Research

Publications, papers, and research contributions in AI, healthcare, and representation learning.

Biomedical Imaging
Research (Publication)

CheX-Nomaly: Lung Abnormality Segmentation

Contrastive Siamese localization model disentangling disease labels from bounding boxes to improve generalization.

Methods: Contrastive learning, Siamese nets
Domain: Chest X-ray
Impact: arXiv paper, strong generalization
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Biomedical Imaging
Research (Publication)

Automated Coronary Calcium Scoring

Semi-supervised U-Net segmentation of non-gated CT scans for cardiovascular risk stratification.

Methods: U-Net, semi-supervised learning
Domain: CT Imaging
Impact: IEEE URTC publication
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Biomedical Imaging
Research (Theory)

False Negative vs False Positive Tradeoffs

Cost-sensitive analysis of error tradeoffs in binary medical ML tasks.

Methods: Loss weighting, evaluation theory
Domain: Medical ML
Impact: arXiv paper
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Biomedical Imaging
Research (Publication)

Brain Tumor Segmentation via Mask R-CNN

Image-subtraction-based Mask R-CNN for heterogeneous tumor segmentation.

Methods: Mask R-CNN, subtraction
Domain: Neuroimaging
Impact: arXiv paper
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Biomedical Imaging
Research (Publication)

PneumoXttention: Pneumonia Detection

Attention-augmented CNN to compensate for diagnostic variability in CXR interpretation.

Methods: CNNs, attention
Domain: Chest X-ray
Impact: IEEE ISPA paper
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Biomedical Imaging
Research Internship

Yale Oncology Lab – Eovist MRI GANs

Teacher–student GANs for liver MRI synthesis and segmentation enhancement (6k+ slices).

Methods: GANs, U-Net
Domain: MRI
Impact: +23% DICE
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Patient Embeddings
Research

Cardiovascular Patient Embeddings (Kellis Lab)

Unsupervised latent embeddings for 10k+ patients to identify high-risk cohorts.

Methods: Autoencoders, UMAP
Domain: Computational biology
Impact: Improved interpretability
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Patient Embeddings
Research Project

Alzheimer's MRI Latent Space Modeling

Latent MRI embeddings capturing disease progression and stage separability.

Methods: CNN embeddings
Domain: Neurodegeneration
Impact: Disease trajectory insight
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Time-Series & Signals
Research / Product

Water Consumption Disaggregation

Appliance-level inference from smart-meter time series using shape-based clustering.

Methods: K-Means, DTW
Domain: Utilities
Impact: 5–10% water reduction
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Time-Series & Signals
Research

Fraud Detection (Gupta Lab)

LSTM/Transformer sequence models on 1M+ transactions improving F1 and lowering false positives.

Methods: LSTM, Transformers
Domain: FinTech
Impact: +12% F1
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Knowledge Systems
Research

O-Health Symptom Extractor

Unsupervised clustering of 50k+ patient records to infer medical specializations.

Methods: Clustering, NLP
Domain: Healthcare
Impact: >60% accuracy
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