Profile

Lukas Döllerer

M.Sc. Student @TUM • Software Engineer

About Me

I'm a master's student @TUM studying Informatics and a software engineer with over 5 years of professional experience in web- and backend development. I specialize in the building of high performance compilers and runtime systems for programming languages. Currently focused on high speed execution of WebAssembly and an alternative Django webserver runtime.

Experience

Student Researcher

TUM Chair for Database SystemsApril 2025 - September 2025

    Software Developer in R&D

    Rohde & Schwarz GmbH & Co. KGFebruary 2023 - March 2025

    • Developed C++ libraries to enable high-speed communication between system components of signal analyzers
    • Implemented diverse communication protocols, including TCP, HTTP, MQTT, ZMQ, and shared memory

    Software Developer for Internal Services

    CHECK24 Services GmbHApril 2021 - Januar 2023

    Developed and deployed multiple Python Django web services, integrated with JavaScript frontends for HR

    Software Developer for Internal Services

    IfTA Systems GmbHJune 2020 - October 2021

    Engineered a web-based time tracking system for HR, streamlining employee productivity management

    Projects

    WebAssembly Standalone RuntimeApril 2024 - Present

    • Created a fully spec-compliant runtime featuring AOT & JIT compilation using LLVM
    • Conducted research on efficient bounds checking, leading to a paper published at the VMIL 2024 conference

    RustLLVMWebAssembly

    A Universal Serialization Framework for C++February 2023 - December 2023

    • Invented an automated (de-)serialization system using template metaprogramming for generic C++ objects
    • Designed an extendable framework with support for multiple serialization formats
    • Implemented support for JSON, MessagePack, Protobuf, Thrift, and FlatBuffers protocols

    C++Template MetaprogrammingJSONMessagePackProtobufThriftFlatBuffers
    Efficient Point Cloud Streaming for EDGAR TUM Self-Driving Car  preview

    Efficient Point Cloud Streaming for EDGAR TUM Self-Driving Car January 2025 - Present

    • Developed efficient pointcloud compression techniques for autonomous driving vehicles
    • Created solutions for HD map updates with optimized data streaming

    Google DracoCompressionAutonomous DrivingHD Maps

    Static Binary Translation from RISC-V to x86_64April 2021 - October 2021

    • Developed a static binary translator to convert RISC-V binaries to x86_64
    • Achieved faster performance than dynamic binary translators like QEMU

    C++RISC-Vx86_64Binary TranslationQEMU