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Watch out for the press-release of the NANOGrav collaboration! Thursday, June 29th, 1pm EDT.

Hello! I'm Rutger van Haasteren, a curious explorer at the intersection of theoretical physics, computational astrophysics, and machine learning. My journey has taken me from studying theoretical physics in the Netherlands to my current position at the Max Planck Institute for Gravitational Physics, otherwise known as the Albert Einstein Institute (AEI), in Hannover, Germany.

My academic pursuit started at Leiden University, where I initially pursued theoretical physics. This path led me to earn my Master's and Ph.D., with my doctoral research focusing on "Gravitational-Wave detection and data analysis for pulsar timing arrays." under supervision of Yuri Levin. I was fortunate enough to be at the right moment at the right time to significantly contribute the groundwork for contemporary pulsar timing array (PTA) projects.

Post-Ph.D., I found myself at the AEI in Bruce Allen's group, which was primarily focused on gravitational-wave detection and analysis from ground-based interferometers like LIGO and Virgo. From there, my journey took me to sunny California, where I joined the Caltech/Jet Propulsion Lab as an NSF Einstein Fellow. My tenure there was dedicated to foundational data analysis aspects of the (NANOGrav) collaboration: the North American PTA effort. Through NANOGrav I am also a member of the International Pulsar Timing Array (IPTA)

With an innate curiosity for machine learning, I made a career shift and spent five wonderful years at Microsoft as a senior data scientist. I worked on a variety of exciting projects, including text analysis using language models, forecasting, classification, Latent Dirichlet Allocation, and reinforcement learning for ad optimization.

Now, I'm back at the AEI, teaming up once again with Bruce Allen, who's recently been delving into PTA work. We are establishing a new group focusing on pulsar timing array data analysis methods and gravitational-wave detection.

My work goes beyond the realms of physics and machine learning. I'm passionate about unearthing insights from data analysis, employing Bayesian methods, and sampling methods. Creating toy models to dissect complex problems is something that brings me joy. Plus, I have a genuine love for teaching; there's nothing quite like the reward of sharing knowledge and igniting the spark of understanding in others.

So that's me - Rutger van Haasteren. A scientist, a coder, and an educator, driven by my love for understanding the universe and sharing that understanding with others. I invite you to join me on this journey of discovery.