Bayesian Optimization, Computability, Risk-Aware AI
A novel Bayesian optimization framework for black-box functions with uncertain or uncomputable outputs, integrating Gaussian process surrogates and halting probability modeling for risk-aware decision making in computationally intractable domains.
Vision Enhancement, Selective Dehazing, Object Detection
An adaptive deep learning pipeline for object detection in adverse weather, leveraging selective region dehazing and human visual system-inspired attention to maintain accuracy in fog, haze, and clear conditions.
January 2025
Started as MLE Intern, focusing on autonomous driving software stack and multimodal sensor fusion.
Read more →Published on Medium
Exploring the complexities and challenges in multi-modal image fusion, discussing why this seemingly straightforward task requires careful consideration and advanced techniques.
Read on Medium →Published on Medium
A deep dive into the world of tokenizers, exploring their importance in natural language processing and how they shape the way machines understand human language.
Read on Medium →Published on Medium
Understanding how Principal Component Analysis (PCA) can be applied to image recognition tasks, exploring dimensionality reduction and feature extraction techniques.
Read on Medium →Feel free to connect for collaborations or opportunities.
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