First Name: Siyuan
Last Name: Yang
My web homepage[blog] and academic homepage
My github account: https://github.com/Reed-yang
Background & Interests:
3D Reconstruction, Neural Rendering, Computer Graphics, Differentiable Rendering
Degree:
Major in Computer Science at Huazhong University of Science & Technology(HUST) 2021 - 2025
Minor in Philosophy at Huazhong University of Science & Technology(HUST) 2022 - 2025
Research & Industrial Experience:
- HUST-EPIC-lab 2022.5-present
Under the guidance of Associate Professor Xianzhi Li at HUST EPIC Lab, I had the opportunity to engage in research in point cloud 3D reconstruction. This research project is scheduled for publication at CVPR 2024. My involvement encompassed coding, conducting experiments, and co-authoring the paper.
- USTC 2023.7
Participating in the “Frontiers of Computer Graphics” course at USTC in 2023 has significantly augmented my knowledge in the field. Topics ranged from MPM physics simulations to neural rendering pipelines, as well as techniques for accelerating NeRF in large-scale scenes.
- Tsinghua University 2023.8
Additionally, I had the privilege of attending the Tsinghua Graphics Rising Star Summer Camp 2023, which was a valuable experience.
Areas of Expertise:
I excel in the fields of computer graphics and graphics API, with an advanced proficiency in Deep Learning frameworks like PyTorch. I have a solid understanding and experience in the domains of Deep Learning and Computer Vision, and I possess extensive knowledge about cutting-edge work in NeRF.
Course Experience:
Due to my early interest in computer graphics in lower grades, I pursued self-study in various courses:
Repeatedly reviewed lectures, slides, and notes. Completed coding assignments and lab experiments. Prof. Lingqi Yan’s course served as my foundation in graphics. This knowledge proved vital in neural rendering and 3D reconstruction work. Concepts like ray marching in NeRF and Mip Maps in MipNeRF originated back to graphics.
Studied OpenGL to gain a deeper understanding of modern graphics APIs. This knowledge not only helped me grasp graphics computation but also facilitated my research in graphics.
Embarked on a journey into deep learning, gaining preliminary insights into deep learning engineering and contemporary computer vision techniques. Through extensive experiments and practical work in research, I honed my PyTorch skills.