Arnab Phani

The DEEM Lab is at ICML this week for the first time, with two contributions!

(1/3)

On Thursday, @oovcharenko.bsky.social will present her research on "scSSL-Bench: Benchmarking Self-Supervised Learning for Single-Cell Data". This paper is joint work with ETH Zuerich and was selected as a spotlight poster:

icml.cc/virtual/2025...

(2/3)

We have a PhD opening in Berlin on "Responsible Data Engineering", with a focus on data preparation for ML/AI systems.

This is a fully-funded position with salary level E13 at the newly founded DEEM Lab, as part of @bifold.berlin .

Details available at deem.berlin#jobs-2225

📢 Our extended benchmark on self-supervised learning for single-cell data, scSSL-Bench 🧬, is now accepted at ICML (spotlight)!

Thanks to all collaborators from @bifold.berlin and @ethzurich.bsky.social!

The @sigmod2025.bsky.social Programming Contest goes into another round. We (Bo Tang, Tilmann Rabl, and myself) just published the timeline and task overview:
sigmod-contest-2025.github.io/index.html

Thanks to Carlo Curino and @microsoft.com for the continued support.

Proud advisor moment: Today, my first PhD student @arnabphani.bsky.social successfully defended his PhD thesis in front of a great committee of Ana Klimovic, Tilmann Rabl, me, and @mersault.bsky.social (w/ summa cum laude - very good with distinction). Arnab is on the job market, so don't miss out.

This work is done at BIFOLD @xtraexer.bsky.social in collaboration with @matthiasboehm7.bsky.social.

MEMPHIS extends LIMA's lineage-based reuse to Spark and GPU. MEMPHIS offers a unified cache abstraction with multi-backend data objects, enabling reuse of Spark RDDs and GPU pointers, and a robust integration with Apache SystemDS compiler and runtime.

Glad to share, our paper MEMPHIS is accepted at EDBT 2025! 🎉 MEMPHIS extends the LIMA framework and proposes a holistic approach for fine-grained reuse of intermediates and memory management across multiple backends.
Paper: openproceedings.org/2025/conf/ed...