Dr Alejandro Granados is a Lecturer in Surgical Data Science at the Department of Surgical & Interventional Engineering at King’s College London, UK. He did his PhD in Simulation and Modelling for Medicine and Surgery at Imperial College London (ICL) and has taken post-doctoral positions at ICL, UCL, and KCL.

His research expertise is the result of working in multidisciplinary and diverse biomedical engineering-related projects looking at different types of data before, during, and after surgical interventions. The goal of his research is to improve surgery from a data perspective by increasing the predictive and prescriptive capabilities of patient-specific cases using innovation and technology. His main research topics include the use of AI for surgical phase and action recognition, the use of multiple modalities in surgical interventions, the reduction of surgical complications, predicting intra-operative events, and modelling patient perspectives towards surgery.

His research has resulted not only in publications in leading international conferences and high-impact factor journals but also in two patents, a commercial prototype, a software tool used at the National Hospital for Neurology and Neurosurgery (UK), international art exhibitions, patient focus groups, and numerous public engagement activities. 

Teaching

Alejandro is leader of the Applied Medical Robotics course. 

Alejandro is also a teacher on the following courses:

• Applied Medical Robotics
• Advanced Medical Robotics
• Advanced Machine Learning
• Computational Applied Biomathematics
• Critical Skills Journal Club