News & Updates

New paper on the arXiv: “Comparing Apples with Apples: Robust Detection Limits for Exoplanet High-Contrast Imaging in the Presence of non-Gaussian Noise”!
I have started a 3-months industry internship at Bosch Digital to work on software engineering, data analytics and MLOps.
I have been invited to and will be participating in the Optimal Exoplanet Imagers workshop at the Lorentz Center in Leiden.
Two new workshop papers (1, 2) accepted at the Machine Learning and the Physical Sciences workshop at NeurIPS 2022! For environmental reasons, I will be attending virtually this year, but please feel free to reach out for some virtual interactions!
I am excited to announce that I have been selected to participate in the Astrobiology challenge of the 2022 edition of the Frontier Development Lab (FDL)!
I will be in the United States for two weeks! I am presenting some of my ongoing research about atmospheric retrievals and parameterizing PT profiles with machine learning at the University of Maryland, NASA Goddard, STScI, and finally at AbSciCon 2022 in Atlanta.
New paper on the arXiv: “Half-sibling regression meets exoplanet imaging: PSF modeling and subtraction using a flexible, domain knowledge-driven, causal framework?” Even better: This work has been accepted for publication in Astronomy & Astrophysics.
I have helped out to set up the website for the First Workshop on Causal Representation Learning at UAI 2022. Check it out, I think it will be a great workshop!
My work was featured in the 3/2021 issue of the Max Planck Research magazine.
I am now an associated PhD student of the ETH AI Center.
I am assisting with the organization of the DALI 2021 meeting. [Cancelled due to COVID.]
I will be presenting my research at the AI+X Summit 2021 in Zurich.
I am a TA for the seminar on Beyond i.i.d. learning: Causality, dynamics, and interactions at ETH in the fall of 2021.
I gave a virtual invited talk about my work on high-contrast imaging of exoplanets at the group seminar of the Planetary and Stellar systems Imaging Laboratory (PSILab) at the University of Liège.
I gave a brief public outreach talk about high-contrast imaging as a de-noising problem at the Machine Learning & Astrophysics Hack Days at ETH Zurich.
New workshop paper on the arXiv: “Physically constrained causal noise models for high-contrast imaging of exoplanets.” This work was accepted into the Machine Learning and the Physical Sciences workshop at NeurIPS 2020!
I am a TA for the seminar on Causal Representation Learning at ETH in the fall of 2020.
I have been selected to participate in the 2020 online edition of AstroHackWeek!
I am participating in DotDotAstro, the first online-only version of the .Astronomy (un)conference.
I am presenting a poster at the virtual Exoplanets III conference in Heidelberg.
I have completed my one-year stay at ETH and moved back to Tübingen.
I was at the workshop on Post-processing for high-contrast imaging of exoplanets and circumstellar disks (HCIpp) at the Harnack House in Berlin.
I have co-organized a one-day workshop on deep learning for (astro)-physics at ETH.
I was invited to attend the workshop on Machine Learning Tools for Astronomy at Schloss Ringberg (and my talk was mentioned in Hogg’s research blog! :) )
Our paper on CNNs for gravitational waves was finally published at Physical Review D!
I was selected to participate at AstroHackWeek 2019 in Cambridge (UK).
I attended the Artificial Intelligence in Astronomy workshop at the ESO Garching.
I gave an invited talk at the mini-symposium on “Topological data analysis and deep learning: theory and signal applications” at ICIAM 2019 in Valencia.
I participated in another science slam, again winning second prize!
New paper on the arXiv: “Convolutional neural networks: a magic bullet for gravitational-wave detection?”
I moved to Zurich and started my one-year stay at ETH.
I gave an invited talk about my work on CNNs and gravitational waves at the group seminar of the Theoretical Astrophysics Section at the University of Tübingen.
I officially started my PhD at the Max Planck ETH Center for Learning Systems.
I participated in a science slam at the Max Planck Day 2018, and won a second prize!