Jian Liu
Engineering 221
Dr. Jian Liuis an associate professor in the Department of Systems and Industrial Engineering at the University of Arizona and an affiliated faculty member in the Graduate Interdisciplinary Degree Program at The University of Arizona. He received BS and MS degrees in precision instruments and mechanology from the Tsinghua University, China in 1999 and 2002, respectively; an MS degree in industrial engineering, an MS degree in statistics and a PhD in mechanical engineering and industrial and operation engineering, all from the University of Michigan in 2005, 2006 and 2008, respectively.
Dr. Liu has more than ten years of research experience in data analytics and system informatics. His research specialty is in the fusion of multi-source, multi-scale and multi-level information in hierarchical and distributed systems for better system design, operation, and maintenance. By integrating engineering knowledge, optimization algorithms and the statistical analysis and learning of massive high-dimensional data, Dr. Liu and his research team advance the scientific research in system performance modeling, system prognostic/diagnostic, decision-making and risk management. These methodological advancements have been successfully applied in a variety of domains, such as manufacturing engineering systems, chemical and civil engineering systems and geographical information systems. His collaborations with domain experts have resulted in joint research projects in quality and reliability improvement for machining/assembly processes, mono-crystalline processes, and service improvement for water systems, software systems, and food assistance provision systems. Dr. Liu and his research team have published research papers in prestigious journals and conference proceedings, such as IISE-Transactions, IEEE Transactions, ASME Transactions and IISE annual conference proceedings. Dr. Liu’s research has been funded by US National Science Foundation, US Department of Homeland Security and US Air Force Office of Scientific Research.
Dr. Liu is a member of INFORMS and a member of IISE. He served as a council member of Quality, Statistics and Reliability Section of INFORMS from 2012 to 2014, a board director of the Quality Control and Reliability Engineering (QCRE) Division of IISE from 2013 to 2015, the president-elect of QCRE from 2015 to 2016. Dr. Liu is currently the president of the QCRE of IISE.
Degrees
- PhD Industrial and Operations Engineering and Mechanical Engineering
- The University of Michigan, Ann Arbor, Michigan, United States
- MS Statistics
- The University of Michigan, Ann Arbor, Michigan, United States
- MS Industrial and Operations Engineering
- The University of Michigan, Ann Arbor, Michigan, United States
- MS Mechanical Engineering
- Tsinghua University, Beijing, Beijing, China
- BS Precision Instruments & Mechanology
- Tsinghua University, Beijing, Beijing, China
Work Experience
- Department of Systems and Industrial Engineering, The University of Arizona (2014 - Ongoing)
- Statistics Graduate Interdisciplinary Degree Programs (2010 - Ongoing)
- Department of Systems and Industrial Engineering, The University of Arizona (2008 - 2014)
Interests
Teaching
Engineering statistics; quality engineering; applied multivariate statistics; design of experiment; reliability engineering
Research
Data analytics; statistical quality control; system reliability modeling and analysis; manufacturing process improvement; machine learning and image processing
Selected Publications
Journals/Publications
- Frantziskonis, G. N., Liu, J., Zhang, Y., & Nikravesh, Y. (2022). A partition and microstructure based method applicable to large-scale topology optimization. Mechanics of Materials, 166(104234), 104234.
- Liu, J., Son, Y., & Yuan, Y. (2022). Bayesian Modeling of Crowd Dynamics by Aggregating Multiresolution Observations From UAVs and UGVs. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 52(10), 6406-6417. doi:10.1109/tsmc.2022.3146455
- Wang, C., Liu, J., Yang, Q., Hu, Q., & Yu, D. (2022). Recoverability effects on reliability assessment for accelerated degradation testing. IISE Transactions, 1-13. doi:10.1080/24725854.2022.2089784
- Baldwin, E., Han, J., Luo, W., Zhou, J., An, L., Liu, J., Zhang, H. H., & Li, H. (2020). On fusion methods for knowledge discovery from multi-omics datasets. Computational and structural biotechnology journal, 18, 509-517.
- Baldwin, E., Han, J., Luo, W., Zhou, J., An, L., Liu, J., Zhang, H., & Li, H. (2020). On fusion methods for knowledge discovery from multi-omics datasets. Computational and structural biotechnology journal, 18, 509–517. doi:https://doi.org/10.1016/j.csbj.2020.02.011
- Li, Z., Yu, D., Liu, J., & Hu, Q. (2020). Higher-order normal approximation approach for highly reliable system assessment. IISE Transactions, 52(5), 555-567.
