Dan S
Lead Software Engineer at dolaGon
New York, New York, United States
Summary
🤩
Rockstar🎓
Top SchoolDan S is a Lead Software Engineer in New York with 15 years of experience building high-performance, research-driven systems across robotics, autonomous vehicles, and scientific Python ecosystems. He blends backend systems and ML/Probabilistic programming expertise—contributing to flagship open-source projects like PyMC, TensorFlow/XLA, JAX, and Astropy—bringing practical improvements to HMC mass-matrix adaptation, KDE in JAX, and exoplanet-detection tooling. At Caterpillar he architected middleware-agnostic frameworks and HIL simulation benches for autonomous systems, and he has a track record of shipping low-level C/C++ and embedded solutions as well as visualization and tooling for validation. Comfortable leading teams (Scrum, 18 engineers) and diving into math-heavy code, he pairs strong production engineering with academic curiosity, routinely reading research and presenting findings. Currently on parental leave, he remains active in open-source and builds cross-domain bridges between robotics, probabilistic modeling, and systems engineering.
16 years of coding experience
6 years of employment as a software developer
BS - Computer Science, Computer Science, BS - Computer Science, Computer Science at NYU Tandon School of EngineeringBrooklyn Technical High School
English, Russian
Github Skills (62)
algorithm10
data-visualizations10
algorithms10
c-language10
probabilistic-programming10
mc10
python10
optimizers10
redis10
astronomy10
matplotlib10
testing10
statistics10
machine-learning10
optimizer10
Programming languages (21)
Github contributions (5)
dfm/corner.py
Sep 2012 - Sep 2022
Make some beautiful corner plots
Role in this project:
Data Scientist
Data ScientistContributions:12 releases, 4 reviews, 205 commits in 10 years 2 months
Contributions summary:Dan primarily contributed to the development of a Python library for creating corner plots. They added functionalities such as support for specifying extents, plotting truth points, and adding labels. The contributions also included adding and refining features like title annotations and adjustments to the error ellipse scaling factor, demonstrating a focus on data visualization and enhancing the library's usability for data analysis tasks.
data-analysispythondata-visualizationplottingmatplotlib
daft-dev/daft
Sep 2012 - Jul 2022
Render probabilistic graphical models using matplotlib
Role in this project:Back-end Developer
Back-end DeveloperContributions:2 releases, 1 review, 150 commits in 9 years 11 months
Contributions summary:Dan contributed significantly to the `daft-dev/daft` project, focused on rendering probabilistic graphical models. They implemented core features such as defining a PGM class, a Node class, and an Edge class, forming the fundamental building blocks for creating and visualizing graphical models. They also added functionality to include plates and edge annotations for a better visual representation of the models. The work involved modifying core classes and adding properties to existing classes.
matplotlibprobabilistic-graphical-models
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