Adriano Fragomeni
PhD candidate in Computer Vision at the University of Bristol, supervised by Professor Dima Damen, with a strong academic background and applied research experience in both academic and industrial settings, including a research internship at Meta AI. My research focuses on multimodal video understanding, particularly in vision-language interactions for tasks such as cross-modal video retrieval. I have developed solid expertise in Machine Learning (ML), Deep Learning (DL), Computer Vision (CV), and Natural Language Processing (NLP), supported by a strong mathematical background. I have several years of experience using PyTorch to build and train ML/DL models. I am now looking to transition into an industry role where I can apply my skills and research experience to solve real-world challenges. When I am not working, I enjoy travelling, exploring new cultures, and mixing music. These interests keep me refreshed and inspire my creativity in both my research and daily life.

Publications


Education & Experience


September 2020 - PRESENT

PhD in Computer Vision

University of Bristol

Supervised by Dr Dima Damen


May 2023 - August 2023

Research Scientist Intern

Meta AI
October 2020 - November 2022

Teaching Assistant

University of Bristol
  • Applied Deep Learning
May 2019

Python/Machine Learning Tutor

Skienda

Tutor of a six-student class during a regional course for future Data Scientist set up by Skienda startup

September 2017 - April 2020

MSc in Data Science

Sapienza University of Rome

Supervised by Dr Aristidis Anagnostopoulos, Dr Danilo Avola and Mr Luigi Cinque

September 2010 - November 2016

BSc in Physics

Sapienza University of Rome

Supervised by Dr Paolo de Bernardis

Document

Interests


Music

I have always loved music, from the raw energy of metal and rock to the electrifying beats of electronic music. But Techno music holds a special place in my heart among all these genres.

Techno music has always been more than just a genre to me; it's a pulsating heartbeat that syncs with my soul. As an amateur techno DJ, I find immense joy in spinning tracks that delve into the depths of Hard Techno, Dark Techno, and Detroit Techno – my favourite subgenres that truly capture the essence of this powerful music. You can find my favourite songs in the Spotify playlist.

The main attitude in the Techno scene is about liberation and unity. It's a soundscape where individuality and community coexist, where the rhythm drives a collective euphoria, and the beat transcends language and culture.

I love the foundation of inclusivity and respect that techno stands on. It's about leaving prejudices at the door, respecting the space and each other, and losing oneself in the music.

Techno is more than music; it's a movement, a way of life that continues to inspire and unite people around the world.

Travelling

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