EPFL Pre-ICML 2025 Research Highlights

Event details
Date | 03.07.2025 |
Hour | 14:00 › 16:00 |
Location | |
Category | Conferences - Seminars |
Event Language | English |
The ELLIS Lausanne Unit and the EPFL AI Center are pleased to host a Pre-ICML 2025 Research Highlights Session, highlighting recent contributions from the EPFL community to ICML 2025 and other leading machine learning conferences.
This session will feature a series of short 10-min presentations, offering an opportunity for researchers to share their work and engage with colleagues across the EPFL machine learning ecosystem. The presentations will be followed by a networking coffee, providing space for further discussion and new connections.
Programme
The full schedule, including confirmed speakers and talk titles, will be shared closer to the event date.
13:45–14:00 - Arrival & Welcome
- 14:00–15:00 — Talks (5 × 10 min)
- Suryanarayana Sankagiri, « Recommendations with Sparse Comparison Data: Provably Fast Convergence for Nonconvex Matrix Factorization »
- Yiming Qin, « DeFoG: Discrete Flow Matching for Graph Generation»
- Ilia Badanin, «Benchmarking Concept-Spilling Across Languages in LLMs »
- Agatha Duzan, « OS-Harm: A Benchmark for Measuring Safety of Computer Use Agent s»
- Filippo Bigi, « The dark side of the forces: assessing non-conservative models for atomistic machine learning »
- 15:00–15:10 — Break
- 15:10–16:00 — Talks (5 × 10 min)
- Emanuele Troiani, « Fundamental limits of learning in sequence multi-index models and deep attentionnetworks: High-dimensional asymptotics and sharp thresholds »
- Adytia Varre, « Learning In-context n-grams with Transformers: Sub-n-grams Are Near-stationaryPoints »
- Roman Bachmann, « FlexTok: Resampling Images into 1D Token Sequences of Flexible Length »
- Ben Lonnqvist, « Contour Integration Underlies Human-Like Vision »
- Hatef Otroshi, « Synthetic Face Datasets Generation via Latent Space Exploration from BrownianIdentity Diffusion »
We look forward to your participation in this session celebrating EPFL’s contributions to cutting-edge machine learning research.
Practical information
- Informed public
- Registration required
Organizer
- ELLIS Lausanne Unit & EPFL AI Center