Summary
Paris Amerikanos is a Data Scientist with eight years of experience bridging physics, applied mathematics, and machine learning to deliver production-ready AI systems. He has led end-to-end ML initiatives—from GPU-optimized inference pipelines and medical LLM prompt engineering to real-time computer vision and geospatial analytics—across startups and product-focused teams. At Eden Library he combined optics R&D, IoT vision models, and AWS infrastructure administration, and more recently accelerated medical AI deployments and agentic frameworks. Currently a PhD candidate in Machine Learning & AI, he pairs rigorous research sensibilities with hands-on engineering and performance profiling. Based in Greece, he’s known for digging into how systems work and migrating critical workloads to GPUs for tangible latency and throughput gains.
8 years of coding experience
6 years of employment as a software developer
M.Sc. Applied Mathematics and Physical Sciences, M.Sc. Applied Mathematics and Physical Sciences at National Technical University of Athens
PhD Candidate Machine Learning & Artificial Intelligence, PhD Candidate Machine Learning & Artificial Intelligence at University of Piraeus
English, Greek, German, Dutch