Nicholas Heller
Minneapolis, Minnesota, United States
Summary
👤
Senior🎓
Top SchoolNicholas Heller is a research scientist and PhD candidate in computer science with nine years of experience applying machine learning to medical imaging, currently embedded in the Glickman Urological and Kidney Institute at the Cleveland Clinic. He focuses on developing and evaluating visualization and segmentation tools for renal imaging, contributing to the widely used KiTS19 kidney tumor segmentation challenge by building multi-plane visualization and evaluation code. Based in Minneapolis, he bridges academic rigor from his doctoral work at the University of Minnesota with hands-on engineering to make model performance interpretable for clinicians. Nicholas combines deep technical expertise in ML pipelines with domain-focused tool development that accelerates research-to-clinic translation.
10 years of coding experience
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of Minnesota
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (11)
computer-vision10
python10
image-processing10
numpy10
scipy9
data-visualisation9
data-visualization9
data-visualizations9
segmentation7
medical-imaging7
image-segmentation7
Programming languages (8)
Github contributions (5)
neheller/kits19
Jan 2019 - Oct 2021
The official repository of the 2019 Kidney and Kidney Tumor Segmentation Challenge
Role in this project:
ML Engineer
ML EngineerContributions:58 commits, 4 PRs, 61 pushes in 2 years 10 months
Contributions summary:Nicholas primarily contributed to the development of the visualization tools for the kidney and kidney tumor segmentation challenge. They implemented a `visualize.py` script to generate image overlays of the segmentation masks and original imaging data, allowing for visual inspection of results. Further contributions included expanding the visualization capabilities to support different viewing planes, and adding evaluation code to measure the segmentation performance. These efforts are targeted towards enhancing the analysis and understanding of the model's performance.
segmentation
neheller/homepage
Nov 2017 - Feb 2023
Contributions:26 pushes in 5 years 4 months
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