Adam Valenta
Senior Software Enngineer at H2O.ai
Prague, Prague, Czechia
Summary
🤩
Rockstar🎓
Top SchoolAdam Valenta is a Senior Software Engineer with a decade of experience building scalable backend systems and machine learning infrastructure, currently at H2O.ai in Prague. He contributes to the flagship open-source H2O-3 platform, where his work spans core ML functionality—from implementing Extended Isolation Forests to low-level matrix utilities and Gaussian vector generators. Adam combines a strong engineering foundation from prior roles and a Data Science Ing. from FIT ČVUT with hands-on ML engineering, delivering production-grade algorithm implementations and API-consistent documentation. Colleagues rely on him for improving model performance and robustness within distributed ML pipelines. He brings a pragmatic balance of research-minded algorithmic thinking and production-focused software craftsmanship, frequently moving novel ML ideas into widely used open-source code.
10 years of coding experience
8 years of employment as a software developer
Inženýr (Ing.), Data Science, Inženýr (Ing.), Data Science at FIT ČVUT v Praze
Stackoverflow
36reputation
625reached
6answers
0questions
Github Skills (20)
algorithm10
algorithms10
machine-learning-algorithms10
java10
implement10
javas10
linear-algebra10
api-design9
data-structures8
data-structure8
h2oai6
h2o6
anaconda6
apple-m16
categorical-data6
Programming languages (5)
Github contributions (5)
h2oai/h2o-3
Dec 2019 - Jan 2023
H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
Role in this project:
Backend Developer & ML Engineer
Backend Developer & ML EngineerContributions:740 reviews, 633 commits, 475 PRs in 3 years 1 month
Contributions summary:Adam's commits focus on enhancing the H2O-3 platform by adding a new method for generating vectors from a Gaussian distribution and implementing vector-vector multiplication within the MatrixUtils class. Furthermore, the commits encompass the creation of an Extended Isolation Forest (EIF) class, including its parameters, output, and model structure, demonstrating work on a machine learning algorithm. Moreover, the user has also made some documentation updates related to the model's API to be consistent with the existing ones. The user's work revolves around the core machine learning functionality of the H2O-3 platform and enhancing the model's performance.
xgboostgampythonk-meansautoencoders
valenad1/h2o-3
Dec 2019 - May 2024
Open Source Fast Scalable Machine Learning Platform For Smarter Applications: Deep Learning, Gradient Boosting & XGBoost, Random Forest, Generalized Linear Modeling (Logistic Regression, Elastic Net), K-Means, PCA, Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
Contributions:80 pushes, 7 branches in 4 years 5 months
xgboostpythonk-meanselastic-netlightgbm
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