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Pietro Leoncini

Ph.D. candidate in Bioingegneria E Scienze Medico-chirurgiche , 41st cycle (2025-2028)
Department of Mechanical and Aerospace Engineering (DIMEAS)

Profile

PhD

Research topic

Cognitive Vision for surgical robotics. Using Sim-to-Real methods, generative AI, and synthetic data to train CV models, reducing dependence on real clinical data.

Tutors

Keywords

Endoluminal surgery and Interventional endoscopy
Robotic surgery
Biomedical signal and image processing

Biography

Pietro Leoncini received his bachelor's degree in Bioengineering from the University of Pavia in 2022 and his master's degree in Bioengineering from the University of Genoa in 2024. He has been a tutor of Mathematical Analysis to second-year engineering students at the University of Pavia, a student representative and a Joint Committee representative at the University of Genoa. From November 2024 to October 2025, he has been a postgraduate research fellow at the Department of Surgical Sciences, University of Turin, at the MITIC (Minimally Invasive Therapy and Innovation Center) Lab.
In June 2025, Pietro presented his first-author publication, “A Reproducible Framework for Synthetic Data Generation and Instance Segmentation in Robotic Suturing,” at the CARS (Computer Assisted Radiology and Surgery) conference in Berlin. That same month, he attended the Hamlyn Symposium on Medical Robotics at Imperial College London, showcasing his work on “Bridging the Sim-to-Real Gap for Surgical Tool Segmentation in Robotic Suturing with Generative AI.” Currently, he is pursuing a PhD in Bioengineering and Medical-Surgical Sciences with Politecnico di Torino at MITIC Lab. His research focuses on advancing cognitive vision for surgical robotics, specifically leveraging simulated environments to generate high-fidelity synthetic data. By utilizing generative AI models to enhance the realism of these datasets, his work aims to bridge the sim-to-real gap—effectively training robust computer vision models while bypassing the logistical and ethical challenges of acquiring and annotating scarce clinical data.

Awards and Honors

  • Best project award won at the Hamlyn Winter School on Surgical Imaging and Vision of the Hamlyn Centre at Imperial College London (2025)