CV

Educational Background

2016.8– 2020.6 Zhejiang University Hangzhou, China Bachelor of Science in Control Science Engineering

• Cumulative Overall GPA: 3.81/4.0
• Relevant Course: Introduction on Robotics, Computer Vision & Machine Learning, Robotics, Introduction on Artificial Intelligence, Embedded Systems 2020.9– Now Zhejiang University Hangzhou, China Ph.D. student in Control Science Engineering
• Robotics & Machine Intelligence Lab, ZJU, Supervised by Qiuguo Zhu.
• Relevant Course: Optimal Control, Artificial Intelligence, Advanced Embedded Systems, Neural Network Control

Academic Experience

RoboCup Junior International Challenge - Rescue A League (2014.7, João Pessoa, Brazil)

Challenge Competition of Natural Disaster Scene with Robot Rescuer based on line-following strategy & object searching.

• Led a team of six and won World Championship among 100+ participating teams

  X-Spider Hexapod Robot Platform Project (2018.5– 2019.7, Hangzhou, China)

  Bionic Intelligent Hexapod Robot with Multi-modal Mobility and Multi-sensors based on CPG, DNN and HMM.

• Advised by Associate Professor Kejun Zhang from college of Computer Science.
• Acted as the leader of a team of seven and was responsible for all hardware and learning.
• Won 2nd Prize in “Intel Cup” National Embedded System Design Contest.
• Won Golden Prize in “Internet+” Contest of Innovation of Zhejiang University.

  IDC Robocon 2019 of ZJU (2019.3– 2019.4, ZJU, Hangzhou, China)

  A Pair of Self-designed Mobile Robots to Finish “Trading” Tasks.

• Won 2nd place and the Best Design award among 30 participants over ZJU.
• Worked as the group leader in the team of four.
• Responsible for electrical circuit design and programming.

  Soot Parameter Analyzing System (2019.6– 2019.8, ZJU, Hangzhou, China)

  Algorithm System Based on Computer Vision for Analyzing Geometrical Parameters from Electronic Microscope Photographs of Soot Particles.

• Advised by Associated Professor Weijun Li from Department of Atmosphere Science.
• Developed CV-based soot particle processing software.
• Paper published on March 2022.

  IDC Robocon 2019 (2019.7, MIT, Boston, US)

  Two Mobile Robots to Finish “Moonshot” Tasks.

• Won 5nd place among over 60 participants from all over the world.
• Worked as the group leader in the team of five participants from different countries.
• Responsible for overall organizing, electrical circuit design and programming.

  Robotics & Machine Intelligence Lab (2018.10–Now, ZJU, Hangzhou, China)

  Research on Robot Intelligence and Motor Skills based on Deep Reinforcement Learning.

• Supervised by Qiuguo Zhu from college of Control Science and Engineering.
• Debugging of STIM-300 IMU on bipedal robot. (2019.3)
• Development and deployment of language processing system on “Jueying” quadruped robot. (2019.5)
• Locomotion generation based on deep reinforcement learning for quadruped robot. (2019.9- 2020.11)
• Backflip motion control for “Jueying Mini Lite” quadruped robot. (2020.12)
• Simulation model extracting for “Jueying” quadruped robot family. (2020.6-2021.4)
• Knowledge-based arm manipulation control for humanoids. (2021.9-2022.2)
• Multi-motion skill generation base on DRL for bipedal robot. (2021.2-Now)

Publications

1. Ren, Z., Hu, B., Wang, Z., Sun, L., & Zhu, Q. (2022). Knowledge Database-Based Multi-objective Trajectory Planning of 7-DOF Manipulator with Rapid and Continuous Response to Uncertain Fast-Flying Objects. IEEE Transactions on Robotics, DOI: 10.1109/TRO.2022.3207616.
2. Pang, Y., Wang, Y., Wang, Z., Zhang, Y., Liu, L., Kong, S., … & Li, W. (2022). Quantifying the Fractal Dimension and Morphology of Individual Atmospheric Soot Aggregates. Journal of Geophysical Research: Atmospheres, 127(5), e2021JD036055, DOI: 10.1029/2021JD036055.
3. Wang, Z., Li, A., Zheng, Y., Xie, A., Li, Z., Wu, J., & Zhu, Q. (2022). Efficient learning of robust quadruped bounding using pretrained neural networks. IET Cyber‐Systems and Robotics, DOI:10.1049/csy2.12062.
4. Wang, Z., Wei, W., Xie, A., Zhang, Y., Wu, J., & Zhu, Q. (2022). Hybrid Bipedal Locomotion Based on Reinforcement Learning and Heuristics. Micromachines, 13(10), 1688, DOI:10.3390/mi13101688.
5. Wei, W., Wang, Z., Xie, A., Xiong, R., Wu, J., & Zhu, Q. (2023). Learning Gait-conditioned Bipedal Locomotion with Motor Adaptation. 2023 IEEE-RAS 22nd International Conference on Humanoid Robots (Humanoids), DOI: 10.1109/Humanoids57100.2023.10375167.
6. Wang, Z., Wei, W., Yu, R., Wu, J., & Zhu, Q. (2024). Toward Understanding Key Estimation in Learning Robust Humanoid Locomotion. Submitted to 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Leadership Experience

Zhejiang University Robot Association (2016.10 – 2018.5)

Core member of technical department and technical leader of association

• Organized Cask Challenge of Intelligent vehicle and RoboSoccer robot competition, etc.
• Elected to be the technical leader of association between 2017.5-2018.5.
• Worked as the chief lecturer for association courses about robot system & sensors for two semesters.

  Course: Introduction on Robotics (2019.3 – 2019.6)

  Teacher’s Assistant

• Responsible for instruction of experiment and final practice examination.

Skills & Interests

• Language Skills: Native Mandarin and fluent English, TOEFL 100/120, CET6 607/720
• Computer & Programming: C/C++, Python, MATLAB, LabVIEW
• Embedded Systems: ARM(STM32F1xx, 4xx), STC(89C51), AVR(Arduino), Altera Cyclone I-IV
• Mechanical Design: SolidWorks, AutoCAD Inventor
• Circuit Design: Altium Designer
• Dynamics Simulation: RaiSim, Webots, V-rep, Pybullet, Gazebo
• Others: Microsoft Office, LaTeX
• Modeling Skills: Robotics, Embedded Systems, NLP, Reinforcement Learning and Neural Networks.