I’m a PhD student in machine learning at the Technical University of Munich, where I’m supervised by Stephan Günnemann.
My current research focuses on temporal point processes (TPP) — probabilistic models for continuous time event data, such user activity on social media or spike trains in neuroscience. I’m interested in both the modeling aspect (“How do we make TPPs more flexible and scalable?”) as well as their applications (“How can we use TPPs to solve real-world problems and better understand our data?”).
My broader interests include generative models, deep learning for graphs, time series forecasting and anomaly detection.
If you want to learn more about my research, check out my blog.
|Jun 28, 2021||I have released a new blog post about neural TPPs.|
|Jun 8, 2021||Check out the pre-print of our work on anomaly detection in event data with TPPs.|
|May 1, 2021||Our survey paper on neural temporal point processes has been accepted to IJCAI 2021.|
|Nov 10, 2020||Our work on fast & flexible TPPs has been accepted to NeurIPS 2020 as an oral presentation.|