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Andrea Vaiuso Curriculum and profile snapshot
Curriculum overview

Researcher, engineer, builder, and creative technologist.

I’m a 30 years old computer engineer with 4+ years of experience as a Python developer in applied machine learning and software engineering. Strong background in building, deploying, and maintaining production-grade Python systems for data processing, AI/ML, and backend services. Experienced with containerized environments, distributed systems, MLOps/DevOps workflows, and applied research translated into reliable software. I contributed to the academic literature with publications in reputable scientific journals, I have written and led projects that was approved and funded by Swiss funding companies

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Bio

Born in Palermo, Italy, in 1995. Now based in Winterthur, Switzerland and focused on applied AI and software engineering.

Core strengths

Artificial intelligence, machine learning, software engineering, system design, backend architecture, computer security, user experience, and product strategy.

Mindset

I value technical depth, human usefulness, aesthetics, and storytelling. I like building products that are both rigorous and emotionally clear.

Experience

Professional timeline

December 2025 — Present Independent Projects

Autonomous iOS App Full-Stack Developer

Independent Projects — MotorHub and FlashLingo

🇨🇭 Winterthur, Switzerland

  • Developed full-stack iOS applications including MotorHub and FlashLingo, both released on the Apple App Store.
  • Implemented the frontend in SwiftUI and integrated iCloud synchronization through CloudKit.
  • Designed backend infrastructure on Cloudflare Workers using D1, R2, KV, and Workers AI.
  • Built backend services in TypeScript using the Hono framework and integrated AWS services including EC2, RDS, S3, and Bedrock.
SwiftUI Swift CloudKit TypeScript Hono Cloudflare Workers Cloudflare D1 Cloudflare R2 Cloudflare KV Workers AI OAuth 2.0 JWT AWS Bedrock iOS Development
September 2023 — February 2026 ZHAW

Fixed-Term Researcher

Zürich University of Applied Sciences (ZHAW)

🇨🇭 Winterthur, Switzerland

  • Designed and built Python-based open-source LLM and RAG systems for automated document analysis and regulatory compliance in collaboration with Bundesamt für Zivilluftfahrt (BAZL).
  • Implemented retrieval systems using FAISS, HNSW, re-ranking strategies, and GraphRAG approaches for grounded information access.
  • Developed modular data-analysis and machine-learning pipelines, with inference services deployed through Docker and Docker Compose.
  • Deployed backend and frontend services on AWS EC2 and worked hands-on with AWS Bedrock.
  • Implemented graph-based models, autoencoders, and physics-informed ML for real-time aerodynamic prediction.
  • Applied reinforcement learning, Bayesian uncertainty quantification, and multi-fidelity data fusion for AI-driven aerospace digital twins in collaboration with EASA.
Python PyTorch LLM RAG FAISS HNSW GraphRAG Docker Docker Compose AWS EC2 AWS Bedrock Graph Neural Networks Autoencoders Physics-Informed ML Reinforcement Learning Bayesian Neural Networks Multi-fidelity Modeling
October 2025 — December 2025 ZHAW

Python Lecturer

Zürich University of Applied Sciences (ZHAW)

🇨🇭 Winterthur, Switzerland

  • Lecturer for Python programming and software logic in an engineering context.
Python Software Engineering Programming Logic Teaching
September 2021 — August 2023 University of Palermo

Research Fellow

University of Palermo (UNIPA)

🇮🇹 Palermo, Italy

  • Developed computer-vision pipelines in Python using CNNs and YOLO for detection, tracking, and classification tasks.
  • Deployed containerized machine-learning services for a smart parking recommendation system.
  • Built time-series forecasting models based on DNNs, RNNs, and LSTMs, together with probabilistic data-fusion workflows.
  • Contributed to backend logic in distributed systems and implemented secure video-stream processing with CTR-AES.
Python CNN YOLO DNN RNN LSTM Machine Learning Time-Series Forecasting Docker Docker Compose Distributed Systems AES-CTR Encryption
Focus areas

What I build

Applied AI for engineering banner

Applied AI for engineering


I build machine-learning systems for physical and industrial problems, including graph neural networks, autoencoders, physics-informed models, reinforcement learning workflows, and Bayesian uncertainty-aware architectures.

LLM retrieval and compliance banner

LLM, retrieval, and compliance tools


I design Python-based LLM and RAG systems for document analysis and regulatory workflows, using retrieval pipelines, FAISS and HNSW indexing, re-ranking, GraphRAG, and modular inference services.

Full-stack apps and cloud backends banner

Full-stack apps and cloud backends


I build end-to-end products across iOS, backend APIs, distributed systems, containerized services, Cloudflare infrastructure, and AWS platforms, turning prototypes and research concepts into usable software.

Computer vision forecasting and teaching banner

Computer vision, forecasting, and teaching


My work also includes computer vision with CNNs and YOLO, time-series forecasting with DNNs, RNNs, and LSTMs, secure media processing, and teaching Python and software logic in an engineering environment.

Contacts

Get in touch

Personal note. I see myself as a hybrid 360° engineer profile: researcher, designer, creator, and builder. I am motivated by understanding complex systems and turning that understanding into something tangible.