Prof. Dr. Sebastian Schelter
Prof. Dr. Sebastian Schelter
Research Group Lead
Affiliation: BIFOLD
Research Group Lead | BIFOLD
Professor | Technische Universität Berlin
Sebastian Schelter is a Full Professor at the Berlin Institute on the Foundations of Learning and Data (BIFOLD) and Technische Universität Berlin. His research is focused on the intersection of data engineering and machine learning, with the goal of lowering the technical bar to efficiently and responsibly work with data. The research of his group is accompanied by efficient and scalable open source implementations, many of which are applied in real world use cases, for example in the Amazon Web Services cloud and in large European e-commerce platforms. In the past, he has been an assistant professor at the University of Amsterdam, a faculty fellow at New York University, a senior applied scientist at Amazon Research and a research intern at Twitter and IBM Almaden in California. His research contributions have been recognized with an ACM SIGMOD Systems Award, an ACM SIGMOD Best Demo Runner Up Award, and a Best Paper Runner Up Award from the Table Representation Learning workshop at NeurIPS.
2023 ACM SIGMOD Systems Award
2018 Moore-Sloan Data Science Fellowship
2015 Amazon Education Research Grant Award
2012 IBM Faculty Award (with Volker Markl)
Data Management for End-to-End Machine Learning
Responsible Data Management
Data processing in compliance with legal regulations
Automated validation of data at scale
Recommender Systems
Apache Software Foundation (emeritus)
Association for Computing Machinery (ACM)
Electronic Frontier Foundation
Deutscher Hochschulverband
Olga Ovcharenko, Luciano Duarte, Sebastian Schelter
SemPiper: Interactive Code Synthesis for Semantic Operators in Machine Learning Pipelines
Matthias Seeger, Zeyu Zhang, Vihang Patil, Konstantinos Benidis, Sebastian Schelter
Learning how to Forget: Fine-tuning for Long-Context Sparse Attention
Luciano Duarte, Olga Ovcharenko, Sebastian Schelter
ArtiFact: A Large-Scale Multi-Modal Cultural Heritage Dataset
Hao Chen, Arnab Phani, Sebastian Schelter
"Will This Data Break My Task?" - Interactive Synthesis of Task-Aware Data Unit Tests
Zeyu Zhang, Xue Li, Iacer Calixto, Paul Groth, Sebastian Schelter.
Beyond Scale and Generation: Understanding Language Model-based Entity Matching.
Photo-Recap: BEADS Kick-Off
BEADS launched its Tech Meetup Series with a kick-off event at BIFOLD, drawing around 60 participants from Berlin's data community for three talks from Snowflake, Databricks, and BIFOLD, followed by a lively Q&A and networking.
BIFOLD participated in SIGIR 2026
Researchers from BIFOLD and the University of Amsterdam presented ERASE, a new real-world-aligned benchmark for machine unlearning in recommender systems, at the 49th ACM SIGIR Conference in Melbourne, Australia, in 2026.
EDBT 2026 Conference Contributions
BIFOLD researchers will present several contributions at EDBT/ICDT 2026 in Tampere, Finland, including three research papers, three demos, and one workshop paper.
DEEM Lab Contributes to RecSys 2025
At RecSys 2025 in Prague, DEEM Lab will present a spotlight oral paper at the main conference on scalable data debugging using Data Shapley Values, as well as a workshop paper on realistic benchmarks for unlearning in recommender systems.
Researcher Spotlight: Dr. Arnab Phani
Dr. Arnab Phani is a Postdoctoral Researcher at BIFOLD, where he addresses data management challenges in modern AI. Building directly on his foundational PhD work at the DAMS Lab, his current research at the DEEM Lab focuses on enhancing runtime efficiency and fostering responsible data management practices across the entire machine learning pipeline - from data cleaning and validation to training and inference.
From Research to Practice
Barrie Kersbergen's PhD thesis on scalable session-based recommender systems powers real-time recommendations at one of Europe's leading retailers — impactful research with direct industry applications and open-source results, co-supervised by BIFOLD´s research group lead, Sebastian Schelter.
Looking Back at SIGMOD/PODS 2025 in Berlin
Between June 22nd and June 27th, Berlin hosted members of the international data management community at this year’s SIGMOD/PODS conference, one of the leading conferences in data management. With inspiring keynotes, vibrant exchange, and a record turnout, it was a fantastic week of science and collaboration. We are proud to have co-organized this landmark event!
SIGMOD 2025 Conference Contributions
BIFOLD researchers will present multiple contributions at the SIGMOD/PODS 2025 conference, scheduled for June 22–27, 2025, in Berlin.
ICDE 2025 Conference Contributions
BIFOLD researchers will participate in ICDE 2025, contributing three research papers. One of these papers will receive the Best Paper Award. The conference will be held May 19–23, 2025, in Hong Kong.
EDBT/ICDT 2025 Conference Contributions
Four BIFOLD research groups will take part in the EDBT/ICDT 2025 data management conference. They will present seven publications, including one that received the EDBT 2025 Best Paper Award. The conference is scheduled for 25–28 March 2025 in Barcelona, Spain.
BIFOLD researcher co-authors paper on next-generation Query Optimization at CIDR
At CIDR 2025 in Amsterdam, BIFOLD researcher Stefan Grafberger presents a paper co-authored during his Microsoft research internship. The study explores "Query Optimizer as a Service," promising simpler, more efficient data system development.
Publication Highlight - Snapcase
At the VLDB 2024 conference, the BIFOLD Research Group DEEM Lab introduced "Snapcase," a demo paper that addresses the concept of machine unlearning.
Reviewing VLDB 2024
Four BIFOLD research groups participated in the 50th International Conference on Very Large Databases in Guangzhou, China, taking place from August 26 to 30, 2024.
Newly appointed BIFOLD Professor: Sebastian Schelter
As of June 1st, 2024, Sebastian Schelter is a full Professor at the Berlin Institute for the Foundations of Learning and Data (BIFOLD) and Technische Universität Berlin. He chairs the Management of Data Science Processes group (DEEM Lab), whose research is focused on the intersection of data management and machine learning.
BIFOLD at the 2024 ACM SIGMOD/PODS Conference
BIFOLD researchers presented four research papers, two demos, one workshop paper and were of a panel at the 2024 ACM SIGMOD/ PODS Conference in Santiago, Chile.
8 researchers represented BIFOLD at SIGMOD 2023
Eight members of the BIFOLD team took the chance to showcase their recent work at SIGMOD 2023 in Seattle through a diverse array of presentations, including research papers, workshop papers, and a demo paper – all of them underscoring the institute's commitment to cutting-edge research in the field of data management.