• After three amazing years in Amsterdam, I followed my advisor Sebastian to TU Berlin to finish my Ph.D. there. Very excited to join the data management community in Berlin!
• I was featured in an ICAI blogpost.
• I presented an overview of my PhD research at the Microsoft GSL talk series.
• I did a research internship in Redmond with the Microsoft Gray Systems Lab this summer.
• I presented a poster on Towards Declarative Systems for Data-Centric Machine Learning at DMLR at ICML.
• Sebastian, Shubha and me won an ACM SIGMOD Best Demo Runner Up Award for our demo on Proactively Screening Machine Learning Pipelines with ArgusEyes.
• We open-sourced our prototype StreamDQ, a library built on top of Apache Flink for defining “unit tests for data”, which measure data quality in large data streams.
• I gave a talk about Automating and Optimizing Data-Centric What-If Analyses on Native ML Pipelines at ETH Zurich.
• I gave an in-depth talk about the inner workings of mlinspect at the Dutch Seminar on Data Systems Design.
• Sebastian and me gave a talk on Data Provenance as the Foundation for Data Governance at the virtual Data Centric AI workshop organised by Stanford and ETH Zuerich.
• We presented our work on mlinspect at the ICAI Lunch Meetup.
• mlinspect will be used for NYU’s course on Responsible Data Science to teach students about the importance of data preprocessing, making data distribution debugging part of their methodological toolkit.
• I joined UvA as Ph.D. student to work on data validation for ML pipelines.

I am a Ph.D. student at BIFOLD and TU Berlin in the DEEM Lab, conducting research at the intersection of data management and machine learning. I mainly publish at conferences like SIGMOD and VLDB.

My Ph.D. advisors are Sebastian Schelter and Paul Groth. I work on responsible data management (also in collaboration with Julia Stoyanovich). I spent the first three years of my Ph.D. at the University of Amsterdam in the Intelligent Data Engineering Lab, before Sebastian transitioned to TU Berlin. Before my Ph.D., I did my masters at TU Munich with Thomas Neumann and Alfons Kemper and focused on databases.

During my studies, I interned with Microsoft GSL, Amazon Research, Oracle Labs, and worked as a research assistant at TU Munich. I also interned and worked as a working student at TNG Technology Consulting in Munich and worked as a teaching assistant at University of Augsburg.

In the past, I have been working on deequ, a library for ‘unit-testing’ large datasets with Apache Spark, PGX, an in-memory graph analytics framework, and Umbra, a disk-based database with in-memory performance. Currently, I work on mlinspect and mlwhatif. The goal is to diagnose and mitigate robustness and reliability issues in machine learning pipelines.