Curriculum Vitae
PhD Student in Computer Science · EPFL VILAB
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My research scales one model across many modalities and tasks, rather than building a separate specialized model for each.
MODUS, my recent work, is a single decoder that generates any modality from any other (RGB, depth, segmentation, text, and learned features alike), with no modality-specific heads, losses, or pipelines. What interests me is what a single unified model makes possible: modalities that strengthen each other when learned together, and the same model fluent across perception, generation, and reasoning. Earlier, I built widely-used systems for high-quality and open-world visual understanding, including HQ-SAM, Gaussian Grouping, Cascade-DETR, and EntitySAM.
Sources: Google Scholar and GitHub, as of June 2026.
* denotes equal contribution