- (Nov 2023) Our work "Blood Glucose Forecasting from Temporal and Static Information in Children with T1D" has been accepted for publication at Frontiers in Pediatrics.
- (Nov 2023) Selected to be among the top reviewers at NeurIPS'23.
- (Oct 2023) New preprint "The Mixtures and the Neural Critics: On the Pointwise Mutual Information Profiles of Fine Distributions" is available!
- (Sep 2023) Two papers got accepted to NeurIPS'23: 1) "Beyond Normal: On the Evaluation of Mutual Information Estimators", and 2) "Effective Bayesian Heteroscedastic Regression with Deep Neural Networks".
- (Apr 2023) Our paper "On the Identifiability and Estimation of Causal Location-Scale Noise Models" got accepted to ICML'23.
- (Mar 2023) Our paper "3DIdentBox: A Toolbox for Identifiability Benchmarking" got accapted to the dataset track at CLeaR'23
- (Feb 2023) I received an AISTATS'23 Reviewer Award (awarded to top 10% best reviewers).
- (Jan 2023) Our submission "Identifiability Results for Multimodal Contrastive Learning" got accepted to ICLR'23.
- (Dec 2022) Our ICLR'23 workshop proposal on Time Series Representation Learning for Health (TSRL4H) got accepted.
- (Aug 2022) I gave a tutorial at the Machine Learning Summer School in Healthcare and Biosciences.
- (May 2022) Our paper titled "Inferring Cause and Effect in the Presence of Heteroscedastic Noise" got accepted at ICML'22.
- (Apr 2022) A portrait article about me and my research got featured in ETH news.
- (Feb 2022) I received an AISTATS'22 Reviewer Award (awarded to top 10% best reviewers).
- (Dec 2021) Our paper titled "Estimating Mutual Information via Geodesic kNN" got accepted at SDM'22.
- (Dec 2021) Two papers ([1], [2]) were accepted the AAAI-22 Workshop ITCI'22.
- (Dec 2021) I will co-teach the course AI Center Projects in Machine Learning Research in the upcoming summer semester.
- (Sep 2021) I started as a Post-Doc Fellow at the ETH AI Center.