Olga Ovcharenko
PhD at TU Berlin 🇩🇪 | Master's at ETH Zurich 🇨🇭
- Reposted by Olga OvcharenkoOur paper "Towards a Real-World Aligned Benchmark for Unlearning in Recommender Systems" is accepted at the #RecSys2025 FAccTRec workshop. 🎉 We propose a realistic benchmark for machine unlearning that addresses real-world privacy challenges like GDPR's "right to be forgotten". @bifold.berlin
- ✨ Excited to present our workshop paper at DataWorld at #ICML2025 tomorrow 🇨🇦 We introduce the problem of detecting cross-modal errors in tabular data that originate from other modalities. Visit our poster: 📅 Saturday, July 19, 10:05 AM - 11:20 AM 📍 West Meeting Room 208-209
- Cross-modal errors span across multiple modaltities, like mismatched images or incorrect text fields, and are are an overlooked but critical issue in domains like e-Commerce and healthcare. Even with modern tools, large orgs struggle to catch cross-modal errors.
- Thanks to my supervisor @mersault.bsky.social! Paper: openreview.net/pdf?id=JJYHb... Code: github.com/OlgaOvcharen...
- 📊 Key findings: - Specialized single-cell frameworks and scFMs excel at uni-modal batch correction - Generic SSL methods like VICReg & SimCLR outperform on cell typing & multi-modal tasks - Masking emerges as the most universally effective augmentation strategy
- Thanks to all co-authors @flobarkmann.bsky.social, Philip Toma, Imant Daunhawer, Julia Vogt, @mersault.bsky.social, and @valboeva.bsky.social. 📄 Full paper: openreview.net/pdf?id=jnPHZ... 💻 Code: github.com/BoevaLab/scS...
- Reposted by Olga OvcharenkoThe DEEM Lab is at ICML this week for the first time, with two contributions! (1/3)
- Our paper "Towards Cross-Modal Error Detection with Tables and Images" was accepted for the DataWorld workshop at ICML'25! 🥳 Thanks to @mersault.bsky.social!
- Reposted by Olga OvcharenkoWe have a PhD opening in Berlin on "Responsible Data Engineering", with a focus on data preparation pipelines that optimize ML models along responsibility objectives. This is a fully-funded position at @bifold.berlin, co-supervised by Julia Stoyanovich from NYU. Details: deem.berlin#jobs-17725
- Reposted by Olga OvcharenkoWe 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!
- 📢 Our benchmark on self-supervised learning for single-cell data🧬 is accepted at the #NeurIPS2024 SSL workshop. We take a first step towards establishing best practices for SSL methods for single-cell data, and benchmark 8 SSL methods on 3 downstream tasks across 8 datasets.
- Reposted by Olga OvcharenkoWe have openings for student assistants in the DEEM Lab at @bifold.berlin. This is a great opportunity to work with PhD students, implement cool stuff, gather research experience and become a co-author of scientific publications :) deem.berlin#jobs-193487
- Reposted by Olga OvcharenkoOur vision "Towards Regaining Control over Messy ML Pipelines" was accepted for the DAIS workshop at ICDE! 🥳 Initial experiments show LLMs are promising for extracting declarative query plans from messy ML code. Joint work w/ @guangchen811.bsky.social @oovcharenko.bsky.social @mersault.bsky.social
- Reposted by Olga OvcharenkoWe have a PhD opening in Berlin on "Responsible Data Engineering", with a focus on efficiently creating, maintaining and evaluating datasets and pipelines for ML use cases. This is a fully-funded position at the newly founded DEEM Lab, as part of @bifold.berlin . deem.berlin#jobs-2225
- Reposted by Olga Ovcharenko📢If you are interested in single-cell foundation models (scFMs), stop by our poster (West 109) at the AiDrugX Workshop at Neurips 2024. We will present CancerFoundation, a scFM tailored for studying cancer biology🧬. Preprint: biorxiv.org/content/10.1...