Agata Chudzińska
where else to find them
no profile links on file
what they talk about
where they keep going back
no series more than once — all 7 in the filters
on a stage with
never shared a talk
who talks about the same things
- Tarry Singh7 talks
- Nicola Pezzotti2 talks
- Djordje Hirs2 talks
- Matthew DiDonato2 talks
- J. Bubonja2 talks
- Irina Vidal Migallón7 talks
| title | conference | date |
|---|---|---|
| Building AI That Learns and Adapts: A Case Study in MRI Diagnostics | NDC Toronto 2026 | 2026-05-05 |
Project starts with 201 FCD MRIs plus ~100 normal and varied-pathology scans, preprocesses with brain tissue segmentation and two expert-inspired filters… | ||
| Building AI That Learns and Adapts: A Case Study in MRI Diagnostics | NDC London 2026 | 2026-01-26 |
201 MRI MRI series (plus 100 normals and 50 other pathologies) train a U-Net style segmentation pipeline; initial model detects about 70% of FCDs but produces… | ||
| Large Multimodal Models: Understanding the State of the Art in Compute | Build Stuff 2025 | 2025-12-03 |
Tracks the concrete shifts from CNNs to transformers and large multimodal stacks: ViT 16×16 patches replaces local convolutions, CLIP (400M image–text pairs)… | ||
| Building AI That Learns and Adapts: A Case Study in MRI Diagnostics | NDC AI 2025 | 2025-11-11 |
Case study builds an MRI pipeline to detect focal cortical dysplasias using a 201 MRI series dataset (192 slices per series) with T1 and FLAIR inputs, brain… | ||
| Building AI That Learns and Adapts: A Case Study in MRI Diagnostics | NDC Oslo 2025 | 2025-05-19 |
Project builds a U‑Net variant fed with T1 and FLAIR plus morphometric filters (junction, extension) and trains on an initial 201 MRI series (≈200 slices each)… | ||
| Building Adaptive AI for MRI Diagnostics: A Continual Learning Case Study | NDC Melbourne 2025 | 2025-04-29 |
A UNet encoder–decoder with a variational decoder and T1 and FLAIR plus junction/extension morphometrics processes MRIs to localize Focal Cortical Dysplasias… | ||
| Lessons Learned From Implementing Generative AI Solutions | DevConf 2023 | 2023-11-08 |
Practical checklist of what actually breaks when shipping LLM features: language ambiguity causes silent errors and nondeterministic grades; hallucinations… | ||
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