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Yan-Fu Li, Yan-Fu Li


Name: Yan-Fu Li Phone: +86-10-6278-0197 E-mail: Fax: +86-10-6279-4399 Address: Room North 410, Shunde Building, Tsinghua University Homepage:


Dr. Yanfu Li is currently a full professor at IE department of Tsinghua University. He was a full professor from Jan 2016 to Aug 2016 and an assistant professor from Jan 2011 to Dec 2015, in Laboratory of Industrial Engineering at CentraleSupélec, University of Paris-Saclay, France. His current research interests include RAMS (reliability, availability, maintainability, safety) assessment and optimization with the applications onto energy systems, computing systems, transportation systems, etc. He has led/participated in several projects supported by EU, France and USA government funding bodies and enterprises. He is a co-author of over 80 publications, on international journals, conference proceedings and books. He is a senior member of IEEE and a member of INFORMS and SRA.

Please contact Prof Li with a resume for information about research positions and scholarships.

Honors and Awards

Awards of Students:

Yan-Hui Lin (2015,Defended),BUAA 100 plan award,associated professor, 2016

Awards and Recognitions:

Habilitation à diriger des Recherches (HDR) Computer Engineering, University of Lorraine, France, Dec. 2015
IEEE Senior Member,Dec. 2014
Who’s Who in the world 2014-2016, Marquis, USA    

Educational Background

National University of Singapore, Ph.D. Industrial & Systems Engineering, Aug. 2005 – Aug. 2009
Wuhan University, China, B.Eng. Software Engineering, Minor Biological Science, Sep. 2001 – Jun. 2005

Employment History

Professor, Department of Industrial Engineering, Tsinghua University, Beijing, China, Sep. 2016 – Present
Professor, Laboratory of Industrial Engineering, CentraleSupélec, University of Paris-Saclay, France, Jan. 2016 – Aug. 2016
Assistant Professor, Laboratory of Industrial Engineering CentraleSupélec, Paris, France, Jan. 2011 – Dec. 2015
Post-doc Research Associate , Department of Industrial & Information Engineering, University of Tennessee Knoxville, USA, Nov. 2009 – Oct. 2010
Research Engineer, Department of Industrial & Systems Engineering, National University of Singapore Singapore, Aug. 2009 – Nov. 2009


Doctoral Students Graduated

Elizaveta KUZNETSOVA 2014 PS2E Institute France Postdoc
Ronay AK 2014 National Institute of Standards and Technology (NIST), visiting researcher
Rodrigo MENA 2015 Politecnico di Milano, Postdoc
Yan-Hui LIN 2015 City University of HK, Postdoc(Now associate professor at BUAA)

Doctoral Students in process

Mu-Xia SUN 2017 exp CentraleSupélec, University of Paris-Saclay
Islam ABUDIN 2018 exp CentraleSupélec, University of Paris-Saclay

Master Students

Mithlesh KUMAR
Sébastien VALLA
Islam ABUDIN    

Research Interests

System Reliability, Maintenance Optimization & Asset Management, Machine Learning    

Research Projects

Development of methods for modeling degradation and maintenance of critical components and of a framework for integrating information and data of different nature EDF 2013.04-2016.03

Methods for the construction of rule-bases by automatic learning from data recorded on railway transport components and systems ALSTOM 2015.09-2016.07

Robust Scheduling of Wind Farm Power Generation Considering System Reliability Campus France 2015.01-2016.12

Development of Optimized Methods for the Reliability Prediction of Industrial Components and Systems CNRS 2013.01-2013.12

Research Network on Flexible Risk Assessment and Decision Science EU 2012.09-2016.09

Modeling and Analysis for Large-Scale Networks and Self-Improvement in LSNS NSF, USA 2009.09-2010.08


Multi-State Systems Reliability Assessment and Optimization 

  1. Y.H. Lin, Y.F. Li*, E. Zio. Reliability Assessment of Systems Subject to Dependent Degradation and Random Shock Processes. IIE Transactions. (Online). Featured article

  2. Y.H. Lin, Y.F. Li, E. Zio. A Reliability Assessment Framework for Systems With Degradation Dependency by Combining Binary Decision Diagrams and Monte Carlo Simulation. IEEE Transactions on Systems, Man, and Cybernetics: Systems. (Online)

  3. Y.H. Lin, Y.F. Li, E. Zio. 2016. Component Importance Measures for Components with Multiple Dependent Competing Degradation Processes and Subject to Maintenance. IEEE Transactions on Reliability. 65(2), 547-557.

  4. Y.H. Lin, Y.F. Li*, E. Zio. 2015. Fuzzy Reliability Assessment of Systems with Multiple Dependent Competing Degradation Processes. IEEE Transactions on Fuzzy Systems. 23(5), 1428-1438.

