Derrick Schultz
Product Lead at NYU Tisch School of the Arts
New York, New York, United States
Summary
👤
Senior🎓
Top SchoolDerrick Schultz is a product-focused designer and educator with 14 years of experience who blends deep UX practice with hands-on machine learning exploration to ship intuitive enterprise and consumer experiences. As a Product Lead and former Principal Product Designer at Vista, he has led multi-company account systems, checkout flows, and a brand kit from concept to production while managing design teams. He teaches machine learning for creatives at institutions like NYU Tisch and through his own studio, helping artists and designers build custom datasets and models. An artist-first coder, Derrick experiments with ML art—publishing Colab notebooks for StyleGAN2 manipulations and Wasserstein style transfer—that inform his practical approach to generative UX. Based in New York, he balances studio work at BustBright with product leadership, bringing a craft-driven sensibility to technical product problems.
14 years of coding experience
12 years of employment as a software developer
BS Graphic Design, BS Graphic Design at University of CincinnatiN/A Poster Design Summer Studies, N/A Poster Design Summer Studies at Rhode Island School of Design
English
Stackoverflow
1reputation
0reached
1answer
0questions
Github Skills (9)
pytorch10
machine-learning10
jupyter-notebook10
computer-vision9
drawimage6
ibooks6
epub6
ipad6
canvas6
Programming languages (7)
Github contributions (5)
dvschultz/ml-art-colabs
Mar 2020 - Feb 2022
A list of Machine Learning Art Colabs
Role in this project:
ML Engineer
ML EngineerContributions:162 commits, 2 PRs, 159 pushes in 1 year 11 months
Contributions summary:Derrick's contributions primarily involve creating and modifying Jupyter Notebooks, likely for machine learning art generation. The commits include the creation of a notebook for "Network Bending", which manipulates StyleGAN2 models through transformations, and another notebook related to Wasserstein style transfer. The changes include installing dependencies (e.g., PyTorch, Ninja, kmeans-pytorch) and setting up the environment, which suggests the user is actively experimenting with and utilizing these tools and techniques.
artdata-sciencedeep-learningmachine-learningtensorflow
dvschultz/network-bending
Jul 2020 - Jun 2021
Manipulating the inner representations of StyleGAN2
Contributions:16 commits, 14 pushes, 1 branch in 11 months
pytorchstylegan2representations
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