Federico Dassiè

Hi, I am
Federico Dassiè

Crafting state of the art apps and tools at the intersection of scientific computing, artificial intelligence, and humanities.

Software Developer
@ FAST Computing, Trieste (IT)
FOCUS
PythonLangChainFastAPIAWS AgentCoreOpenAI AgentsStrands AgentsNext.JS

About Me

Background & Philosophy

I am a Digital Humanist with a unique intersection of technical expertise and humanistic curiosity. I like working where complex data meets real people, turning messy, fascinating traces — historical or scientific — into something machines can reason about.

I enjoy building systems that bridge code and culture, from complex pipelines to tools that help explore, preserve, and reinterpret historical materials. I care about making complex technology feel clear, useful, and human, because even the smartest model still needs context.

Currently at FAST Computing, I bring that same approach to scientific computing: building web applications that turn reduced-order models, high-performance simulations, and AI into fast, interactive tools for real-time engineering and digital twins.

EDUCATION
2016
Diploma in Computer Science
ITST J.F. Kennedy (PN)
2019
BA in History
Ca' Foscari University of Venice
2020
First-Level Master in Digital Humanities
Ca' Foscari University of Venice
2022
MSc in Digital and Public Humanities
Ca' Foscari University of Venice

Work Experience

2022 — 2026
2026-

Software Developer

FAST Computing

Architecting end-to-end, high-performance web applications that bridge advanced scientific computing, machine learning, and interactive data visualization.

PythonTypescriptFastAPINext.JSKeycloak
2025

Digital Transformation Developer

Express Global

Designing and implementing applications and automation scripts to optimize and standardize company processes, reducing manual effort and enhancing operational efficiency.

PythonRubyPandasFastAPILangChain
2024-2025

Research Fellow

Istituto Italiano di Tecnologia (CCHT-IIT)

Working towards the implementation of robotic manipulation workflows for the transport and scanning of Cultural Heritage materials, and developing a 3D reconstruction pipeline leveraging Structure-from-Motion, NeRF, and Gaussian Splatting.

PythonUniversal Robots SDKGenesisNerfstudioOpenCV
2022-2024

Digitization Developer

Fondazione Giorgio Cini

Developing a computer vision and machine learning pipeline for the automated digitization of Cultural Heritage materials, transforming captured images into post-processed, metadata-enriched outputs.

PythonOpenCVSegmentAnythingDetectronAdobe Lightroom

Let's Connect

Always interested in new opportunities, collaborations, and conversations about scientific computing, AI, and humanities — from real-time simulation to cultural heritage.

© 2026 Federico Dassiè. All rights reserved.