1) AI Automation & Enterprise Delivery
- OfferGenerator (Flask → PowerPoint): implemented, tested, and deployed on a domain network; manual offer creation was reduced from 4–5 hours to ~30 minutes (≈85–90%). More information. See demo.
- Tender/Ausschreibung Generator (Flask → PowerPoint): designed for structured generation of BA/MSc announcements; PDF extraction, template-driven PPTX generation, and Azure/OpenAI-based text generation are integrated. Source content is derived from official PEM study pages (see: pem.rwth-aachen.de/go/id/fecr ). Automated export to network locations is supported. More information. See demo.
- PowerPoint Add-in (C#, .NET Framework VSTO/COM): implemented, tested, and deployed on a domain network and developed as an internal productivity tool; GPT-enabled text and image generation, image analysis, and text-to-diagrams/charts workflows are provided; production deployment for staff use has been established. More information. See demo.
- AI-based Local-First Marketing Agent Framework: conceptualized and developed as a local-first AI marketing operating system for brand workspace analysis, campaign generation, platform-specific post package preparation, media management, approval-gated publishing, simulation, analytics import, learning loops, and guarded connector workflows. The implementation combines a Next.js dashboard, FastAPI backend, Campaign Autopilot services, safe credential handling, scheduler workflows, local and stub LLM modes, YouTube OAuth publishing, TikTok and Instagram dry-run scaffolds, and Paperclip/MiroFish extension points. The verified engineering baseline includes 131 backend tests, Ruff and ESLint checks, a Next.js production build, healthy launcher and API routes, dry-run publish audit jobs, and analytics and scoring checks; final deployment-readiness tests are running before production deployment. More information. See demo.
2) Enterprise AI (Privacy-First)
- On-Prem RAG (offline / privacy-first): retrieval-augmented generation for internal knowledge workflows; emphasis is placed on governance, operational robustness, and deployment constraints in enterprise environments. More information. See demo.
3) Generative AI Media & Commercial Production Framework
- AIMG - Local-First AI Commercial Production Framework (06/2026): conceptualized, engineered, and deployed end to end as a local-first, cloud-ready production framework that turns a text brief and brand references into finished, quality-checked multi-scene commercials. The framework combines a Next.js/React front end, FastAPI/SSE backend, model registry and auto-discovery, ComfyUI/Diffusers/cloud adapters, FLUX/Wan/Kling/Seedance/Veo model routing, LLM-based direction, automated quality gates, MCP-based agent orchestration, production provenance, and server-side cost governance; local rendering is designed for a 12 GB GPU, including 14B video-model operation via fp8 quantization, block swapping, and distilled sampling. More information. See demo.
4) Speech & Emotion Recognition (ASR/SER) Framework
- AI-based Development: Speech & Emotion Recognition (ASR/SER) Framework — Two Models: separate models for Automatic Speech Recognition (ASR) and Speech Emotion Recognition (SER) have been trained via wav2vec2 fine-tuning; both audiofile-based and real-time inference are supported; evaluation is performed via Word Error Rate (WER) and Unweighted Average Recall (UAR).
- HPC Training (RWTH High Performance Computing): training and inference workflows of the ASR/SER models are executed on RWTH HPC (SLURM) to accommodate large-scale datasets and controlled experiments. More information. See demo.
5) Enterprise IT & System Integration (Avantis + BIC)
- Identity & Access: Active Directory and Group Policy Objects (GPO) are administered, including groups/permissions, service accounts, and file server access control.
- Stability & Security: WSUS patching, Sophos Endpoint Security, CommVault backups, standardized rollouts, documentation, and security awareness/testing are applied to support stable operations.
- Site Operations: Multi-site infrastructure work has been delivered at PEM Avantis and the Battery Innovation Cluster (BIC) .
6) XR Learning Technologies (RWTH LearnTech)
- Project Context (04/2022–10/2023): contributions were delivered within the RWTH LearnTech environment (see LearnTech), including the Unity-based xTeach VR project (see xTeach VR).
- Spatial Audio Integration: Google Resonance Audio was integrated and parameterized for improved realism of distance and room perception in immersive learning environments (Unity-based audio pipeline design and tuning).
- Learning Analytics Instrumentation: keyword recognition and interaction events were operationalized via xAPI; statements were collected in a Learning Record Store (LRS) for subsequent analysis.
- Analytics Visualization: Learning analytics were processed and visualized through a React-based dashboard, enabling structured exploration of user behavior and interaction patterns.
- Research Stimuli: Experimental stimuli were created and iteratively optimized to support controlled studies (audio stimulus engineering and quality assurance under research constraints).
- Publication: Teaching and research context—including this project period—is documented in the Osnabrück Teach-R publications (PDF).
7) Web Design & Web Development
- Front-End — UX/UI & Presentation Layer: Layout, typography, spacing, responsive behavior, and information architecture are treated as first-class design and engineering concerns. For beatandwin.com, a bilingual DE/EN user experience was conceptualized and implemented with React, Next.js, TypeScript, i18n routing, localized metadata, structured content, calculator flows, and Core Web Vitals-oriented performance. Semantic HTML, modular styling, accessible landmarks and labels, optimized assets, and restrained dependencies support fast rendering, visual stability, and consistent user flows across desktop and mobile surfaces. Visit site 1, Visit site 2, Visit site 3
- Back-End & Server-Side Delivery: Application logic, routing, validation, form workflows, secured endpoints, and API-backed integrations are implemented as part of reliable server-side delivery. beatandwin.com was deployed and operated on Cloudflare edge infrastructure with Cloudflare Workers, Cloudflare D1, serverless REST endpoints, GitHub Actions CI/CD, 300+ automated tests, post-deploy healthchecks, and rollback-oriented production safeguards. Automated data pipelines support recurring updates from official HTML/PDF sources with AI-assisted extraction, validation gates, and privacy-by-design operation without cookies, tracking, or user accounts. This backend foundation also extends into on-premises RAG architectures, where documents are processed, stored, embedded, vectorized, and retrieved through structured database-backed pipelines. See project.