poroject pages

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layout: single
title: "Detection and localization of leakages in water networks."
categories: projects
excerpt: "A u"
excerpt: "We researched the possibilities of leakage detection in real-world water networks in Munichs suburbs."
tags: acoustic anomaly-detection
header:
teaser: assets/images/projects/pipe_leak.png

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---
![logo](\assets\images\projects\openmunich.png){: .align-left style="padding:0.1em; width:5em"}
In cooperation with [Accenture](https://www.accenture.com/de-de) and [Red Hat](https://www.redhat.com/en), our chair organized the an opensource conference [`OpenMunich`](https:\\openmunich.eu) with focus on professional costumers and such becoming (students).
We also utilized thihs platform to talk about our research, while topics reached from Machine Learning applications to advanced in Quantum Computing technology.
Accenture and Red Hat contributed not only financial support, they were also responsible for a major share of each years programm with sessions reaching from `Ansible` hands-on to ML applications and QC advances.
My role was to organize the necessary infrastrukture, physical and personal as well as coordinate between the partners, colloegues and external speakers.
Furthermore, I was responsible for the projects website (content, structure and technology) as well as the personal to maintain it.![OpenMunich Website](\assets\images\projects\openmunich_website.png){: .align-rightstyle="padding:0.1em; width:10em"}

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layout: single
title: "AI-Fusion: Emergence Detection for mixed MARL systems."
title: "AI-Fusion: Emergence Detection for Mixed MARL Systems."
categories: acoustic anomaly-detection projects
excerpt: "Bringing together agents can be an inherent safety problem. Building the basis to mix and match."
header:
teaser: assets/images/projects/robot.png
  teaser: assets/images/projects/robot.png
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![logo](\assets\images\projects\robot.png){: .align-left style="padding:0.1em; width:5em"}
In cooperation with [Fraunhofer IKS](https://www.iks.fraunhofer.de/) this project aimed to investigate and detect emergent effects in multi-agent reinforcement learning scenarios, i.e., mixed-vendor autonomous systems (AI fusion).
Emergence in general refers to emerging dynamics of higher complexity (i.e., sum), which are fed by interacting entities (each other and the environment) of a specific complexity level (regarding their policies and capabilities).
![Relation emergence](/assets/images/projects/rel_emergence.png){: .align-center style="padding:0.1em; width:30em"}
In this context, we developed a full-stack, high-performance environment in Python, following the [gymnasium](https://gymnasium.farama.org/main/) specification for the training of reinforcement learning algorithms.
<div class="table-right">
![logo](\assets\images\projects\full_domain.png){: .align-right style="padding:0.5em; width:10em"}
| [GitHub Repo](https://github.com/illiumst/marl-factory-grid/) | [Read-the-docs](https://marl-factory-grid.readthedocs.io/en/latest/)  |
| [Install via PyPI](https://pypi.org/project/Marl-Factory-Grid/) | Read the Paper (TBA)  |
</div>
The main differentiation from already established MARL environments is its ability to employ various scenarios as a combination of `modules` and `configurations`. As well as the option to define per-agent observations, including placeholder and combined observation slices (grid-world). Moreover, this environment can handle multi-agent scenarios as well as sequential actions for inter-step observations.
Furthermore, we designed and implemented a [Unity demonstrator unit](https://github.com/illiumst/F-IKS_demonstrator) that can load and replay specific pre-recorded scenarios. This way, emerging unwanted and unsafe situations can be replayed and intuitively investigated.

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layout: single
title: "Linux Server Administration"
title:  "Linux Server Administration"
categories: projects server_admin unix
excerpt: "Linux Server Administration (Workstations and Web)"
header:
teaser: assets/images/projects/arch.png
  teaser: assets/images/projects/arch.png
---
![logo](\assets\images\projects\arch.png){: .align-left style="padding:0.1em; width:5em"}
During my time at the Mobile Distributed Systems Chair, I also supported my colleagues regarding the setup and maintenance of our workstations, the Windows server hypervisor, our Linux file server, and our networking infrastructure.
We orchestrated and utilized multiple systems with varying operating systems, hardware, driver versions, and libraries (damn you CUDA), mostly through Ansible.
Most recently transferred a major partition of or services to Kubernetes (K3S) while setting up a complete tool chain including Longhorn, Argo CD, Sealed Secrets, and GitLab. For ingress and egress, we set up Traefik as our fully automated proxy manager.
This way, we could differentiate between routes through different virtual networks for clients within our networks and external users, i.e., colleagues in the home office or students.
Crossing network borders was possible through a self-hosted WireGuard jump-host, which could also be utilized as our full-fledged VPN when traveling aboard.
This way, the whole team could access our ZFS-file server from anywhere.
Starting with self-scripted ML runs on non-reliable SLURM infrastructure (pool PCs could be turned off or used by students, which killed the SLURM agent at any time), I slowly transitioned to runs on individual, high-performance workstations.
Lately, those units were automated by weights-and-biases (WandB), which automatically runs experiments in pre-defined Docker containers; for that, we utilized our self-hosted registry through GitLab.
All in all, I learned a lot about Linux server administration, networking, code-as-infrastructure, and the spirit of the cloud native approach.
Nowadays, I thoroughly enjoy the `make your requirements less dumb` approach to things, moving from central services to a bunch of problem-specific (self-hosted) microservices.
Moreover, I really like to build systems from the ground up with only the necessary elements on top of a rolling release distribution (Arch-Linux-based).
I took some concepts into my `home lab`, where I now self-host most of my services, including this website. Isn't that cool? :cool: More of the tech stack I encountered on my journey is listed [here](/about).

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