Leif Jonsson
Expert ML & AI at Ericsson
Stockholm, Stockholm County, Sweden
Summary
👤
Senior🎓
Top SchoolLeif Jonsson is an expert ML & AI engineer with 13+ years of experience at Ericsson, combining deep telecom systems knowledge (Bluetooth, MMS, IMS, WCDMA RBS) with hands-on machine learning research as an industrial PhD at Linköping University. He has moved between research and product delivery, designing high-throughput C++ streaming services, contributing to standards and patents, and leading teams in presence/group management and quality assurance. More recently he has focused on machine learning and analytics platforms, bringing production-aware ML practices to telecom-grade systems. An active coder and open-source contributor, he has improved Java data-frame tooling (Joinery) and still enjoys writing Perl scripts for fun. Uncommonly, his background spans technical psychology and criminal psychology studies, which informs a pragmatic, human-centered approach to system design.
13 years of coding experience
24 years of employment as a software developer
Criminal Psychology, Criminal Psychology at Kristianstad UniversityM.Sc, Computer Science, M.Sc, Computer Science at Uppsala UniversityDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Linköping UniversitySpace Engeneering, Space Engeneering at Umeå UniversityPsychology: Anger and Aggression, Psychology: Anger and Aggression at Växjö University
Stackoverflow
1reputation
871reached
2answers
2questions
Github Skills (17)
dataframes10
java10
data-structure10
dataframe10
javas10
data-structures10
csv10
data-analysis10
eclipse6
nlp6
classloading6
spring-boot6
machine-learning6
spring6
document-classification6
Programming languages (9)
Github contributions (5)
cardillo/joinery
Feb 2015 - Nov 2015
Data frames for Java
Role in this project:
Back-end Developer
Back-end DeveloperContributions:35 commits, 6 PRs in 8 months
Contributions summary:Leif primarily contributed to the Joinery data frame library by implementing new features and improving existing ones. Their work included adding documentation for the `explode` method, enhancing the `join` method with improved error messages, incorporating new date formats, and refining the `toString` method with column padding and CSV separator flexibility. Furthermore, they added methods to export a DataFrame as an array of doubles and addressed a bug related to tab handling.
data-framesjavadata-framedataframe-libraryjoinery
lejon/PartiallyCollapsedLDA
May 2015 - Nov 2022
Implementations of various fast parallelized samplers for LDA, including Partially Collapsed LDA, Light LDA, Partially Collapsed Light LDA and a very efficient Polya-Urn LDA
Contributions:43 releases, 566 commits, 7 PRs in 7 years 6 months
implementationssamplersldalightmachinelearning
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