@andreaskipfi
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Professor @utn_nuremberg. Formerly @AWS, @MIT_CSAIL, @TU_Muenchen. Focused on building efficient, easy-to-use data systems.
Germany
Joined June 2009
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Excited to share that I’ll start as Professor of Data Systems @utn_nuremberg in early 2024! My research will explore the intersection of data systems and ML.
I’ll soon announce PhD and postdoc positions in my group.
Andreas Kipf retweeted
📣 🏆2026 SIGMOD Research Highlight Awards 🏆:
sigmod.org/sigmod-awards/sig…
DPconv: Super-Polynomially Faster Join Ordering
@mihail_sto, @andreaskipf
dl.acm.org/doi/10.1145/36988…
Automating Vectorized Distributed Graph Computation
Wenyue Zhao, Yang Cao, Peter Buneman, Jia Li, @ntarmos
dl.acm.org/doi/10.1145/36988…
AnyBlox: A Framework for Self-Decoding Datasets
Mateusz Gienieczko, @maxikuschewski, Thomas Neumann, Viktor Leis, @JanaGiceva
dl.acm.org/doi/10.14778/3749…
Rel: A Programming Language for Relational Data
@molhamaref, Paolo Guagliardo, @gkastrinis, Leonid Libkin, Victor Marsault, Wim Martens, Mary McGrath, Filip Murlak, Nathaniel Nystrom, Liat Peterfreund, Allison Rogers, Cristina Sirangelo, Domagoj Vrgoč, David Zhao, Abdul Zreika
dl.acm.org/doi/10.1145/37222…
MEMPHIS: Holistic Lineage-based Reuse and Memory Management for Multi-backend ML Systems
@ArnabPhani, @matthiasboehm7
openproceedings.org/2025/con…
Diva: Dynamic Range Filter for Var-Length Keys and Queries
Navid Eslami, @IoanaBercea, @niv_dayan
dl.acm.org/doi/10.14778/3749…
The Key to Effective UDF Optimization: Before Inlining, First Perform Outlining
Samuel Arch, Yuchen Liu, Todd C. Mowry, @pateljm, @andy_pavlo
dl.acm.org/doi/10.14778/3696…
Output-sensitive Conjunctive Query Evaluation
@ShaleenDeep, @HangdongZ79542, Austen Z. Fan, Paraschos Koutris
dl.acm.org/doi/10.1145/36958…
Output-Optimal Algorithms for Join-Aggregate Queries
Xiao Hu
dl.acm.org/doi/10.1145/37252…
Differentially Private Substring and Document Counting
Giulia Bernardini, @philipbille, @li_rtz, Teresa Anna Steiner
dl.acm.org/doi/10.1145/37252…
Congratulations to all the authors👏 👏 💐
#SIGMOD2026 #ACM #researchhighlight #SIGMODawards
Andreas Kipf retweeted
Can your cloud database predict underprovisioning before it even happens?
Meet ◒ xBound, the very first framework for join size lower bounds. xBound tells you how many tuples your SQL query will produce *at least*.
Brought to you by Microsoft GSL & @utndatasystems.
I hope you've had a great start to the year! I'm excited to announce our blog. We're kicking things off with a look back at everything that happened in 2025.
utndatasystems.github.io/blo…
Andreas Kipf retweeted
PoC customer bringing their own workload to test?
👉 Boost their LIKE/REGEX predicates with 🌰 string fingerprints.
Freshly presented at AIDB'25 @VLDBconf.
Paper: arxiv.org/abs/2507.10391
Code: github.com/utndatasystems/st…
Tuesday, 1:45 PM:
🪂 Parachute: Single-Pass Bi-Directional Information Passing
by Mihail Stoian (Research 8 — Westminster, 4F)
PDF: vldb.org/pvldb/vol18/p3299-s…
Code: github.com/utndatasystems/pa…
Andreas Kipf retweeted
Today we release Franca, a new vision Foundation Model that matches and sometimes outperforms DINOv2.
The data, the training code and the model weights (with intermediate checkpoints) are open-source, allowing everyone to build on this.
Methodologically, we introduce two new SSL components, one is a multi-granularity SK clustering loss that utilizes Matryoshka representations and a quick post-pretraining scheme to remove unwanted spatial biases.
This is the result of a close and fun collaboration @valeoai (in France) and @FunAILab (in Franconia)
The Data Systems Lab is seeking a motivated PhD candidate to join our team and work on foundation models for data compression.
🛠️ The position requires strong programming skills in C++ and Python.
We've already published early results in this space:
- Virtual, TRL @ NeurIPS'24: arxiv.org/pdf/2410.14066v3
- Virtual, EDBT'25 (Best Demo): openproceedings.org/2025/con…
🔗 Learn more about our research and team: utndatasystems.github.io/
Off to SIGMOD 2025 in Berlin! 🚄
Here’s our schedule:
Today, 4:20 PM:
💡 Redbench: A Benchmark Reflecting Real Workloads (aiDM)
Wed, 2:00 PM:
🏆 DPconv: Super-Polynomially Faster Join Ordering
Thu, 2:30 PM:
❄️ Pruning in Snowflake: Working Smarter, Not Harder
Come say hi! 👋
Parachute takes semi-join filtering to the next level!
Congrats to my PhD student @mihail_sto and thanks to our co-authors from MIT for initiating the project four years ago.
See you in London! 🇬🇧
Delighted to announce that Parachute 🪂 will appear at @VLDBconf! 🇬🇧
Compared to regular semi-join filtering, Parachute removes dangling tuples in a bi-directional manner by precomputing fingerprint columns.
Dangling tuples ⏬ = Join pruning ⏫.
📎 arxiv.org/abs/2506.13670
Fantastic news 🎖️
@mihail_sto will present DPconv at SIGMOD in Berlin this June.
Thrilled to share that we've received the Best Demonstration Award 🏆 at EDBT 2025!
Congratulations to my students @mihail_sto and Ping-Lin Kuo for their excellent work and dedication over the past few weeks—well deserved!
Paper: openproceedings.org/2025/con…
Andreas Kipf retweeted
Check out our poster tomorrow at EDBT Demo 🇪🇸!
🔥Update: Virtual v0.2 now supports S3 and 🤗 Parquet files - try it out!
pip install virtual-parquet.
We just released Redbench, a new benchmark that contains 30 analytical SQL workloads that can be used to benchmark workload-driven optimizations. Go check it out!
GitHub: github.com/utndatasystems/re…