Imperial College London

Mr Joao Cartucho

Faculty of MedicineFaculty of Medicine Centre

Casual - Lib. Ass, Clerks & Gen. Admin Assistants







Commonwealth BuildingHammersmith Campus





Joao Cartucho is a Ph.D. student in The Hamlyn Centre at Imperial College London, working at Surgical Robotics and Imaging Diagnostics and Sensing. He is supervised by Dr. Stamatia GiannarouProfessor Dan Elson and Professor the Lord Darzi of Denham.

During his master thesis, he collaborated with Professor Manuela Veloso at Carnegie Mellon University on a learning algorithm that enhances a robot's object recognition capabilities by proactively asking humans for help, at the Machine Learning Department. This work was published in IROS 2018 and was a finalist for the Best RoboCup Paper Award.

He is a member of the RoboCup Organizing Committee and a mentor for OpenCV at Google Summer of Code 2019.

Recent Work

This video illustrates Joao's master thesis work where robots learn to detect new objects by proactively interacting with humans. This video was awarded as the Best Master’s Thesis Video at IST / DEEC.



Weld A, Cartucho J, Xu C, et al., 2023, Regularising disparity estimation via multi task learning with structured light reconstruction, Computer Methods in Biomechanics and Biomedical Engineering-imaging and Visualization, Vol:11, ISSN:2168-1163, Pages:1206-1214

DeLorey C, Davids JD, Cartucho J, et al., 2022, A cable‐driven soft robotic end‐effector actuator for probe‐based confocal laser endomicroscopy: Development and preclinical validation, Translational Biophotonics, ISSN:2627-1850

Cartucho J, Wang C, Huang B, et al., 2021, An enhanced marker pattern that achieves improved accuracy in surgical tool tracking, Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization, Vol:10, ISSN:2168-1163, Pages:1-9


Wang C, Cartucho J, Elson D, et al., 2022, Towards autonomous control of surgical instruments using adaptive-fusion tracking and robot self-calibration, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE, Pages:2395-2401, ISSN:2153-0858

Leiloglou M, Gkouzionis I, Kedrzycki MS, et al., 2021, Real-time spectral tracking routine for fluorescence hyperspectral guidance in breast conserving surgery

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