Rik L.E.M. Ubaghs
Neural Engineer
Technology plays a crucial role in advancing healthcare and improving the well-being of patients. Through the development of next generation medical technology, we can build healthcare solutions that redefine the way care is delivered and experienced.
About
Neurotechnology (Ph.D.)
Brain and Cognitive Sciences (M.Sc.)
I am a neural scientist and engineer specialized in neurotechnology. I received my Ph.D. from the Swiss Federal Institute of Technology Zurich (ETH Zurich). My areas of expertise are neural engineering, health technologies, brain-machine interfaces, and data analysis.
My main interest lies in bridging the gab between experimental technology and practical applications.
Current Positions
CEO, Arago Labs
I am currently the CEO and co-founder of Arago Labs in Zurich, Switzerland. At Arago, we design innovative surgical equipment aimed at improving the precision of tumor removal procedures. Through the seamless integration of advanced microscopy techniques and artificial intelligence, we offer surgeons an unparalleled view of deceased tissue during resection, promising to transform oncological surgery and enhance patient outcomes.
Past Projects
Combined fluorescence microscopy and functional MR imaging
During my Ph.D. at the Swiss Federal Institute of Technology Zurich (ETH Zurich), I studied the interaction between several genetically defined cell populations and the brain vasculature.
My research included several subprojects:
- I developed an MRI compatible fluorescence microscope (full-cycle product design) that allows researchers to measure the single-cell calcium activity of a neural population (> 150 cells) while simultaneously recording BOLD fMRI activity across the whole brain.
- Using the combined microscopy-MR imaging approach, we demonstrated a difference in the cellular activity patterns that was dependent on their location with respect to the vasculature. Results are currently under review at Nature Methods.
- In several conference proceedings we demonstrated that genetically distinct neural populations (CamKII, SOM, VIP, and PV), had a differential effect on the BOLD fMRI signal. To acquire data to support this claim I designed a MRI compatible dual-color fiber-photometry setup with > 100 channels.
Agora Technologies
In 2016, I co-founded Agora Technologies, a startup that aimed to build data solutions to streamline and automate several daily operations in the medical sector. We mainly focussed on the creation, maintenance, and analysis of large-scale data bases using advanced machine learning approaches.
The project was ultimately discontinued in 2018.
Hybrid signals for brain-machine interfaces
In 2015, I developed and tested (> 100 days) a brain decoding method based on the combined local field potential and single/multi unit electrophysiological signals collected with an Utah array implanted in the primary sensory and motor area of non-human primates. We found that channels that did not show single unit activity due to the advanced age of the implant, contained significant levels of task-relevant information in the LFP signal.
