Systems Group @ TU Darmstadt (Moved)
@tuda_systems
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We have moved to Bluesky (@tuda-systems.bsky.social) and LinkedIn (https://t.co/z1yMPgbbbF).
Darmstadt, Deutschland
Joined July 2019
Hello World! The Systems Group at TU Darmstadt is a collaboration of professors from the Computer Science department, pursuing research and teaching in systems topics together. @cbinnig
@zistvan Find out more at
informatik.tu-darmstadt.de
The Systems Group at TU Darmstadt – Hello World! The Systems Group at TU Darmstadt is a collaboration of professors from the Computer Science department, pursuing research and teaching in systems...
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🚨 Important Update! 🚨 We've moved our social presence to Bluesky and LinkedIn! Follow us on Bluesky @tuda-systems.bsky.social Connect with us on LinkedIn https://t.co/kKurqmO3Qm This isn't goodbye, it's see you there! 👋 #Bluesky #LinkedIn
linkedin.com
Systems Group @ TU Darmstadt | 403 followers on LinkedIn. Systems Group at the Technical University of Darmstadt, led by Carsten Binnig and Zsolt István. | Systems Group at the Technical University...
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Extremely proud to share that our paper "Towards Foundation Database Models" by Johannes Wehrstein (joint work with Google) has won the Best Paper Award at CIDR'25 @cidrdb! 🎖️🚀 This work revolutionizes how we realize learned database components. https://t.co/Wr3LMaDZZk
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Abstract submission deadline of @SIGMODConf 2026 (round 1) is in 2 days, 10 Jan, AoE. For this (1) All authors must have a registered CMT account with a valid ORCID. (2) All authors must declare their domain and their individual conflicts. Please check the CfP carefully.
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CMT for round 1 of ACM SIGMOD 2026 is now open. @SIGMODConf 2026 has a two-step submission process: all authors must have a registered CMT account with an ORCID & completed conflict of interest declarations by the abstract submission deadline (10 Jan 2025, 11:59 PM AoE).
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Happy to share that our work on WikiDBs - a large-scale corpus of relational databases - was accepted as a spotlight to the Dataset & Benchmarks track @NeurIPSConf. This is an important step for enabling foundation models on structured databases rather than text or images.
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I am very proud of my team who worked on this paper jointly with @SAP. 🎉 The results clearly show that more work is needed to make LLMs work on enterprise data. We will continue this line of work which we hope will lead to large tabular models for enterprise data.
Congratulations for the excellent work @tuda_systems!
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We proudly announce that our recent paper "LLMs for Data Engineering on Enterprise Data" has won the Best Short Paper award of the @TadaWorkshop @VLDB2024. The paper reveals the limitations of LLMs when faced with real-world scenarios like enterprise data. https://t.co/akeGOTDn2p
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It is a really great honor to receive the LOEWE top professorship for my research on building the next generation of AI-centered database systems: https://t.co/auZaVemQQE Many thanks to the State of Hesse & TU Darmstadt as well as @Hessian_AI and @CS_TUDarmstadt.
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We @tuda_systems had a great time last week in our team retreat at Darmstädter Haus in the Austrian Alps discussing the future of AI & cloud data management. Thanks a lot also to our external guests, Norman May and Ulf Brackmann from @SAP.
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Due to @SIGMODConf, I totally forgot to share that Sven Langenecker of @tuda_systems defended his PhD thesis on learned semantic type detection in tabular data lakes on June 4. Congrats, Sven! It was a pleasure working with you 🎉 🥳
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I am honored that we just received the best demo award for our demo at @SIGMODConf 2024. Congrats to my PhD student Matthias Urban @tuda_systems for this great work.
Today from 5:00 – 6:30 pm, we will show our CAESURA demo again. Come and see us in @SIGMODConf today if you want to know more on how we use LLMs as query planners for multi-modal data sources with tables, images and text.
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We proudly present our paper "Surprise Benchmarking: The Why, What, and How", accepted at the DBTest'24 workshop @SIGMODConf. The work resulted from the @dagstuhl Seminar 23441 on Ensuring the Reliability and Robustness of Database Management Systems. https://t.co/FzI17itsAi
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We proudly share that our paper "Rethinking Table Retrieval from Data Lakes" was accepted to the aiDM'24 workshop @SIGMODConf. The paper proposes the idea of fine-grained structured table retrieval to take on two limitations of existing table retrievers. https://t.co/Ici0urSXdl
dl.acm.org
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We are proud to announce that our recent paper "COSTREAM: Learned Cost Models for Operator Placement in Edge-Cloud Environments" has been accepted to ICDE'24. Roman Heinrich presents his work next week in the AI for Databases III session at ICDE. https://t.co/9JrTiVmnSI
arxiv.org
In this work, we present COSTREAM, a novel learned cost model for Distributed Stream Processing Systems that provides accurate predictions of the execution costs of a streaming query in an...
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🎉 #DAMON2024 turns 20 with a fresh new look! 🌟 Check out the re-designed website and the list of accepted papers at
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Did you really want to attend the VLDB #SummerSchool on #DataManagement in the #Cloud but you missed the application period? Hurry, there is still a chance!
We’re excited to meet the accepted students in Cluj! 🤩 For those who missed the application period, we opened a waiting list, in case someone cancels. 🚨 To secure a spot on the waiting list, you can apply before May 16th (midnight CEST) 👇 https://t.co/8O29fArjwE
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I was running my first Dagstuhl last week with David Bacon (Google), Dave Patterson (UC Berkeley), and Margo Seltzer @margo_seltzer (UBC) bringing together researchers on #CloudDatabases & #ComputerArchitecture : https://t.co/ME9r9ZP6iT. The was a fun & highly interesting week.
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We are happy to share that our paper "Parallel Processing of Temporal Anti-Joins in Memory" has been accepted to DASFAA'24! 🚀🚀 The paper introduces a novel approach to efficiently process temporal anti-joins, a task known for its complexity and scalability issues.
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Meet the speakers! Carsten Binnig - Professor@TU Darmstadt & Visiting Researcher@SystemsResearch@Google His research on scalable data systems on modern hardware & machine learning for scalable data systems received a Google Faculty Award & multiple Best Paper & Best Demo awards
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