News & Updates

10 / 2024	New paper on the arXiv: “Flow Matching for Atmospheric Retrieval of Exoplanets: Where Reliability meets Adaptive Noise Levels”. This work has been accepted for publication in Astronomy & Astrophysics.
06 / 2024	I will be presenting my current research as a poster at Exoplanets 5 in Leiden.
06 / 2024	New (co-author) paper on the arXiv: “Use the 4S (Signal-Safe Speckle Subtraction): Explainable Machine Learning reveals the Giant Exoplanet AF Lep b in High-Contrast Imaging Data from 2011”.
05 / 2024	My latest work is an eLightning at AbSciCon 2024. Unfortunately, I am not attending myself, but come talk to my co-authors if you are there!
12 / 2023	New paper on the arXiv: “Inferring Atmospheric Properties of Exoplanets with Flow Matching and Neural Importance Sampling”. This work has been accepted as an oral at the AI to Accelerate Science and Engineering (AI2ASE) workshop at AAAI 2024.
09 / 2023	New paper on the arXiv: “Parameterizing pressure-temperature profiles of exoplanet atmospheres with neural networks”. Update: Now also officially published in Astronomy & Astrophysics.
08 / 2023	I will be attending the 2023 CZS Summer School on Scientific Machine Learning for Astrophysics in Heidelberg.
08 / 2023	New paper published in MNRAS: “Chasing rainbows and ocean glints: Inner working angle constraints for the Habitable Worlds Observatory” 🌈 This was the result of a really fun collaboration that started at the Lorentz Center in Leiden. Also: Check our our GitHub!
03 / 2023	New paper on the arXiv: “Comparing Apples with Apples: Robust Detection Limits for Exoplanet High-Contrast Imaging in the Presence of non-Gaussian Noise”! Update: Now also officially published in The Astrophysical Journal.
03 / 2023	I have started a 3-months industry internship at Bosch Digital to work on software engineering, data analytics and MLOps.
02 / 2023	I have been invited to and will be participating in the Optimal Exoplanet Imagers workshop at the Lorentz Center in Leiden.
12 / 2022	Two new workshop papers (1, 2) accepted at the Machine Learning and the Physical Sciences workshop at NeurIPS 2022!
06 / 2022	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)!
05 / 2022	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.
04 / 2022	New paper on the arXiv: “Half-sibling regression meets exoplanet imaging: PSF modeling and subtraction using a flexible, domain knowledge-driven, causal framework?” Update: Now also officially published in Astronomy & Astrophysics.
04 / 2022	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!
12 / 2021	My work was featured in the 3/2021 issue of the Max Planck Research magazine.
11 / 2021	I am now an associated PhD student of the ETH AI Center.
10 / 2021	~~I am assisting with the organization of the DALI 2021 meeting.~~ Cancelled due to COVID.
10 / 2021	I will be presenting my research at the AI+X Summit 2021 in Zurich.
09 / 2021	I am a TA for the seminar on Beyond i.i.d. learning: Causality, dynamics, and interactions at ETH in the fall of 2021.
01 / 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.
12 / 2020	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.
10 / 2020	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!
09 / 2020	I am a TA for the seminar on Causal Representation Learning at ETH in the fall of 2020.
08 / 2020	I have been selected to participate in the 2020 online edition of AstroHackWeek!
08 / 2020	I am participating in DotDotAstro, the first online-only version of the .Astronomy (un)conference.
07 / 2020	I am presenting a poster at the virtual Exoplanets III conference in Heidelberg.
07 / 2020	I have completed my one-year stay at ETH and moved back to Tübingen.
01 / 2020	I was at the workshop on Post-processing for high-contrast imaging of exoplanets and circumstellar disks (HCIpp) at the Harnack House in Berlin.
01 / 2020	I have co-organized a one-day workshop on deep learning for (astro)-physics at ETH.
12 / 2019	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! :) )
09 / 2019	Our paper on CNNs for gravitational waves was finally published at Physical Review D!
08 / 2019	I was selected to participate at AstroHackWeek 2019 in Cambridge (UK).
07 / 2019	I attended the Artificial Intelligence in Astronomy workshop at the ESO Garching.
07 / 2019	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.
05 / 2019	I participated in another science slam, again winning second prize.
04 / 2019	New paper on the arXiv: “Convolutional neural networks: a magic bullet for gravitational-wave detection?”
02 / 2019	I moved to Zurich and started my one-year stay at ETH.
12 / 2018	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.
09 / 2018	I officially started my PhD at the Max Planck ETH Center for Learning Systems.
09 / 2018	I participated in a science slam at the Max Planck Day 2018, and won a second prize.