CV
Basics
Name | Yuechuan Hou |
Label | Master's Student |
yuechuanhou@gmail.com | |
Url | https://yuechuanhou.com |
Summary | A Master's student at Carnegie Mellon University with experience in Robotics and Computer Vision, currently focusing on learning-based human pose 3D reconstruction. |
Education
-
2022 - 2024 Master's Student
Caenegie Mellon University
Mechanical Engineering
- Machine Learing and Artificial Intelligence
- Visual Learning and Recognition
- Mobile Robots
-
2017 - 2021 -
2017 - 2021 Bachelor's
University of Pittsburgh
Mechanical Engineering
- Data Structures
- Algorithm Implementation
- Computer Organization and Assembly Language
Skills
Programming Languages | |
Python | |
C++ | |
Java |
Engineering Analysis | |
MATLAB | |
ANSYS |
CAD | |
SolidWorks | |
NX | |
CATIA |
Robotics and Simulation | |
ROS | |
Isaac Sim |
Projects
- 2022.10 - Present
Dense 3D Reconstruction of Dynamic Actors in Natural Environments using Multiple Flying Cameras
Research project funded by the National Science Foundation Grant No. 2024173.
- Formation Planning: Designed adaptive aerial formations for filming groups of people based on Python and ROS.
- Field Testing: Developed and executed planning and control strategies for filming moving individuals using an aerial robot equipped with GPS-based tracking.
- 3D Reconstruction: Human pose detection using OpenPose with photo-realistic simulation via Isaac Sim and progressed towards a comprehensive 3D pose reconstruction pipeline.
- 2023.01 - 2023.05
Advanced Cross-Platform Game Porting of 'Metal Slug' with C++ and OpenGL
Team project at Carnegie Mellon University.
- Game Adaptation: Transitioned 'Metal Slug' to modern platforms using C++ and OpenGL, ensuring seamless gameplay functionality.
- Game Design: Architected intricate gameplay mechanics and graphics, delivering an immersive user experience through algorithms.
- AI Integration: Engineered intelligent enemy behaviors and integrated dynamic difficulty scaling based on player performance to maintain a balanced gameplay experience.
- 2021.07 - 2022.06
Investigation of Thermal Mechanical Properties of 3D Printed Lattice Cooling Structure for Hot Section Components Using High Temperature Alloys
Research project funded by the National Natural Science Foundation of China.
- Deep Learning Modeling: Designed neural network algorithms for accurate heat transfer property predictions of varied lattice structures.
- System Optimization: Integrated genetic algorithms to optimize the heat transfer efficiency.
- Algorithm Verification: Employed nonlinear regression and sensitivity analysis, ensuring the precision and robustness of algorithms for real-world applicability.
Work
- 2019.07 - 2019.08
Intern
Siemens Smart Manufacturing and Innovation Center Chengdu
Utilized NX to address practical problems in mechanical engineering.
Languages
Chinese | |
Native speaker |
English | |
Fluent |