务系统的建模、分析、控制和优化。

·IISE 会士 2020

·IEEE 杰出讲师 2018

·IEEE 会士 2017

·最佳论文奖，IEEE International Conference on Automation Science and Engineering, Gothenburg, Sweden, 2015

·最佳论文奖，IFAC Conference on Manufacturing Modeling, Management and Control, St Petersburg, Russia, 2013

·早期职业奖，美国国家科学基金会，2010

·最佳论文奖, IIE Transactions, 2009

·早期职业奖，IEEE Robotics and Automation Society, 2006

·最佳论文奖，IEEE Transactions on Automation Science and Engineering, 2005

·Production Systems Engineering，J. Li, S.M. Meerkov, Springer, 2009

·生产系统工程（中译本），北京理工大学出版社，2012

·J. Li, N. Kong and X. Xie, Stochastic Modeling and Analytics in Healthcare Delivery Systems, World Scientific Publishing, 2017.

·J. Li, B. Lennartson, G. Tang, S. Biller and A. Matta, Sustainable Production Automation, Momentum Press, 2016.

·J. Li, S. Zhou and Y. Han, Advances in Battery Manufacturing, Service, and Management Systems, IEEE Press/Wiley, 2016.

· J. Li and C. Pascale, ``Health Care 4.0: A vision for smart and connected health care,'' IISE transactions on healthcare systems engineering, vol. 11, no. 3, pp. 171-180, 2021.

· S. Lee, P.A. Bain, A.J. Musa, C. Baker and J. Li, ``An integrated opioid prescription optimization framework for total joint replacement surgery patients,'' IISE Transactions on Healthcare Systems Engineering, vol. 11, no. 3, pp. 209-223, 2021.

· M. Wang, H. Huang and J. Li, ``Transient analysis of multi-product Bernoulli serial lines with setups,'' IEEE Transactions on Automation Science and Engineering, vol. 18, no. 1, pp. 135-150, 2021.

· S. Lee, L. Liu, R. Radwin and J. Li, ``Machine learning in manufacturing ergonomics: recent advances, challenges, and opportunities,'' IEEE Robotics and Automation Letters, vol. 6, no. 3, pp. 5745-5752, 2021.

· W. Zhu, A. DeLonay, M. Smith, P. Carayon and J. Li, ``Reducing fall-related readmission for elderly diabetes patients in emergency departments: a transition flow model,'' IEEE Robotics and Automation Letters, vol. 6, no. 3, pp. 5642-5649, 2021.

· M. Wang, H. Huang and J. Li, ``Transients in flexible manufacturing systems with setups and batch operations: modeling, analysis, and design,'' IISE Transactions, vol. 53, no. 5, pp. 523-540, 2021.

· Y-J. Zhang, L. Liu, N. Huang, R. Rodwin and J. Li, ``From manual operation to collaborative robot assembly: an integrated model of productivity and ergonomic performance,'' IEEE Robotics and Automation Letters, vol. 6, no. 2, pp. 895-902, 2021.

· S. Lee, S. Wei, V. White, P.A. Bain, C. Baker and J. Li, ``A semi-supervised classification model for predicting opioid usage after total knee and hip replacement surgeries,'' IEEE Journal on Biomedical and Health Informatics, vol. 25, no. 1, pp. 189-200, 2021.

· S. Lee, P.A. Bain, A.J. Musa and J. Li, ``A Markov chain model of physician workflow in primary care clinics,'' Health Care Management Science, vol. 24, no. 1, pp. 72-91, 2021.

· K. Gong, H.K. Lee, K. Yu, X. Xie and J. Li, ``A prediction and interpretation framework of acute kidney injury in critical care,'' Journal of Biomedical Informatics, vol. 113, 103653, 2021.

· L. Liu, A.J. Schoen, C. Henrichs, Y. Zhang, J. Li, B. Mutlu and R. Radwin, “Human robot collaboration for enhancing work activities,” accepted, Human Factors, 2022.

· L. Liu, C.-B. Yan and J. Li, “Modeling and analysis of batch-discrete production systems: a systems approach,” IEEE Transactions on Automation Science and Engineering, vol. 24, no. 1, pp. 617-631, 2022.

· H.K. Lee, J. Li, P.A. Bain and C. Baker, “Optimal intervention policies for TJR postoperative care process,” Manufacturing & Service Operations Management, vol. 24, no. 1, pp. 617-631, 2022.

· N. Chen, N. Huang, R. Radwin and J. Li, “Analysis of Assembly-Time Performance (ATP) in Manufacturing Operations with Collaborative Robots: A Systems Approach, ” International Journal of Production Research, vol. 60, no. 1, pp. 277-296, 2022.

· Y-J. Zhang, N. Huang, R. Radwin, Z. Wang and J. Li, “Flow time in collaborative assembly systems: performance evaluation, system properties, and a case study,” IISE Transactions, vol. 54, no. 3, pp. 238-250, 2022.

· L. Liu, A.J. Schoen, C. Henrichs, Y. Zhang, J. Li, B. Mutlu and R. Radwin, “Human robot collaboration for enhancing work activities,” accepted, Human Factors, 2022.