Hilaf Hasson
Senior Staff Applied Scientist at Cohesity
Mountain View, California, United States
Summary
🤩
Rockstar🎓
Top SchoolHilaf Hasson is a Senior Staff Applied Scientist based in Mountain View with six years of industry experience translating deep mathematical training into production-scale ML and GenAI systems. He has led science and productization for time-series forecasting and explainability at AWS—driving Amazon Forecast ensembling and Sagemaker Canvas features—and most recently leads R&D for enterprise GenAI at Cohesity. His background spans rigorous academic research (PhD in Mathematics) and applied ML roles, with publications and contributions that bridge theory—such as probabilistic forecasting and uncertainty quantification—and practice. As an active open-source contributor to GluonTS, he implemented tree-based probabilistic forecasters (QRX) with LightGBM integration, NaN handling and explainability, highlighting a rare combination of algorithmic depth and production-grade engineering. Colleagues describe him as a scientist who reliably converts theoretical insights into scalable, interpretable products that ship.
6 years of coding experience
7 years of employment as a software developer
High School, High School at Handesaim Tel-Aviv (The School for Practical Engineers)Bachelor of Science (BSc) Mathematics Magna Cum Laude, Bachelor of Science (BSc) Mathematics Magna Cum Laude at Tel Aviv UniversityProgram for Gifted Youth in Mathematics, Program for Gifted Youth in Mathematics at Bar-Ilan UniversityDoctor of Philosophy (PhD) Mathematics, Doctor of Philosophy (PhD) Mathematics at University of Pennsylvania
Github Skills (17)
xgboost10
python10
data-science10
machine-learning10
time-series-forecasting10
lightgbm10
forecasting9
forecast9
deep-learning8
mlops8
pytorch7
mxnet7
data-structures6
datastructures-algorithms6
algorithms6
Programming languages (1)
Github contributions (3)
awslabs/gluonts
Aug 2020 - Jan 2023
Probabilistic time series modeling in Python
Role in this project:
ML Engineer & Data Scientist
ML Engineer & Data ScientistContributions:7 reviews, 16 commits, 54 PRs in 2 years 5 months
Contributions summary:Hilaf significantly contributed to the implementation of tree-based models, specifically QRX (Level Set Forecaster), within the GluonTS framework. Their work involved integrating lightgbm for model training, introducing functionalities like random sampling and flexible parameter passing to improve QRX's capabilities and usability. Furthermore, the user added support for handling NaN values and incorporated explainability features, enhancing the model's interpretability and robustness. The user also made refactoring and code improvements, which significantly improve the robustness and usability of the project.
forecastingpythontime-series-analysistimeseries-forecastingaws
zoolhasson/gluon-ts
Feb 2020 - Aug 2023
Probabilistic time series modeling in Python
Contributions:5 PRs, 147 pushes, 5 branches in 3 years 6 months
pythontime-series-analysismachine-learningprobabilistictime-series
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