From Tab Autocomplete to Agents: The Mastery-Volume Tradeoff in AI Coding

There's a spectrum of AI coding—from tab autocomplete to agents that rewrite your codebase. The mode you choose determines how fast you ship and whether you'll understand what you shipped six months from now.

Essential vs Accidental Difficulty: Programming with LLMs for Process, Not Output

There's a right way and a wrong way to code with LLMs. Fixate on the output and you lose your grip on your codebase's internals. Here's how to use LLMs to stay in control.

My Ph.D. was Pointless, Noisy, and Exploitative–and I would do it again.

A systems-level look at a California-based STEM Ph.D. An honest reflection on exploitation, noise, and uncertainty in academia—and why I'd still do it again.

[Video] Design Out Helplessness: AI Interventions for Game Inclusivity

My PhD dissertation defense on using AI techniques to make games more accessible and inclusive, covering diagnostic taxonomy of failure, dynamic tutorials, and reinforcement learning-powered assistance methods.

[Video] The Today and Tomorrow of Machine Learning in the Games Industry

An overview of how machine learning is currently used in the games industry and a survey of exciting research projects that may shape its future—from testing and matchmaking to procedural generation and co-creation tools.

Designer-centered reinforcement learning

Making RL more accessible to game designers through preference learning, automatic reward balancing, and designer-friendly workflows. Research conducted during my internship at Microsoft Research Cambridge.

So You Want to Get a PhD?

Things I wish I had known before starting my PhD. A guide for those considering the academic path, covering the decision, the search, and the application process.