Samuele Pasini

Università della Svizzera Italiana. Deep Learning Engineer. Como - Lugano.

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Software Institute, USI

samuele.pasini@usi.ch

samu.pasini98@gmail.com

I am Samuele Pasini and I am a PhD researcher in USI Lugano. I am a member of the Software Institute and I work under the supervision of Prof. Paolo Tonella.

I am graduated at Politecnico di Milano, Master’s degree in Computer Science and Engineering, where I specialized myself into Artificial Intelligence and Deep Learning, combining scientific research to a large amount of practical projects. I have done my Thesis in the context of Illegal Landfills Detection, applying Computer Vision techniques in the field of Remote Sensing under the supervision of Prof. Piero Fraternali.

After the graduation, I worked as Computer Vision Engineer for Mindearth, a Swiss company that operates in a wide range of sectors combining street-level and remote sensing imagery.

After one year, I decided to start my PhD in USI. My research is related to Deep Learning and LLMs, with a specific focus on Adversarial/Poisoning attacks and the usage of LLMs for code generation.

News

Jul 20, 2024 Excited to Announce: My PyTorch Course is Now Available on ProfessionAI!
Jun 15, 2024 Thrilled to have participated in ACDL 2024! I was exited to explore the future of AI with brilliant minds.
Apr 20, 2024 Delighted to Share AI and Autonomous Driving Insights with Students! Grateful for the opportunity to inspire the next generation.
Jan 08, 2024 Embarking on a new academic adventure! Delighted to commence my PhD journey at USI. Grateful for the opportunity and eager to dive into research excellence! :books:
Jul 22, 2023 Excited to have participated in AWS Summit 2023! Grateful to MindEarth for the opportunity to engage with cutting-edge technologies and innovations.

Latest Posts

Selected Publications

  1. MDPI
    Weakly supervised object detection for remote sensing images: A survey
    Corrado Fasana ,  Samuele Pasini ,  Federico Milani , and 1 more author
    MDPI Remote Sensing, 2022