AI & ML Expert

Carlo Calledda
Machine Learning Engineer

μηδὲν ἄγαν

Specialized in developing cutting-edge ML/DL architectures with 5+ years of experience. From computer vision to NLP, I architect solutions that solve real-world problems at scale.

5+
Years
Experience
100+
Articles
20+
Projects
6
Professional
Certifications
Profile Image
Deep Learning
Big Data
MLOps

About Me

Hi, I’m Carlo Calledda. I started with a thesis on neural networks for seismic design and academic research in data science and machine learning engineering, which I turned into specialized experience developing end‑to‑end MLOps solutions and computer vision systems.

Today I’m a Data Scientist specialized in MLOps implementations and microservice systems: I design automated ML pipelines, build REST APIs with FastAPI, and deliver containerized deployments. I have proven experience delivering end‑to‑end solutions, from dataset automation tools to production‑ready services.

I have a solid foundation in structural engineering and growing expertise in NLP and large language model applications, with a strong passion for Rust. I aspire to lead projects that combine my MLOps background with emerging ML/NLP/LLM technologies in companies that value technical excellence, automation, and impactful AI solutions.

5+
Years of Experience
50+
Articles
20+
Projects
6
Professional Certifications

Technical Skills

Machine Learning & AI

Deep Learning Neural Networks Computer Vision Natural Language Processing Time Series Forecasting Transformers Model Optimization MLOps Reinforcement Learning

Programming & Frameworks

Python PyTorch Scikit-learn TensorFlow FastAPI ONNX ONNX Runtime Pydantic Auth (OAuth2/JWT) Bearer Token WebAssembly Flask Rust Leptos Active-web Plotly LaTeX

Cloud & DevOps

Docker AWS Kubernetes CI/CD MLflow Argo Nginx Keycloak Google Cloud Terraform

Data Engineering & Databases

SQL ETL Pipelines PostgreSQL Apache Spark DuckDB Data Warehousing MinIO Rasterio GDAL PostGIS GeoPandas PyArrow MongoDB Redis

Tools & MLOps Ecosystem

Jupyter VS Code Git GitHub Pandas NumPy Streamlit GitLab Weights & Biases Optuna SciPy RAPIDS Ruff Bandit Label Studio Git LFS MKDocs UV loguru marimo

Featured Projects

wasm-knowledge-chatbot-rs

Rust WASM Leptos WebLLM Chatbot

A blazingly fast, modern chat interface built with Rust/WASM and Leptos, featuring local AI model execution via WebLLM. Privacy‑first design with no backend dependencies. (Updated 2 weeks ago)

Code Live Demo

mcp-py-json-doc

Python MCP Knowledge Graph Rust Docs

A Model Context Protocol (MCP) server that transforms Rust documentation into a queryable knowledge graph, enabling semantic search and AI‑assisted discovery. (Updated 3 weeks ago)

Code Live Demo

wasm-image-studio-rs

Rust WebAssembly Image Processing

Web‑based image editor built with Rust & WebAssembly. Apply filters, adjust colors, and process images in real‑time with near‑native performance. (Updated on Jul 9)

Code Live Demo

mcp-rustdoc-parser

Rust MCP Rustdoc Parser

MCP server for parsing and querying Rust documentation. Extracts details about functions, structs, and enums, exposing them via a programmable interface. (MIT, updated on Jun 15)

Code Live Demo

python-project-analyzer-mcp

Python MCP Static Analysis

MCP server that analyzes Python projects, extracts library signatures, and surfaces project information to help AI assistants understand codebases. (MIT, updated on May 18)

Code Live Demo

Rust-MLOps-predictor-RestAPI

Rust Actix-Web MLOps Object Detection

The "Prediction" project: a high‑performance object detection service built with Rust and Actix‑Web, focused on robustness and production‑ready APIs. (Updated on Feb 16)

Code Live Demo

Scientific Publications

Research Paper
MAY 19, 2021

Optimal design of earthquake‑resistant buildings via neural network inversion (AI)

Presents a neural‑network inversion framework to optimize structural parameters for seismic resilience. Combines simulated ground‑motion data, sensitivity analysis and gradient‑based search to minimize expected seismic demand while maintaining material efficiency. Demonstrates improved performance on benchmark structural models under varying seismic scenarios.
Research Grant (Winner)
SEP 2021 – FEB 2022

Development of a CNN object‑detection algorithm for identifying celestial bodies

Built an astronomy image dataset with Aladin, applied targeted data augmentation, and bootstrapped a detector from an image classifier. The pipeline was optimized for low‑power CubeSat hardware via pruning/quantization and memory‑aware batching, accompanied by monthly technical reports and a comprehensive final deliverable.
Conference Paper
NOV 24, 2021

A SOM‑based method for detecting plastic patches in the sea (AI)

Proposes a Self‑Organizing Map approach on multi‑spectral remote‑sensing imagery to detect marine plastic aggregations. The method includes atmospheric correction, texture/ratio features and spatial post‑processing, achieving promising precision/recall against reference datasets from coastal monitoring campaigns.

Certifications & Achievements

Google Data Analytics Professional Certificate

Google (via Coursera)
—
Job-ready training in spreadsheets, SQL, R, and data visualization for entry-level data analyst roles.
Analytics

Google IT Automation with Python Professional Certificate

Google (via Coursera)
—
Python scripting, Git/GitHub, troubleshooting, and automation of IT tasks including OS and cloud workflows.
Python

Google Business Intelligence Professional Certificate

Google (via Coursera)
—
BI foundations: data modeling, ETL, SQL, and dashboarding to deliver business-ready insights.
BI

Machine Learning Specialization

DeepLearning.AI & Stanford Online (Coursera)
—
Supervised ML, classification, regression and neural networks with hands-on Python implementations.
ML

Natural Language Processing Specialization

DeepLearning.AI (Coursera)
—
NLP with RNNs, attention, transformers and sequence-to-sequence models for text tasks.
NLP

Machine Learning Engineering for Production (MLOps)

DeepLearning.AI (Coursera)
—
End-to-end ML systems: data pipelines, deployment, monitoring, and CI/CD for models in production.
MLOps