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Software Engineering & Data Science


  • Fullstack development

    Full-Stack Development

    Fullstack developing is exciting in many ways, one of which is that it allows me to build holistic systems from scratch and integrate different technologies. I usually start from first principles and plan the system's structure, recognizing that a well-organized foundation is a precondition for integrating functionality and thoughtful designs. Fullstack developing includes web applications, desktop software, mobile apps or industrial software.

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    • Web applications
    • Desktop software
    • Mobile apps

  • Data systems and ai

    Data Systems and AI

    In today's world data has become an integral part of most digital technologies, products and business processes. With data gaining in importance businesses increasingly rely on systems such as artificial intelligence, databases, APIs, ETL-pipelines, big data analysis, model simulation or visualizations. In the past I built prediction algorithms for the finance industry, data integrations for marketing businesses or manufacturing systems, crawling bots, recommendation and classification systems or LLMs.

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    • Data systems and AI

  • Industrial software

    Industrial Software

    Industrial software often involves automating and scaling manufacturing processes and the integration and interoperability of data streams. Industrial software is generally used in manufacturing systems, but today they are built for all kinds of industries, including logistics and transportation, accounting, banking, insurance or marketing. One of the exciting things about it is not only to automate data streams and business processes, but also to make them more intelligent by implementing AI algorithms.

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    • Industrial software

Release Notes


Bitcoin onboarding - release of a comprehensive documentation

Bitcoin is not only a highly fascinating rabbit hole, it is also a huge white pill that gives me hope for our future. In recent years I was frequently asked by friends and clients to help them implement a Bitcoin setup. Before I implemented the setup I tested the entire onboarding process on my own devices and documented the main steps. In doing so, I created a documentation that gives an overview of the main advantages of Bitcoin and discusses different risk scenarios, solutions for key storage and other security considerations. 


Release of our new weekly newsletter - no spam, just high-signal content

Our new weekly newsletter is now officially released, which delivers updates, exciting releases, special offers and valuable insights straight to your inbox. Designed for clients and tech enthusiasts, the newsletter keeps you informed not only about our products, but also about the world of tech, software, AI, data science and other related topics without spamming your inbox.


New desktop software and data management system for Signum News

Just recently I completed a desktop app for Signum News that allows us to organize our data management process at the business level. The high level functionalities of the desktop app include the management of data sources, the control and monitoring of data crawling jobs, data processing and editing as well as data quality management.


My Stack


Python

Django

JavaScript / React

Java

SQL

Microsoft Azure

Linux

Blog


Developing and simulating robot stability

Just recently I learned a new software tool that allows me to program and simulate a robot, using Python, ROS2 and Gazebo. This setup can be used not only to code the software for a real world robot, but also to simulate the behavior of the robot, its physics and environment. 


Resilience engineering and what it means for the future of manufacturing systems

Over the past few decades the lean production paradigm, along with the closely related just-in-time production, has dominated modern supply chain management and manufacturing systems. However, the Covid-19 pandemic revealed a fundamental weakness of modern supply chains and production systems: a persistent trade-off between efficiency and resilience.


The fundamental flaws of AI

The invention of large language models (LLMs) has profoundly shaped the landscape of AI, sparking another wave of hype in the media and the industry with voices even speculating about the emergence of general artifical intelligence. What often goes overlooked in these optimistic accounts, however, is the fact that the challenges of AI to engineer general artificial intelligence are more fundamental than commonly assumed.


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