PhD in Deep Learning with 7+ years across computer vision, medical imaging and large-scale ML systems. I design and train novel models from scratch — like DeepEMSeg for cryo-EM — and bring that depth to foundation models (SAM2, SAM3, ViT) in production.
I sit at the intersection of frontier research and shipped systems. For my PhD I designed and trained models from scratch — DeepEMSeg — to automatically segment structural features in cryo-EM protein maps, contributing novel methods for structural biology and drug discovery, published at IEEE conferences with Purdue's Kihara Lab.
That full-lifecycle range carries into industry: I both build models end-to-end and adapt foundation models for production — training custom architectures, deploying SAM2 and SAM3 into annotation pipelines, building CV systems from point-cloud extraction to inference, and driving ML optimization across segmentation, detection and LiDAR 3D projection.
Alongside industry, I teach graduate-level Deep Learning at the Costa Rica Institute of Technology — from training architectures from scratch (CNNs, U-Net, diffusion, GNNs) to modern multimodal systems (ViT, DINOv2, CLIP, Grounding DINO) — and continue research in biomedical imaging and HPC-parallelized image processing.
My PhD work: designed and trained deep-learning models from scratch to automatically segment structural features in 3D cryo-EM protein density maps — novel methods for structural biology and drug discovery, developed with Purdue's Kihara Lab.
Deployed Segment Anything foundation models in Databricks for ML-assisted pre-annotation, and built a SAM3 video tracker via Promptable Visual Segmentation — a single bounding box auto-tracks masks across full video sequences.
Designed and trained deep-learning models to automatically classify seismo-volcanic signals at Turrialba Volcano, in collaboration with OVSICORI — published at IEEE BIP 2023.
Looking for senior individual-contributor work in computer vision, multimodal AI, autonomous systems or medical imaging. Remote-first, available immediately.