Markus Borg
Adjunct Associate Professor
Malmo, Skåne County, Sweden
Summary
👤
Senior🎓
Top SchoolMarkus Borg is an experienced software engineering researcher and educator with 12 years of industry and academic experience, currently serving as Principal Researcher at CodeScene and Adjunct Associate Professor at Lund University. He leads research bridging software engineering intelligence, AI/ML testing, and MLOps while managing university collaborations and supervising PhD students. His background spans applied research with industry partners (Sony Mobile, Ericsson, ABB), safety-critical embedded development, and research programs like ITEA3 TESTOMAT. Markus combines hands-on engineering roots—from IDE and C/C++ work at ABB to test automation—with a strong publication and teaching record in requirements engineering and software testing. Based in Malmö, he is known for translating academic insights into practical decision support for software evolution and test effectiveness. A less obvious strength is his long-standing focus on making ML verification and validation tractable for real-world, component-based systems.
12 years of coding experience
10 years of employment as a software developer
Computer Engineering, Computer Engineering at Technische Universität Hamburg-HarburgNorth Carolina State UniversityUniversity Certificate, Computer science, University Certificate, Computer science at Malmö UniversityMaster of Science in Computer Science and Engineering, Software development, Master of Science in Computer Science and Engineering, Software development at Lund UniversityGerman, German at Sapientia International
Swedish, English, German
Stackoverflow
3reputation
649reached
1answer
2questions
Github Skills (54)
fitness10
pattern-recognition10
quality-assurance10
squash10
android-open-source9
machine-learning9
kotlin8
android8
java8
git8
algorithm8
oms6
soundpool6
xml6
parsing6
Programming languages (7)
Github contributions (5)
RI-SE/smirk
Dec 2020 - Dec 2022
SMIRK is an experimental pedestrian emergency breaking ADAS facilitating research on quality assurance of critical components that rely on machine learning.
Contributions:2 reviews, 498 commits, 8 PRs in 2 years
criticalemergencypedestrianmachine-learningadas
mrksbrg/adas-pro-sivic
Sep 2019 - Oct 2020
Contributions:135 commits, 100 pushes in 1 year 1 month
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