Why I’m Starting my Personal Blog

Cool, let’s start with the why. Why am I starting this blog?

One thing I have realized is that I’ve been a bit shy to share my work with others. Too often, I’d hold back from sharing until something felt “finished” — which meant many ideas never left my notebook. The result: projects that could have sparked discussion or evolved into something bigger instead stayed hidden.

I think sharing ideas earlier is just as important as finishing them. It allows for feedback, collaboration, and learning in public. This blog is my attempt to reframe how I approach creative work: not as a polished showcase, but as a living record of experiments, progress, and lessons learned.

I want to treat ideas less like finished products and more like an idea garden — where some will sprout, some will bloom, and others may lie dormant until the right time. The value isn’t in perfection, but in visibility and growth.

Here’s how I’ve envisioned the blog, the blog will be split into three sections:

• blog: blog posts are usually some kind of analysis or exploration of a topic, it could be a data analysis, a technical post, a tutorial, a review, etc.
• projects: projects posts are usually some kind of project that I’ve worked on, it could be a side project, a personal project, a client project, etc.
• ideas: ideas posts are usually some kind of idea that I’ve had, it could be a new product idea, a new business idea, a new technology idea, etc.

What will be in the blog

Over the coming months, I’ll be writing in four main directions:

1. Machine learning for geospatial data - I’ve spent years working with maps, cities, and data. Now I’m interested in applying machine learning and multimodal models to geospatial data. Think clustering retail hubs, identifying urban hotspots, identifying perceptions from streetview or testing whether language models can “label” places in meaningful ways. These posts will be part technical experiment, part exploration of what geospatial ML can and can’t do.

2. Spatial analysis and the geography of AI - AI isn’t evenly distributed. The places with the talent, compute, and capital pull ahead, while others risk being left behind. I want to map and reflect on these inequalities — where AI adoption is happening, who benefits, and who doesn’t. This draws on my background in geography and social science, but with a sharp eye on today’s shifts.

3. Machine learning and engineering - Some of my writing will be practical: building pipelines, deploying models, wrestling with infrastructure. I want to document the messy process of moving from a notebook hack to a production system, and to be honest about the trade-offs along the way. These posts will lean more technical, but always connect back to why the work matters.

4. General reflections - Finally, I’ll be writing more openly about the personal side: navigating a career in the industry, and trying to find meaning in building things. These pieces are where I’ll step back and ask what all this work is for.

Taken together, these threads form a kind of constellation: technical experiments, social critique, and personal reflection. My hope is that by writing regularly, I’ll sharpen my thinking, share useful insights, and maybe connect with others asking similar questions.

If any of this resonates, I’d love for you to follow along.