Dominik Engel, Dr.

Dominik Engel joined the Visual Computing Research Group in December 2018. He completed his Ph.D. in May 2024. Prior to that He finished his M.Sc. in 2018 with a focus on Computer Vision, Computer Graphics and Deep Learning. He earned his Bachelor’s degree in 2016, also at the University of Ulm. Find newest updates on https://dominikengel.com.

Research interests

  • Deep Learning Techniques for Computer Graphics
  • Deep Learning in Volume Rendering
  • Differentiable & Neural Rendering
  • Self-Supervised Training and its Emerging Applications

Teaching

Lectures

  • Deep Learning for Graphics and Visualization [Contributed Chapter: Generative Models Chapter]
  • Deep Learning for Graphics and Visualization Summer School 2019
  • Deep Learning for Graphics and Visualization Lecture & Exercise [WT19/20, WT20/21, WT21/22]
  • 3D Deep Learning [Contributed Chapters: Automatic Differentiation, Differentiable Rendering, Neural Radiance Fields]
  • 3D Deep Learning Exercise [WT23/24]
  • Visual Computing Seminar Bachelor [ST19, WT19/20, ST20, WT20/21, ST21, WT21/22, ST22, WT22/23, ST23]
  • Visual Computing Seminar Master [ST19, WT19/20, ST20, WT20/21, ST21, WT21/22, ST22, WT23/24]

Finished Theses

  • Tushar Singhal - “Efficient Fine-Tuning of Stable Diffusion for Novel View Synthesis” (Master Thesis)
  • Michael Nix - “Recognition and Tracking of Real-World Objects in Mixed Reality Environments” (Master Thesis)
  • Luca Dubies - “Neural Audio Fields” (Master Thesis)
  • Jan Haßler - “Differentiable Rendering for Constructive Solid Geometry” (Master Thesis)
  • Niklas Trieu - “Generative Models for Order-Independent Point Clouds” (Bachelor Thesis)
  • Jannes Lehwald - “Development of a Context-Aware Simulation-Based Worker Assistance using Human Simulation Data” (Master Thesis)

Finished Projects

  • Deep Learning Dataset Generation using Mitsuba2
  • Differentiable Depth Raycasting

Open Thesis and Project Topics

As I will finish my journey here at Ulm Univeristy soon, I am no longer available for theses or projects.

Publications

Pre-Print

Peer-Reviewed