王泽群 (教授)

教授 博士生导师

主要任职：机械与电气工程学院副院长

曾获荣誉：国家优秀青年科学基金（海外）获得者
生产力促进（创新发展）一等奖获得者
四川省科学进步二等奖获得者
2024年电子科技大学教学成果奖（研究生）一等奖获得者
四川省峨眉人才计划入选者

性别：男

毕业院校：威奇塔州立大学

学历：博士研究生毕业

学位：哲学博士学位

在职信息：在职人员

所在单位：机械与电气工程学院

入职时间：2022-12-01

办公地点：清水河地区

电子邮箱：

   
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  • International Journal Papers

  1. Tang, Q., Xu, T., Xu, J., Zhang, X., & Wang, Z. (2025). Confidence-driven adaptive evolutionary learning for reliability-based design optimization of nickel-based alloys. Engineering Optimization, 1–19. 

  2. Jiang, Z., Gao, S., Tang, Q., Wang, Z., Liu, Y., and Huang, H. (September 23, 2025). "Generative Reliability-Based Design Optimization Using In-Context Learning Capabilities of Large Language Models." ASME. J. Mech. Des. March 2026; 148(3): 031705. 

  3. Chen W, Deng J, Wang Z, et al. Combustion Parameter Prediction for Mining Conveyor Belts by Using Convolutional Neural Network–Long Short-term Memory[J]. Energy and AI, 2025: 100524.

  4. Jiang Z, Wang Z. Adaptive machine learning-enabled evolutionary optimization for reliability-based design of Through Silicon Via (TSV) structures under uncertainty[J]. IEEE Transactions on Components, Packaging and Manufacturing Technology, 2025.

  5. Shi L, Wang Z. High-dimensional reliability estimation of engineered structures using deep networks and adaptive hierarchical learning[J]. Engineering Structures, 2025, 340: 120657.

  6. Shi L, Pan B, Chen W,  Z Wang. Deep learning-based multifidelity surrogate modeling for high-dimensional reliability prediction[J]. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering, 2024, 10(3): 031106.

  7. Su Y, Shi L, Zhou K, G Bai， Z Wang. Knowledge-informed deep networks for robust fault diagnosis of rolling bearings[J]. Reliability Engineering & System Safety, 2024, 244: 109863.

  8. Shi L, Zhou K, Wang Z. Convolutional dimension-reduction with knowledge reasoning for reliability approximations of structures under high-dimensional spatial uncertainties[J]. Journal of Mechanical Design, 2024, 146(7): 071701.

  9. Zhou K, Wang Z, Gao Q, et al. Recent advances in uncertainty quantification in structural response characterization and system identification[J]. Probabilistic Engineering Mechanics, 2023, 74: 103507.

  10. Zhou K, Wang Z, Ni Y Q, et al. Unmanned aerial vehicle-based computer vision for structural vibration measurement and condition assessment: A concise survey[J]. Journal of Infrastructure Intelligence and Resilience, 2023, 2(2): 100031.

  11. Cao P, Zhang S, Wang Z, et al. Damage identification using piezoelectric electromechanical impedance: a brief review from a numerical framework perspective[C]//Structures. Elsevier, 2023, 50: 1906-1921.

  12. Bai G, Su Y, Rahman M M,  Z Wang. Prognostics of Lithium-Ion batteries using knowledge-constrained machine learning and Kalman filtering[J]. Reliability Engineering & System Safety, 2023, 231: 108944.

  13. Li M, Wang Z. Deep reliability learning with latent adaptation for design optimization under uncertainty[J]. Computer Methods in Applied Mechanics and Engineering, 2022, 397: 115130.

  14. Li M, Wang Z. LSTM-augmented deep networks for time-variant reliability assessment of dynamic systems[J]. Reliability Engineering & System Safety, 2022, 217: 108014.

  15. Li M, Wang Z. An LSTM-based ensemble learning approach for time-dependent reliability analysis[J]. Journal of Mechanical Design, 2021, 143(3): 031702.

Engineering Conference. Volume 11A: 46th Design Automation Conference (DAC). Virtual, Online. August 17–19, 2020. V11AT11A038. ASME.

Li M, Wang Z. Heterogeneous uncertainty quantification using Bayesian inference for simulation-based design optimization[J]. Structural Safety, 2020, 85: 101954.