About me

I'm a 5th year Ph.D candidate at Ohio State University advised by Professor Han-Wei Shen. I enjoy creating tech used in delightful experiences for 3D AI. My strengths are in 3D neural representations and their applications for 3D capture and 3D generation.

In my free time, I love: 🎾 playing tennis 🚴🏻 riding my bike 🚀 flying my FPV drones 🚗 playing Rocket League 🌲 the redwoods

What I'm doing

  • OSU

    Ph.D. Candidate

    In my final semester, concluding my thesis on adaptive neural models for large-scale scientific data representation.

  • Adobe icon

    Applied Researcher - Substance 3D

    In Jan 2025, I'll be joining Adobe as an Applied Researcher in the Substance 3D team. I'll be working on integrating 3D AI/ML research with Adobe software on the Tech Transfer Team.

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BibTeX

Publications

  1. T. Xiong, S.W. Wurster, H. Guo, T. Peterka, H.-W. Shen, "Regularized Multi-Decoder Ensemble for an Error-Aware Scene Representation Network," in Proc. IEEE Visualization, 2024.

  2. S. W. Wurster, R. Zhang, C. Zheng, "Gabor Splatting for High-Quality Gigapixel Image Representations," in Proc. ACM SIGGRAPH 2024 Posters, 2024.

  3. S. W. Wurster, T. Xiong, H. -W. Shen, H. Guo and T. Peterka, "Adaptively Placed Multi-Grid Scene Representation Networks for Large-Scale Data Visualization," in IEEE Transactions on Visualization and Computer Graphics, vol. 30, no. 1, pp. 965-974, Jan. 2024.

  4. S. W. Wurster, H. Guo, T. Peterka and H. -W. Shen, "Neural Stream Functions," 2023 IEEE 16th Pacific Visualization Symposium (PacificVis), Seoul, Korea, Republic of, 2023, pp. 132-141.

  5. S. W. Wurster, H. Guo, H. -W. Shen, T. Peterka and J. Xu, "Deep Hierarchical Super Resolution for Scientific Data," in IEEE Transactions on Visualization and Computer Graphics, vol. 29, no. 12, pp. 5483-5495, Dec. 2023.

  6. J. Xu, H. Guo, H. -W. Shen, M. Raj, S. W. Wurster and T. Peterka, "Reinforcement Learning for Load-Balanced Parallel Particle Tracing," in IEEE Transactions on Visualization and Computer Graphics, vol. 29, no. 6, pp. 3052-3066, 1 June 2023.

  7. Shi, N., Xu, J., Wurster, S. W., Guo, H., Woodring, J., Van Roekel, L. P., & Shen, H. W. (2022). GNN-Surrogate: A Hierarchical and Adaptive Graph Neural Network for Parameter Space Exploration of Unstructured-Mesh Ocean Simulations. IEEE transactions on visualization and computer graphics, 28(6), 2301-2313.

  8. Paul Hyunjin Kim, Jacob Grove, Skylar Wurster, and Roger Crawfis. 2019. Design-centric maze generation. In Proceedings of the 14th International Conference on the Foundations of Digital Games (FDG '19). Association for Computing Machinery, New York, NY, USA, Article 83, 1-9.

  9. Kevin J. Bruggeman and Skylar W. Wurster. 2018. The Hiatus system: virtual healing spaces: low dose mindfulness based stress reduction virtual reality application. In ACM SIGGRAPH 2018 Appy Hour (SIGGRAPH '18). Association for Computing Machinery, New York, NY, USA, Article 8, 1-2.

Education

  1. Ph.D. - The Ohio State University

    2019 — 2024

    Ph.D. Degree with Professor Han-Wei Shen as my advisor within the GRAVITY group.

  2. B.S. - The Ohio State University

    2015 — 2019

    B.S degree with a focus in Computer Graphics.

Experience

  1. AI/ML Research Intern, Substance 3D - Adobe

    May 2024 — Aug 2024

    Integrating AI/ML research with Adobe software.

  2. Graphics Research Intern - Tencent Pixel Lab

    May 2023 — Aug 2023

    Research toward a periodic kernel as a primitive for splatting for efficient scene reconstruction.

  3. Graduate Research Assistant - Ohio State University

    Aug 2020 — Dec 2024

    Designed adaptive neural models for efficient parameter use on large-scale scientific visualization problems.

  4. Graduate Research Aide - Argonne National Lab

    May 2020 — Aug 2020, May 2021 — Aug 2021, May 2022 — Aug 2022

    Developed hierarchical super resolution and neural stream surface solutions.

My skills

  • Python, PyTorch, CUDA, Pybind
    80%
  • Volume Rendering, NeRF, Gaussian Splatting, Rendering Pipeline, 3D reconstruction
    70%
  • Generative AI - Stable Diffusion, GANs
    60%
  • LLMs - Transformers, LLAMA
    40%

Contact

Currently located in San Francisco if you'd like to meet in person. Otherwise, feel free to email, text, or shoot me a message on any of the platforms linked in the sidebar.