Hello! I'm Vaibhav Sinha

PhD Student in Computer Science at University of Cincinnati

I am particularly interested in developing models that can navigate complex, multimodal data, interpret nuanced contextual information, and perform robustly in challenging settings like small or skewed datasets. My research interests also align with topics such as model interpretability, fairness, and scalability, with a focus on building trustworthy AI systems for critical applications like healthcare and other areas.

Research Areas

Robust Machine Learning

Developing models that perform reliably by learning effectively from small, skewed, or noisy datasets.

Multimodal Representation

Designing models that can navigate complex, heterogeneous information streams to capture nuanced context.

Trustworthy AI

Ensuring machine learning systems are interpretable, fair, and transparent for deployment in critical environments.

Recent Publications

A Study of Feature Selection and Extraction Algorithms for Cancer Subtype Prediction

2022 IEEE International Conference for Advancement in Technology (ICONAT) • Jan 2022