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Tom Bakkes is a postdoctoral researcher in the Biomedical Diagnostics lab at the Eindhoven University of Technology. Here he works on using statistics and machine learning to build clinical decision support systems for the perioperative care. Thereby his current studies focus on automatic detection of patient-ventilation asynchrony, and early detection of deterioration in post-operative patients. For the latter study he works in close collaboration with clinical experts from the Catharina hospital in Eindhoven.

I work on clinical decision support systems in the perioperative care that will allow clinicians to achieve a more accurate and faster insight on their patients.

Tom Bakkes received his bachelor's degree in Electrical Engineering from Eindhoven University of Technology in 2016. He continued his studies in Electrical Engineering, specializing in the Signal Processing Systems group, where he developed a strong interest in applying data-driven and signal processing techniques to healthcare challenges. For his master's graduation project, he joined the Biomedical Diagnostics Lab, where he worked on machine learning methods for predicting the outcome of in vitro fertilization treatments.

After obtaining his master's degree in 2018, he remained at the Biomedical Diagnostics Lab as a PhD candidate. His research focused on the development of clinical decision support systems for perioperative and intensive care, combining statistics, signal processing, and machine learning to support clinicians in making timely and informed decisions. His work included automatic detection of patient-ventilator asynchrony and the early prediction of deterioration in postoperative patients, in collaboration with clinical experts from Catharina Hospital Eindhoven.

In April 2025, he earned his PhD from Eindhoven University of Technology with the dissertation Machine Learning for Clinical Decision Support in Perioperative and Intensive Care. He currently continues his work at the intersection of engineering, machine learning, and healthcare, with a particular focus on translating data-driven innovations into clinically relevant decision support tools.