Software engineer and AI researcher with hands-on experience in developing and deploying machine learning and deep learning models, specializing in explainable AI, sequence modeling, and real-time data pipelines. Currently pursuing a PhD at HAW Hamburg, focusing on neuro-symbolic reinforcement learning frameworks and adaptive decision systems, with expertise in integrating symbolic rules, multi-agent systems, and explainable AI for high-stakes, real-time environments. Experienced in Python, PyTorch, ONNX, Pandas, and RESTful API development, with a strong track record of building scalable, secure, and high-performance backend systems. My work spans anomaly detection, behavioral modeling, real-time data visualization, and AI explainability, complemented by a solid foundation in software engineering, cloud deployment (AWS, Docker), and full-stack application development. I bring a structured, detail-oriented, and collaborative approach well-suited for designing, implementing, and deploying robust AI solutions in dynamic, contract-based projects.
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