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ORCIDLing Zhu 0001
Person information
- affiliation: Ford Motor Company, Dearborn, MI, USA
- affiliation (former): Michigan State University, East Lansing, MI, USA
Other persons with the same name
- Ling Zhu — disambiguation page
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2020 – today
- 2024
[j4]Yashesh D. Dhebar
, Kalyanmoy Deb, Subramanya Nageshrao, Ling Zhu, Dimitar P. Filev:
Toward Interpretable-AI Policies Using Evolutionary Nonlinear Decision Trees for Discrete-Action Systems. IEEE Trans. Cybern. 54(1): 50-62 (2024)- 2023
- [i3]Xunzhao Yu, Yan Wang, Ling Zhu, Dimitar P. Filev, Xin Yao:
Experience-Based Evolutionary Algorithms for Expensive Optimization. CoRR abs/2304.04166 (2023) - 2021
- [c14]Anuj Pal, Wenpeng Wei, Ling Zhu, Yan Wang, Guoming Zhu:
Dynamic System Identification for a Nonlinear Vehicle Model Using $q$-Markov Cover under Different Operational Conditions. ACC 2021: 2830-2835 - [c13]Hamed Javidi, Dan Simon, Ling Zhu, Yan Wang:
A multi-objective optimization framework for online ridesharing systems. BigComp 2021: 252-259 - [c12]Abhiroop Ghosh, Yashesh D. Dhebar, Ritam Guha, Kalyanmoy Deb, Subramanya Nageshrao, Ling Zhu, H. Eric Tseng, Dimitar P. Filev:
Interpretable AI Agent Through Nonlinear Decision Trees for Lane Change Problem. SSCI 2021: 1-8 - 2020
- [c11]Anuj Pal, Ling Zhu, Yan Wang, Guoming G. Zhu:
Multi-Objective Stochastic Bayesian Optimization for Iterative Engine Calibration. ACC 2020: 4893-4898 - [c10]Ling Zhu, Meghna Menon, Mario A. Santillo, Gregory Linkowski:
Occlusion Handling for Industrial Robots. IROS 2020: 10663-10668 - [i2]Yashesh D. Dhebar, Kalyanmoy Deb, Subramanya Nageshrao, Ling Zhu, Dimitar P. Filev:
Interpretable-AI Policies using Evolutionary Nonlinear Decision Trees for Discrete Action Systems. CoRR abs/2009.09521 (2020) - [i1]Hamed Javidi, Dan Simon, Ling Zhu, Yan Wang:
A multi-objective optimization framework for on-line ridesharing systems. CoRR abs/2012.05046 (2020)
2010 – 2019
- 2019
- [c9]Xunzhao Yu, Xin Yao, Yan Wang, Ling Zhu, Dimitar P. Filev:
Domination-Based Ordinal Regression for Expensive Multi-Objective Optimization. SSCI 2019: 2058-2065 - 2018
- [j3]Kalyanmoy Deb, Ling Zhu, Sandeep S. Kulkarni:
Handling Multiple Scenarios in Evolutionary Multiobjective Numerical Optimization. IEEE Trans. Evol. Comput. 22(6): 920-933 (2018) - [c8]Mohammad Roohitavaf, Ling Zhu, Sandeep S. Kulkarni, Subir Biswas:
NetSynth: a framework for synthesizing customized network protocols using genetic programming. GECCO (Companion) 2018: 243-244 - [c7]Mohammad Roohitavaf, Ling Zhu, Sandeep S. Kulkarni, Subir Biswas:
Synthesizing customized network protocols using genetic programming. GECCO (Companion) 2018: 1616-1623 - 2015
- [j2]Reza Hajisheykhi, Ling Zhu, Mahesh Arumugam, Murat Demirbas, Sandeep S. Kulkarni:
"Slow is Fast" for wireless sensor networks in the presence of message losses. J. Parallel Distributed Comput. 77: 41-57 (2015) - [c6]Kalyanmoy Deb, Ling Zhu, Sandeep S. Kulkarni:
Multi-scenario, multi-objective optimization using evolutionary algorithms: Initial results. CEC 2015: 1877-1884 - [c5]Ling Zhu, Sandeep S. Kulkarni:
Using Model Checking Techniques For Evaluating the Effectiveness of Evolutionary Computing in Synthesis of Distributed Fault-Tolerant Programs. GECCO 2015: 1119-1126 - [c4]Ling Zhu, Sandeep S. Kulkarni:
Using Genetic Programming to Identify Tradeoffs in Self-Stabilizing Programs: A Case Study. ICDCS Workshops 2015: 29-34 - [c3]Ling Zhu, Jingshu Chen, Sandeep S. Kulkarni:
Refinement of Probabilistic Stabilizing Programs Using Genetic Algorithms. SSS 2015: 217-232 - 2014
- [c2]Ling Zhu, Kalyanmoy Deb, Sandeep S. Kulkarni:
Multi-scenario optimization using multi-criterion methods: A case study on Byzantine agreement problem. IEEE Congress on Evolutionary Computation 2014: 2601-2608 - 2013
- [c1]Ling Zhu, Sandeep S. Kulkarni:
Synthesizing Round Based Fault-Tolerant Programs Using Genetic Programming. SSS 2013: 370-372
2000 – 2009
- 2008
- [j1]Ashrar A. Omer, Johnson P. Thomas, Ling Zhu:
Mutual authentication protocols for RFID systems. Int. J. Autom. Comput. 5(4): 348-365 (2008)
Coauthor Index
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