Conducting research at Eindhoven University of Technology on fast and scalable Bayesian inference. I'm a part of the AiM-TT project, which is an AI Learning Initiative for Multi-model Traffic and Transporation in the Netherlands. AiMTT aims to cultivate a highly skilled and diverse AI talent pool equipped to address the opportunities and challenges of AI in mobility, transport, and logistics. By combining real-world case studies with knowledge development, this initiative fosters deep expertise in the field. I work directly together with Delft university and Nationaal Dataportaal Wegverkeer to solve real problems on Dutch roads.

Co-founded Lazy Dynamics, a startup focused on transforming uncertainty into actionable insights through cutting-edge Probabilistic AI Solutions for enterprise applications.

Co-organize public events and meetups for the Julia and Python communities in Eindhoven, fostering local developer engagement and knowledge sharing. I'm mostly focused on marketing and community management as well as content creation, photos, videos and social media management.

Conducted research on novel reactive message-passing frameworks for Bayesian inference. Served as postdoctoral researcher for 18 months following PhD completion.

Completed two summer internships at ExxonMobil's headquarters, focusing on the integration of advanced numerical linear solvers into large-scale simulation software. Collaborated closely with a small team to deploy solutions on a high-performance computing cluster with thousands of compute nodes.

Developed VDJdb, a curated database of T-cell receptor (TCR) sequences with known antigen specificities. The database facilitates access to information on T-cell receptor antigen specificities, specifically the recognition of epitopes in MHC contexts. Served as lead developer for the web interface, resulting in a publication in Nature.