GeorgeĀ Valkanas
Machine Learning Engineer at Apple
New York, New York, United States
Summary
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Seniorš
Top SchoolGeorge Valkanas is a Machine Learning Engineer based in NYC with 11 years of experience building production ML systems and research-driven features across startups and large tech companies, now at Apple. He has led end-to-end ML infrastructure and data-quality initiatives at Compass and delivered high-impact, efficiency-focused solutions and frameworks at Detectica that improved module performance by up to an order of magnitude. His work spans applied NLP, graph mining and valuation/analytics pipelines, and he has academic experience teaching data mining at NYU Stern and conducting postdoctoral research. An active contributor to the well-known MALLET NLP toolkit, he implemented stratified splitting and cross-validation support to strengthen model evaluation. He combines rigorous academic training (PhD in Computer Science) with practical delivery, often finishing contracts ahead of schedule and turning PoCs into long-term client relationships. Colleagues describe him as a pragmatic engineer who blends deep research instincts with production-first execution.
10 years of coding experience
13 years of employment as a software developer
Master of Science (MSc), Computer Science, 10.0 / 10.0, Master of Science (MSc), Computer Science, 10.0 / 10.0 at Aristoteleion Panepistimion ThessalonikisBachelor of Science (BSc), Computer Science, 8.01 / 10.0 ( Ranked 3rd), Bachelor of Science (BSc), Computer Science, 8.01 / 10.0 ( Ranked 3rd) at Ethnikon kai Kapodistriakon Panepistimion Athinon
Greek, English, French, Spanish
Github Skills (6)
javas10
machine-learning10
java10
cross-validation10
nlp9
unit-testing9
Programming languages (6)
Github contributions (5)
mimno/Mallet
Aug 2018 - Aug 2018
MALLET is a Java-based package for statistical natural language processing, document classification, clustering, topic modeling, information extraction, and other machine learning applications to text.
Role in this project:
ML Engineer
ML EngineerContributions:8 commits, 2 comments, 1 issue in 4 days
Contributions summary:George primarily contributed to the implementation of stratified splitting and cross-validation strategies within the MALLET library. This involved modifying the `InstanceList` class to incorporate stratified splitting, enabling more robust model evaluation. Furthermore, the user developed a `StratifiedCrossValidationIterator` to facilitate cross-validation using the new stratified split, and wrote unit tests to ensure the correctness of the new functionality.
extractionmalletlanguage-processingdata-miningsemantics
chowjl94/dm4ba_S2019
Jan 2019 - Apr 2019
Data Mining for Business Analytics class
Contributions:59 commits in 2 months
data-analyticsanalyticsminingdata-miningbusiness-analytics
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