  5. Y.H. Lin, Y.F. Li*, E. Zio. 2015. Integrating Random Shocks into Multi-State Physics Models of Degradation Processes for Component Reliability Assessment. IEEE Transactions on Reliability. 64(1), 154-166.

  6. Y.F. Li, R. Peng. 2014. Availability modeling and optimization of dynamic multi-state series–parallel systems with random reconfiguration. Reliability Engineering & System Safety. 127, 47-57.

  7. Y.F. Li*, Y. Ding, E. Zio. 2014. Random Fuzzy Extension of the Universal Generating Function Approach for the Reliability Assessment of Multi-State Systems under Aleatory and Epistemic Uncertainties. IEEE Transactions on Reliability. 63(1), 13 - 25.

  8. Y.F. Li*, E. Zio, Y.H. Lin. 2012. A Multistate Physics Model of Component Degradation Based on Stochastic Petri Nets and Simulation. IEEE Transactions on Reliability. 61(4), 921-931.

  9. Y. Ding, E. Zio, Y.F. Li, L. Cheng, Q. W. Wu. 2012. Definition of Multi-state Weighted k-out-of-n: F Systems. International Journal of Performability Engineering. 8(2), 217-219.

Renewable Energy Systems Reliability Assessment and Optimization 

  1. H.D. Mo, Y.F. Li*, E. Zio. A System-of-Systems Framework for the Reliability Analysis of Distributed Generation System Accounting for the Impact of Degraded Communication Networks. Applied Energy (Accepted).

  2. Y.F. Li*, E. Zio. 2012. A Multi-State Model for the Reliability Assessment of a Distributed Generation System via Universal Generating Function. Reliability Engineering & Systems Safety. 106, 28–36.

  3. Y.F. Li*, S. Valla, E. Zio. 2015. Reliability Assessment of Generic Geared Wind Turbines by GTST-MLD Model and Monte Carlo Simulation. Renewable Energy. 83, 222-233.

  4. Z. Yang, Y.X. Chen, Y.F. Li, E. Zio, R. Kang. 2014. Smart Electricity Meter Reliability Prediction based on Accelerated Degradation Testing and Modeling. International Journal of Electrical Power & Energy Systems. 56, 209-219.

  5. Y.F. Li*, E. Zio. 2012. Uncertainty Analysis of the Adequacy Assessment Model of a Distributed Generation System. Renewable Energy. 41, 235-244.

  6. R. Mena, M. Hennebel, Y.F. Li, E. Zio. 2016. A multi-objective optimization framework for risk-controlled integration of renewable generation into electric power systems. Energy. 106, 712-727.

  7. R. Rocchetta, Y.F. Li*, E. Zio. 2015. Risk Assessment and Risk-Cost Optimization of Distributed Power Generation Systems Considering Extreme Weather Conditions. Reliability Engineering & System Safety. 136, 47-61.

  8. R. Mena, M. Hennebel, Y.F. Li, C. Ruiz, E. Zio. 2014. A Risk-Based Simulation and Multi-Objective Optimization Framework for the Integration of Distributed Renewable Generation and Storage. Renewable & Sustainable Energy Reviews. 37, 778-793.

  9. R. Mena, M. Hennebel, Y.F. Li, E. Zio. 2014. A self-adaptable hierarchical clustering differential evolution for optimal integration of renewable distributed generation. Applied Energy. 133, 388-402.

  10. E. Kuznetsova, Y.F. Li, C. Ruiz, E. Zio. 2014. An integrated framework of agent-based modelling and robust optimization for microgrid energy management. Applied Energy. 129, 70 – 88.

  11. E. Kuznetsova, C. Ruiz, Y.F. Li, E. Zio. 2015. Analysis of robust optimization for decentralized microgrid energy management under uncertainty. International Journal of Electrical Power and Energy Systems. 64, 815-832.

  12. Y.F. Li*, N. Pedroni, E. Zio. 2013. A Memetic Evolutionary Multi-Objective Optimization Method for Environmental Power Unit Commitment. IEEE Transactions on Power Systems. 28(3), 2660 – 2669.

  13. E. Kuznetsova, Y.F. Li, C.R. Mora, E. Zio, G. Ault, K. Bell. 2013. Reinforcement learning for microgrid energy management. Energy. 59, 133–146.

  14. Y.F. Li*, G. Sansavini, E. Zio. 2013. Non-Dominated Sorting Binary Differential Evolution for the Multi-Objective Optimization of Cascading Failures Protection in Complex Networks. Reliability Engineering & System Safety. 111, 195–205.

