Peter Izsak
Sr. Data And Applied Scientist
Haifa District, Israel
Summary
🤩
Rockstar🎓
Top SchoolPeter Izsak is a senior data and applied scientist with 13 years of experience building production-grade NLP and deep learning systems, now at Microsoft after leading research teams at Intel Labs. He combines strong Python and Java engineering skills with deep familiarity across major DL frameworks and a research grounding from Technion in computer science and information retrieval. At Intel he progressed from deep learning data scientist to staff research scientist and team lead, shipping intent-extraction and data-loading components and contributing backend implementations to the notable Intel NLP-Architect repository. Comfortable bridging research and engineering, he has a track record of turning state-of-the-art NLP topologies into scalable, maintainable code and shipping them in enterprise settings. Based in Haifa, he blends academic rigor with hands-on open-source contributions and a pragmatic focus on deployable ML.
13 years of coding experience
11 years of employment as a software developer
Master’s Degree, Master’s Degree at Technion - Israel Institute of Technology
Hungarian, English, Hebrew
Stackoverflow
1reputation
0reached
1answer
0questions
Github Skills (6)
nlp10
python10
tensorflow9
keras9
machine-learning8
data-processing7
Programming languages (4)
Github contributions (5)
IntelLabs/nlp-architect
Mar 2018 - Oct 2022
A model library for exploring state-of-the-art deep learning topologies and techniques for optimizing Natural Language Processing neural networks
Role in this project:
Backend Developer
Backend DeveloperContributions:14 releases, 13 reviews, 360 commits in 4 years 7 months
Contributions summary:Peter's commits focused on implementing and importing intent extraction models, indicating a back-end development role. The changes involved modifications to Python files, particularly within the `intent_extraction` directory, suggesting the addition or integration of new functionalities related to intent recognition within the NLP Architect framework. The user also contributed to the structure of the data loading process.
nlunatural-language-understandingbertlanguage-processingstate-of-the-art
peteriz/Indri-toolkit
Jun 2013 - Jul 2014
Contributions:5 commits, 1 comment, 1 issue in 1 year 1 month
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