About Me

Particle Assembly · Identity Through Geometry

CS Researcher & ML Engineer probing the geometry of machine learning — from sparse autoencoders to SSL representation theory and graph embeddings

Background

I'm a Computer Science student at the University of Washington's Paul G. Allen School of Computer Science & Engineering, maintaining a 4.0 GPA while doing research at the intersection of geometric deep learning, mechanistic interpretability, and representation theory.

Currently I'm working as an ML Research Engineer at a stealth AI startup, investigating how CNN inductive biases shape SSL representation geometry — diagnosing alignment, uniformity, and dimensional collapse across architectures. This summer I'll be joining Analog Devices as an AI/ML Intern focused on graph-based ML and embedding models for structured circuit data.

I was previously a Research Fellow at Algoverse AI, where I published RT-TopKSAE at ICLR 2026 — adapting the rotation trick to TopK sparse autoencoders, achieving 100% dictionary utilization vs. the baseline's 47%.

Manifold Hypothesis · Relational Bias · Force-Directed Clustering

Latent Synthesis

Skills as a structured latent space — related tools gravitate into clusters, edges encode learned associations. Hover a node to probe its neighborhood.

ML · AI

PyTorchPyTorch Lightningscikit-learnNumPyPandasLlamaIndex

Backend · DevOps

FastAPIFlaskDockerPostgreSQLAWSPyTestGitHub Actions

Languages

PythonC++TypeScriptJavaScriptJavaSQL

General Relativity · Geodesics · Spacetime Curvature

Temporal Curvature

Each role warps the career path around it — like mass curves spacetime. The glowing particle follows the geodesic.

Incoming · Summer 2026

Analog Devices

AI/ML Intern — Graph ML & Embeddings

Boston, MA

Graph-based ML and embedding models for structured circuit data.

Current · Feb 2026 → Present

Stealth AI Startup

ML Research Engineer

  • Investigating inductive bias effects of CNN architectures (ResNet, ConvNeXt) on SSL representation geometry — diagnosing alignment, uniformity, and dimensional collapse
  • Two-stage experimental pipeline on CIFAR/STL-10 and ImageNet with ResNet-50; developing loss regularization and augmentation interventions targeting SSL training failure modes
May 2025 – Mar 2026

Algoverse AI Research

Research Fellow · Remote

  • Designed distributed training infrastructure with PyTorch Lightning across 100+ model configurations, cutting experiment runtime by 30% through optimized data loading and gradient checkpointing
  • Built experiment tracking and evaluation framework processing 10K+ runs, enabling systematic ablations across hyperparameter sweeps to surface statistically reliable results
  • Adapted the rotation trick to TopK sparse autoencoders via custom PyTorch autograd functions, achieving 100% dictionary utilization vs. baseline's 47% and 6.1× lower feature overlap

University of Washington

Paul G. Allen School of Computer Science & Engineering

Bachelor of Science in Computer Science

Statistical Machine LearningAlgorithm Design & ComplexityAbstract Linear AlgebraReal AnalysisDiscrete Mathematics
Expected June 2028

4.0 GPA

Dean's List

Equivariance · Numerical Methods · Geometric Engineering

Projects

Equivariant VAE for Video Generation

PyTorchPyTorch LightningFastAPIDockerAWS

Designed a VAE enforcing equivariance in the latent space to ensure geometric transformations in input frames correspond to predictable latent trajectories, improving temporal consistency in generated video.

SVD & Eigendecomposition Engine

NumPyPython

Derived and implemented a full numerical linear algebra engine in pure NumPy — Gram-Schmidt QR factorization, power iteration with deflation, and two-sided Jacobi SVD. Validated against scikit-learn with residuals under 10⁻¹⁰.

Equivariance · Symmetry Groups · Invariant Representations

Structural Invariance

Community and recognition encoded as geometry. Toggle between force-directed graph and icosahedral simplicial complex — same data, different projections.

Achievements

  • ·NSF REU — AFUS Program, NC State · Autonomous systems, edge-assisted cooperative perception for CAVs under Dr. Wujie Wen (May – Jul 2026)
  • ·Kaggle Bronze Medal — Medical Image Segmentation · Top 100 teams (top 7%), 0.87 Dice score on UW-Madison MRI segmentation
  • ·Dean's List · 4.0 GPA
  • ·Published at ICLR 2026 @ Re-Align Research Workshop

Involvement

  • ·ColorStack Member
  • ·NSBE — National Society of Black Engineers
  • ·CodePath Technical Interview Prep
  • ·Open Source Contributor