π Braunschweig, Germany | π§ patnisiddharth1311@gmail.com
π΅οΈ Explore Dashboard | π Project Hub | π οΈ Skills Matrix | π Academic Timeline
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π€ Executive Summary & Focus Areas
I am a full-stack developer and Master's student in Digital Technologies, passionate about connecting software development with the future of AI . My focus is on building robust, cloud-connected systems, especially using agentic AI and LLM pipelines . I bring a strong, hands-on background in key technologies like Python, FastAPI, Docker, Playwright, and ML frameworks, with a growing portfolio of AI-first applications .
π¬ Research & Industry Cooperation (Ostfalia / TU Clausthal)
- Scalable Extraction: Built and evaluated LLM-based scraper generation pipelines using Python, Playwright, and multi-model LLM APIs (OpenRouter) .
- Self-Healing Loops: Implemented automated feedback loops with sandboxed code execution to verify script reliability .
- Benchmarking Infrastructure: Conducted comparative benchmarks across multiple LLM providers; analyzed cost, latency, and success rate trade-offs to identify optimal models for production use .
- Autonomous UI Execution: Explored Computer-Use Agent (CUA) architectures for GUI-based autonomous web interaction; contributed to a cascaded FastAPI pipeline with asynchronous job processing and persistent document storage .
πΌ Professional Experience History
- Performance Optimization: Refactored React component layer and Flask APIs; reduced perceived load times by ~30% through bundle optimization and response caching .
- CI/CD Integration: Dockerized microservices and integrated into Linux-based CI/CD pipeline, reducing environment-specific regressions .
- Architecture Quality: Standardized API-UI contracts and added input validation, reducing cross-team integration defects .
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Open-Source LLM Observability Platform
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AI Learning & Knowledge Platform
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Visual No-Code Automation Builder
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AI-Powered Retail Assistant
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π View Production-Ready Media & Medical Pipelines
- Tech Stack:
Python|FastAPI|OpenCV|Hugging Face|FFmpeg|Redis - Automated captioning, media retrieval and GPU-accelerated rendering; reduced production turnaround from 6 hours to 20 minutes .
- Tech Stack:
Python|Flask|OpenCV|scikit-learn - End-to-end diagnostic pipeline with ~85% accuracy; reduced per-case processing time from 30 minutes to 10 seconds .
π Mar 2025 - Present M.Sc. Digital Technologies @ Ostfalia & TU Clausthal (Germany)
ββ GPA: 2.80 | Focus: Distributed Systems & Agentic Implementations
π Jul 2021 - May 2024 B.Tech. Computer Engineering @ CHARUSAT (India)
ββ CGPA: 7.6 / 10
π Jun 2018 - Jun 2021 Diploma in Computer Engineering @ GTU (India)
ββ CGPA: 8.92 / 10