A personal reflection on four transformative years at Cloudfactory. Building data teams, solving hard problems, and growing through life and leadership. This post explores the human side of data work, from late-night debugging to mentoring and shaping a predictive-first culture.

A reflection on the evolving path from data science to AI engineering, and the things I miss.

A comprehensive exploration of Meta AI's Segment Anything Model (SAM), a foundation model designed to generalize across various segmentation tasks with minimal prompting, zero-shot and few-shot learning capabilities, and applications in a wide range of domains.

A primer at sampling methodologies, including probability and non-probability sampling methods, sample size determination, and minimizing bias.

I spoke at TEDx (DWIT College) on 'Nepal in the Loop'. The talk focused on the remarkable role Nepal is playing—and can play—in the global data landscape.

The paper introduces a novel architecture called residual networks (ResNets), which significantly improves deep neural network training by using skip connections to mitigate the vanishing gradient problem. This approach achieved state-of-the-art performance on several benchmarks, including the ImageNet dataset, and has become foundational in modern deep learning applications.