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Peer-Reviewed Journal Papers Heading link

  1. Abu-Mualla, M., & Huang, J. (2023). Inverse Design of 3D Cellular Materials with Physics-Guided Machine Learning. Materials & Design, 112103.
  2. Rastegarzadeh, S., Wang, J., & Huang, J. (2023). Implicitly Represented Architected Materials for Multi‐Scale Design and High‐Resolution Additive Manufacturing. Advanced Materials Technologies, 2300274.
  3. Rastegarzadeh, Sina, Jun Wang, and Jida Huang. 2022. “Two-Scale Topology Optimization with Isotropic and Orthotropic Microstructures” Designs 6, no. 5: 73. https://doi.org/10.3390/designs6050073
  4. Wang, Jun, and Jida Huang. “Functionally Graded Non-Periodic Cellular Structure Design and Optimization.” Journal of Computing and Information Science in Engineering (2021): 1-10.
  5. Joyee, Erina Baynojir, Jida Huang, Ketki Mahadeo Lichade, and Yayue Pan. “Multi-material distribution planning for additive manufacturing of biomimetic structures.” Rapid Prototyping Journal, 2021.
  6. Saini, Devansh, Quintin L. Williams Jr, Lee Alkureishi, Pravin Patel, Linping Zhao, Prashant Banerjee, Jida Huang, and Mathew Mathew. “A systematic review of the latest technologies in Cranial Vault Remodeling and its outcomes for correction of craniosynostosis.” Surgery Research Journal 1, no. 2 (2021).
  7. Jida Huang, Tsz-Ho Kwok, Segmentation-based Wireframe Generation for Parametric Modeling of Human Body Shapes, ASME Journal of Computing and Information Science in Engineering, 2021
  8. Jida Huang, Luis Javier Segura, Tianjiao Wang, Guanglei Zhao, Hongyue Sun, Chi Zhou, Unsupervised learning for the droplet evolution prediction and process dynamics understanding in inkjet printing, Additive Manufacturing, Volume 35, 2020.
  9. Jida Huang, Hongyue Sun, Tsz-Ho Kwok, Chi Zhou, and Wenyao Xu. Geometric Deep Learning for Shape Correspondence in Mass Customization by Three-Dimensional Printing. ASME Journal of Manufacturing Science and Engineering 142, no. 6 (2020).
  10. Jida Huang, Tsz-Ho Kwok, Chi Zhou, Surfel convolutional neural network for support detection in additive manufacturing, International Journal of Advanced Manufacturing Technology, 2019, pp. 1-12.
  11. Jida Huang, Tsz-Ho Kwok, Chi Zhou, Parametric Design for Human Body Modeling by Wireframe-Assisted Deep Learning, Computer-Aided Design, Volume 108, 2019, pp.19-29.
  12. Binbin Zhang, Jida Huang,  Rahul Rai, Hemanth Manjunatha, A Sequential Sampling Algorithm for Multistage Static Coverage Problems, ASME  Journal of Computing and Information Science in Engineering, Volume 18, Issue 2, 021016-10, 2018.
  13. Jida Huang, Tsz-Ho Kwok, Chi Zhou, V4PCS: Volumetric 4PCS Algorithm for Global Registration. ASME  Journal of Mechanical Design, 139(11), 111403-9, 2017.
  14. Xiangzhu He, Jida Huang, Yunqing Rao, Liang Gao, Chaotic teaching-learning-based optimization with Lévy flight for global numerical optimization, Computational Intelligence and Neuroscience, Volume 2016, January 2016, Article No. 43.
  15. Xiangzhu He, Yunqing Rao, Jida HuangA novel algorithm for economic load dispatch of power systems, Neurocomputing, Volume 171, 2016, Pages 1454-1461.
  16. Wenchao Yi, Xinyu Li, Liang Gao, Yinzhi Zhou, Jida Huangε constrained differential evolution with pre-estimated comparison using gradient-based approximation for constrained optimization problems, Expert Systems with Applications, Volume 44, 2016, Pages 37-49.
  17. Jida Huang, Liang Gao, Xinyu Li, An effective teaching-learning-based cuckoo search algorithm for parameter optimization problems in structure designing and machining processes, Applied Soft Computing, Volume 36, 2015, Pages 349-356.
  18. Jida Huang, Liang Gao, Xinyu Li, A Teaching–Learning-Based Cuckoo Search for Constrained Engineering Design Problems, Advances in Global Optimization. Springer Proceedings in Mathematics & Statistics, vol 95,2015, Springer.
  19. Jida Huang, Liang Gao, Xinyu Li, A new hybrid algorithm for unconstrained optimisation problems, International Journal of Computer Applications in Technology, 46(3), 2013, pp.187-194.
  20. Liang Gao, Jida Huang, Xinyu Li, An effective cellular particle swarm optimization for parameters optimization of a multi-pass milling process, Applied Soft Computing, Volume 12, Issue 11, 2012, Pages 3490-3499.

Peer-Reviewed Conference Papers Heading link

  1. Jida Huang, Tsz-Ho Kwok, and Chi Zhou, Statistical Learning of Human Body through Feature Wireframe, 8th International Conference and Exhibition on 3D Body Scanning and Processing Technologies, 11-12 Oct. 2017, Montreal, Canada.
  2. Jida Huang, Tsz-Ho Kwok, and Chi Zhou, V4PCS: Volumetric 4PCS Algorithm for Global Registration, The ASME International Design Engineering Technical Conferences & Computers and Information in Engineering Conference IDETC/CIE 2017, August 6-9, 2017, Cleveland, Ohio.
  3. Jida Huang, Behzad Esmaeilian, Sara Behdad, Design for Ease-of-Repair: Insights From Consumers’ Repair Experiences, The ASME 2016 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference, IDETC/CIE 2016, Aug 21-24, 2016, Charlotte, North Carolina, USA
  4. Hemanth Manjunatha, Jida Huang, Binbin Zhang, Rahul Rai, A Sequential Sampling Algorithm for Multi-Stage Static Coverage Problems, The ASME 2016 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference, IDETC/CIE 2016, Aug 21-24, 2016, Charlotte, North Carolina, USA
  5. Jida Huang, Behzad Esmaeilian, Sara Behdad, Multi-Purpose Disassembly Sequence Planning, The ASME 2015 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference, IDETC/CIE 2015, Aug 2-5, Boston, MA, USA.

Poster and Presentations Heading link

  1. Annual International Solid Freeform Fabrication Symposium, “Geometric deep learning for on-demand production of customized products by additive manufacturing”, Aug. 2018, Austin, TX.
  2. Graduate Student Poster Award Presentation in ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, “Towards a Reuse-Centric Computational Paradigm for Mass Customization in Additive Manufacturing”, Aug. 2017, Cleveland, OH.
  3. ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, “Multi-Purpose Disassembly Sequence Planning”, Aug. 2015, Boston, MA.