Yuanxiang WANG

Address
B405 Kaiwu Building, Tongji University, No. 4800 Cao'an Highway, Shanghai 201804, P. R. China

Prof. Dr. Yuanxiang Wang

  • Research Interests

      • Intelligent Control of Robotic Hands & Arms
      Human-Machine Hybrid Augmented Intelligence
      Domain-Informed Quality Control in Additive Manufacturing
      Data Science in Engineering Applications


  • Work Experience

      • 2023.11 - Present Tongji University, Research Fellow
      2022.08 - 2023.08 Anhui Chungu 3D Printing Intelligent Equipment and Industrial Technology Research Institute, Research Fellow


  • Education

      • 2017.08 - 2022.08 Ph.D. in Industrial & Systems Engineering University of Southern California (USC)


  • Honors & Awards

      • 2024 Tongji University "Outstanding" Graduate Student Mentoring Team
      2024 Tongji University Youth May Fourth Medal Collective
      2022 Awardee of Shanghai Overseas High-level Talents Plan
      2021 Best Conference Paper Award of IEEE CASE
      2021 INFORMS Bonder Foundation Award


  • Publications

      • Black: published, green: accepted, red: submitted
      [13] Xiaotian Li, Feng Chen, Yuanxiang Wang, Baoping Ma, and Qirong Tang*. Obstacle Avoidance for Guided Quadruped Robots in Complex Environments. IEEE 17th International Conference on Intelligent Robotics and Applications (ICIRA), 2024.
      [12] Xiaotian Li, Hongwei Kan, Yuanxiang Wang, Baoping Ma, and Qirong Tang*. Multi-sensor Fusion Localization and Terrain Reconstruction for Guided Quadruped Robots. IEEE 17th International Conference on Intelligent Robotics and Applications (ICIRA), 2024.
      [11] Bingzheng Wang, Yuanzhe Cui, Yuanxiang Wang, and Qirong Tang*. An Automatic Weighting Decision-making Framework for Trajectory Tracking of the Overactuated UAVs Platform. IEEE 17th International Conference on Intelligent Robotics and Applications (ICIRA), 2024.
      [10] Weizhi Lin, Yuanxiang Wang, and Qiang Huang*. Automated Printing Primitive Extraction and Learning for Complexity Reduction in Additive Manufacturing Operations. IEEE 20th International Conference on Automation Science and Engineering (CASE), 2024.
      [9] Weizhi Lin, Yuanxiang Wang, and Qiang Huang*. Finite Manufacturing Primitives: A Representation Scheme for Additive Manufacturing Quality Assurance. CIRP Annals – Manufacturing Technology, 2024, in press.
      [8] Yuanxiang Wang, Cesar Ruiz, and Qiang Huang*. Learning and Predicting Shape Deviations of Smooth and Non-Smooth 3D Geometries Through Mathematical Decomposition of Additive Manufacturing. IEEE Transactions on Automation Science and Engineering, 20(3): 1527-1538, 2022.
      [7] Yuanxiang Wang and Qiang Huang*. Small-Sample Learning of 3D Printed Thin-Wall Structures Using Printing Primitives. IEEE 18th International Conference on Automation Science and Engineering (CASE), 2022.
      [6] Yuanxiang Wang, Cesar Ruiz, Sanglok Park, Kyeong-Ho Shin, Joo-Hyung Kim, and Qiang Huang*. A Shape Registration Methodology for Geometric Deviation Correction in Additive Manufacturing. ASME Manufacturing Science and Engineering Conference (MSEC), 2022.
      [5] Nathan Decker*, Mingdong Lyu, Yuanxiang Wang, and Qiang Huang. Geometric Accuracy Prediction and Improvement for Additive Manufacturing Using Triangular Mesh Shape Data. ASME Transactions, Journal of Manufacturing Science and Engineering, 143(6): 061006, 2021.
      [4] Anne-Francoise Obaton*, Yuanxiang Wang, Bryan Butsch, and Qiang Huang. A Non-Destructive Resonant Acoustic Testing and Defect Classification of Additively Manufactured Lattice Structures. Welding in the World, 65(3): 361-371, 2021.
      [3] Yuanxiang Wang, Cesar Ruiz, and Qiang Huang*. Extended Fabrication-Aware Convolution Learning Framework for Predicting 3-D Shape Deformation in Additive Manufacturing. IEEE 17th International Conference on Automation Science and Engineering (CASE), 2021.
      [2] Nathan Decker*, Yuanxiang Wang, and Qiang Huang. Efficiently Registering Scan Point Clouds of 3D Printed Parts for Shape Accuracy Assessment and Modeling. Journal of Manufacturing Systems, 56: 587-597, 2020.
      [1] Qiang Huang*, Yuanxiang Wang, Mingdong Lyu, and Weizhi Lin. Shape Deviation Generator - A Convolution Framework for Learning and Predicting 3-D Printing Shape Accuracy. IEEE Transactions on Automation Science and Engineering, 17(3): 1486-1500, 2020.