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 27, 2022||I released a library that extends the functionality of PyTorch distributions with focus on TPPs.|
|Oct 12, 2021||I will be giving a talk on TPPs at the Berlin Timeseries Analysis Meetup (slides).|
|Sep 28, 2021||Our paper on anomaly detection with TPPs has been accepted to NeurIPS 2021.|
|Aug 31, 2021||I’m starting an internship at Facebook AI Research, where I will work with Maximilian Nickel.|
|Jun 28, 2021||I have released a new blog post about neural TPPs.|