DeepSleepBench
Benchmarking Neural Latent Representations on EEG data for Sleep Stage Classification
Projects
Showcased here are key projects highlighting my technical skills and problem-solving approach.
While my portfolio includes these recent research initiatives, most of my engineering work remains proprietary to my employers (spanning 1 year of professional experience, 5 internships, and 2 research collaborations). View my complete professional journey in my CV.
PyRecover
Robust distributed checkpointing and job management for multi-GPU SLURM workloads. Efficient, time-aware, and fault-tolerant training.
Research at ETH Zurich
Center of Technology and Innovation Management
SimpleSleepNet
A lightweight self-supervised contrastive-learning framework for EEG-based sleep stage classification