Software/Computing System Reliability Assessment and Optimization 

  1. Y.F. Li, R. Peng. 2015. Service Reliability Modeling of Distributed Computing Systems with Virus Epidemics. Applied Mathematical Modelling. 39(18), 5681-5692.

  2. R. Peng, Y.F. Li*, J.G. Zhang, X. Li. 2015. A risk-reduction approach for optimal software release time determination with the delay penalty cost. International Journal of Systems Science. 46(9), 1628-1637.

  3. C.T. Lin, Y.F. Li*. 2014. Rate-Based Queueing Simulation Model of Open Source Software Debugging Activities. IEEE Transactions on Software Engineering. 40(11), 1075 – 1099.

  4. Y.S. Dai, Y.P. Xiang, Y.F. Li, L.D. Xing. 2011. Consequence Oriented Self-Healing and Autonomous Diagnosis for Highly Reliable Systems and Software. IEEE Transactions on Reliability. 60(2), 369 – 380.

  5. X. Li, Y.F. Li, M. Xie, S.H. Ng. 2011. Reliability analysis and optimal version-updating for open source software. Information and Software Technology. 53(9), 929-936.

  6. R. Peng, Y.F. Li, W.J. Zhang, Q.P. Hu. 2014. Testing effort dependent software reliability model for imperfect debugging process considering both detection and correction. Reliability Engineering & System Safety 126, 37–43.

  7. Y.F. Li*, S.H. Ng, M. Xie, T.N. Goh. 2010. A Systematic Comparison of Metamodeling Techniques for Simulation Optimization in Decision Support Systems. Applied Soft Computing. 10, 1257-1273.

Machine Learning Methods with Applications 

  1. J.L. Huang, Y.F. Li, M. Xie. 2015. An empirical analysis of data preprocessing for machine learning-based software cost estimation. Information and Software Technology. 67(c), 108-127.

  2. R. Ak, Y.F. Li., V. Vitelli, E. Zio, E. L. Droguettc, C. M. C. Jacintod. 2013. NSGA-II-Trained Neural Network Approach to the Estimation of Prediction Intervals of Scale Deposition Rate in Oil & Gas Equipment. Expert Systems with Applications. 40(4), 1205-1212.

  3. Y.F. Li*, M. Xie, T.N. Goh. 2010. Adaptive ridge regression system for software cost estimating on multi-collinear datasets. Journal of Systems and Software. 83(11), 2332-2343.

  4. Y.F. Li*, M. Xie, T.N. Goh. 2009. A Study of the Non-linear Adjustment for Analogy Based Software Cost Estimation. Empirical Software Engineering. 14(6), 603-643.

  5. Y.F. Li*, M. Xie, T.N. Goh. 2009. A Study of Mutual Information Based Feature Selection for Case Based Reasoning in Software Cost Estimation. Expert Systems with Applications. 36(3), 5921-5931.

  6. Y.F. Li*, M. Xie, T.N. Goh. 2009. A Study of Project Selection and Feature Weighting for Analogy Based Software Cost Estimation. Journal of Systems and Software. 82(2), 241-252. (Best Student Paper Award, IEEE TMC, Singapore Chapter)


  1. Y.F. Li, E. Zio. 2017. RAMS Optimization Principles, in Handbook of Safety Principles. ed. Niklas Moller, Sven Ove Hansson, Jan-Erik Holmberg, Carl Rollenhagen. John Wiley & Sons, NJ, USA.

  2. Y.F. Li, E. Zio, Y.H. Lin. 2012. Methods of Solutions of Inhomogeneous Continuous Time Markov Chains for Degradation Process Modeling, Applied Reliability Engineering and Risk Analysis. Probabilistic Models and Statistical Inference. Dedicated to the Centennial of the birth of Boris Gnedenko, renowned Russian mathematician and reliability theorist. ed. Alex Karagrigoriou, Anatoly Lisnianski, Andre Kleyner, Ilia Frenkel. Wiley.

  3. C.J. Xiong, Y.F. Li, M. Xie, S.H. Ng, T.N. Goh. 2009. Service Reliability and Availability Analysis of Distributed Software Systems Considering Malware Attack, in Advances in Software Engineering, vol. 36 of Communications in Computer and Information Science. Springer Berlin Heidelberg. Page: 313-320. ISSN: 1865-0929.

  4. Y.F. Li, J. Liu. 2005 Predicting Subcellular Localization of Proteins Using Support Vector Machine with N-Terminal Amino Composition. in Advanced Data Mining and Applications, vol. 3584 of Lecture Notes in Computer Science. Springer Berlin Heidelberg, Page: 618-625. ISSN: 0302-9743.

Many conference papers


Department of Industrial Engineering, Tsinghua University
Phone: 010-62772989
Address:Shunde Building, Tsinghua University, Beijing 100084

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