Filip Krikava is an Associate Professor and seasoned software engineer with 15 years of experience bridging academic research and production systems in Prague. His work spans distributed systems, model-driven engineering, and language tooling—evidenced by contributions to scalameta improving SemanticDB semantics and to macOS window manager ShiftIt. He has led teams and platforms at TomTom and built IoT and big-data analytics at Oracle, then moved into research roles including postdocs in France and the U.S. and a faculty role at Czech Technical University. More recently he implemented a high-throughput, low-latency streaming pipeline in Rust for Lacework, showing a continued focus on performance-critical systems. He brings a rare mix of compiler-level insight, practical systems engineering, and teaching experience, with a PhD grounding his work in formal methods and adaptive distributed software.
15 years of coding experience
12 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Doctor of Philosophy (Ph.D.) at Université de Nice-Sophia Antipolis
Master's Degree, Master's Degree at České vysoké učení technické v Praze
Contributions:3 releases, 128 commits, 17 PRs in 9 years 5 months
Contributions summary:Filip contributed to the `ShiftIt` project, which manages window size and position on macOS, by fixing issues related to resizing and moving windows. The commits reveal code modifications within the `AXWindowDriver.m` file, showcasing interactions with the Accessibility API and window management functionalities. The user's changes also involved code formatting and the addition of definitions.
Library to read, analyze, transform and generate Scala programs
Role in this project:
Back-end Developer
Contributions:6 commits, 1 PR, 11 comments in 10 months
Contributions summary:Filip made several contributions to the `scalameta/scalameta` repository, primarily focused on enhancing the SemanticDB functionality for the Scala compiler. Their work involved refining how the compiler handles synthetic arguments and implicit views within the semantic analysis phase. This includes modifications to accurately reflect the structure of for-comprehensions, including the addition of `foreach`, and fixing the missing symbol occurrences in certain scenarios to improve the accuracy of code analysis.
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