Julien Hoachuck
CEO at 789 Labs
San Francisco Bay Area United States
Summary
👤
Senior🎓
Top SchoolJulien Hoachuck is a founder and CEO based in the San Francisco Bay Area with 11 years of experience building machine learning and product-focused software for both startups and large tech. He led ML initiatives and incident response for Copilot and M365 Cloud Intelligence at Microsoft, then shifted to entrepreneurship, founding ArkiTask and now Notewell, a LAUNCH-backed startup focused on social services. Julien blends applied research—including work on privacy-aware facial feature removal at Stanford—with hands-on engineering across mobile, web, embedded robotics, and cloud systems. His background in mechanical engineering and computer science (UC Davis, Georgia Tech, Stanford AI coursework) gives him a systems-level perspective that helps translate complex ML research into production-ready products. An operator who codes, he has a track record of shipping end-to-end solutions from embedded robotics to large-scale cloud ML.
11 years of coding experience
11 years of employment as a software developer
Mechanical Engineering, Mechanical Engineering at University of California, Berkeley ExtensionHong Kong University of Science and Technology (HKUST)B.S. Double Major: Mechanical Engineer & Computer Science, B.S. Double Major: Mechanical Engineer & Computer Science at University of California, DavisMaster of Science - MS Computer Science, Master of Science - MS Computer Science at Georgia Institute of TechnologyArtificial Intelligence Graduate Studies Certificate Computer Science, Artificial Intelligence Graduate Studies Certificate Computer Science at Stanford University
Github Skills (37)
clustering-algorithm10
hdbscan10
clustering-evaluation10
cluster-analysis10
clustering9
arff8
machine-learning-algorithms8
microsoft-azure8
probabilistic-graphical-models8
machine-learning7
bayesian6
deidentify6
python6
convolutional-neural-networks6
pytorch5
Programming languages (9)
Github contributions (5)
mechaman/ARFF-CNN
May 2018 - Dec 2018
Automatic Facial Feature Removal (ARFF) to de-identify MR scans via Convolutional Neural Networks
Contributions:46 commits, 8 PRs, 42 pushes in 6 months
arffconvolutional-neural-networksdeidentify
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