I am a researcher, designer, and builder driven by the pursuit of fundamental truths—elegant, universal principles that reveal beauty within complexity. My perspective is shaped by a fusion of disciplines: a deep understanding of AI/ML, a well-honed spatial intuition, and the appreciation of mathematical rigor. These facets intertwine, constantly sparking a dynamic interplay of ideas.

AI/ML RESEARCHER ARCHITECT OF SYSTEMS AND SPACES

PARTICLES LAB ｜ EXP-2

Simulated Annealing, Energy Minimization, and the Travelling Salesman Problem

EXP-1
Laplace Operator, Convolution, and the Propagation of Heat

PARTICLES LAB is a personal initiative where I use WebGL/WebGPU and GPU programming (GPGPU, GLSL, custom compute shaders) to prototype and visualize elegant computational ideas encountered in — and emerging from — my AI/ML research. Particle systems offer a natural embodiment of the elements and principles I care about: discreteness, locality, physics, emergence, and optimization.

EXP-2 is inspired by the simulated annealing algorithm and the travelling salesman problem. It demonstrates how a discrete optimization problem can be efficiently solved using a stochastic search algorithm that mimics the physical process of annealing. It is quite useful (and elegant) in finding global optima among large numbers of local optima. This experiment is currently WIP, and is associated with an ongoing research project.

References
Kirkpatrick et al. Optimization by simulated annealing. Science, 1983.
CMU CS. What is Simulated Annealing?.

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