- Crist, J., Heasley, B., Lacasse, C., Martin-Plank, L., Phillips, L. R., & Liu, J. (2019). CREATING A PORTAL PLUS. Innovation in Aging, 3(Supplement_1), S598-S598. doi:10.1093/geroni/igz038.2221
- Minaeian, S., Liu, J., & Son, Y. (2018). Effective and Efficient Detection of Moving Targets From a UAV's Camera. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 19(2), 497-506.
- Liu, J., Han, J., & Li, M. (2017). Bayesian nonparametric modeling of heterogeneous time-to-event data with an unknown number of sub-populations. IISE Transactions, 49(5), 481-492. doi:10.1080/0740817x.2016.1234732
- Li, M., & Liu, J. (2016). Bayesian hazard modeling based on lifetime data with latent heterogeneity. RELIABILITY ENGINEERING & SYSTEM SAFETY, 145, 183-189.
- Minaeian, S., Liu, J., & Son, Y. (2016). Vision-Based Target Detection and Localization via a Team of Cooperative UAV and UGVs. IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 46(7), 1005-1016.
- Wang, L., Hu, Q., & Liu, J. (2016). Software reliability growth modeling and analysis with dual fault detection and correction processes. IIE TRANSACTIONS, 48(4), 359-370.
- Jung, D., Kang, D., Liu, J., & Lansey, K. (2015). Improving the rapidity of responses to pipe burst in water distribution systems: a comparison of statistical process control methods. JOURNAL OF HYDROINFORMATICS, 17(2), 307-328.
- Kim, B. U., Goodman, D., Li, M., Liu, J., & Li, J. (2015). Improved Reliability-Based Decision Support Methodology Applicable in System-Level Failure Diagnosis and Prognosis (vol 50, pg 2630, 2014). IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 51(3), 2519-2524.
- Mingyang, L. i., Liu, J., Jing, L. i., & Kim, B. U. (2014). Bayesian modeling of multi-state hierarchical systems with multi-level information aggregation. Reliability Engineering and System Safety, 124, 158-164.
Proceedings Publications
- Pan, F., Zhang, Y., Head, L., Liu, J., Elli, M., & Alvarez, I. (2022, December). Quantifying Error Propagation in Multi-Stage Perception System of Autonomous Vehicles via Physics-Based Simulation. In 2022 Winter Simulation Conference.
- Zhang, Y., Liu, J., Lansey, K. E., Lansey, K. E., Zhang, Y., & Liu, J. (2020, December). Detecting Burst in Water Distribution System via Penalized Functional Decomposition. In IEEE International Conference on Industrial Engineering and Engineering Management, 205-209.
- Phillips, L. R., Beverly, H., Zhang, Y., May, J., Lacasse, C. L., Martin Plank, L. M., Liu, J., Jessica, P., Loque, K., Peterson, R., Shea, K. D., & Crist, J. D. (2019, Fall). Sensor Technology: Mexican American Caregiving Families. In Council for the Advancement of Nursing Science.
- Phillips, L. R., Liu, J., Beverly, H., Martin Plank, L. M., Lacasse, C. L., Rachel, P., Crist, J. D., & Shea, K. D. (2019, November). Symposium The Tipping Point Study, Digital Detection and Decision Support for Older Adults and Families. In Gerontological Society of America.
Poster Presentations
- Liu, J., Son, Y., Yuan, Y., Minaeian, S., & Lee, S. (2017, September). DDDAMS-based Border Surveillance and Crowd Control via Aerostats, UAVs, and Ground Sensors. InfoSymbiotic:DDDAS17. University of Arizona.
Awards
- Honorable Mention for the Best Paper in the 2020 IISE Transactions Focus Issue on Quality and Reliability Engineering
- Institute of Systems and Industrial Engineering, Spring 2021
- Honorable Mention for the Best Paper Award
- International Conference on Industrial Engineering and Engineering Management, 2020, Fall 2020
- Outstanding Associate Editor Award
- Journal of Manufacturing Systems, Transactions of Society of Manufacturing Engineering, Spring 2019