Vibu Vigneshwaran, Ph.D.

Machine Learning Scientist — applied AI in clinical oncology & medical imaging.

Translating rigorous academic research into deployable, responsible clinical AI. Specialized in architecting multi-agent reasoning systems, large language models (LLMs), and 3D vision foundation models for healthcare environments.

LinkedIn
Google Scholar
GitHub
Email

§ 01Oncology

Applied AI for clinical oncology — agentic workflows, decision support, and high-fidelity microscopy.

§ 02Causality

Causal generative models for medical imaging — moving beyond correlation toward interventional, explainable predictions.

§ 03Fairness & Bias in AI

Methods to audit, mitigate, and reason about bias in clinical AI systems.

§ 04Large-Data Rapid Image Processing

Vibu Vigneshwaran, Ph.D.

Applied AI for clinical oncology — agentic workflows, decision support, and high-fidelity microscopy.

OncoAssist

HER2 Status Prediction from Brain MRI

Cervical Cytology Cell Segmentation

Causal generative models for medical imaging — moving beyond correlation toward interventional, explainable predictions.

MACAW: Masked Causal Flow for Neuroimaging

TEA: Counterfactual Evaluation Framework

Causal Discovery: Cardiometabolic Risk & Gray Matter Atrophy

Methods to audit, mitigate, and reason about bias in clinical AI systems.

Causal Flow Harmonization for Multi-Site PD Classification

Counterfactual Shortcut Analysis for Protected Attributes

Pipelines that scale to terabyte-class imaging datasets without sacrificing scientific rigor.

Chunk-Based Pipeline for Coronary Vasculature Imaging