I build models that predict the physical world, and study where they stop being right.

Autonomous systems and multimodal detection in practice; world models and representation learning in research.

Junior ML Engineer at Hertz New Technologies.

Experience and education

ObservedModel rolloutPrediction errorHénon map. The rollout starts 10−6 away from the true state. The error stays invisible for 23 steps, then compounds. Anchor is my attempt at closing that gap.

Selected work

Anchor

Path consistency for latent world models

A self-supervised mechanism that penalizes disagreement between horizon-conditioned direct prediction and autoregressive rollout, aimed at reducing compound error in latent rollouts. Designed as an importable component rather than a standalone architecture.

Status
In progress
Topics
world models, self-supervised learning

Drone Audio Detection

Acoustic early warning, and where it breaks

A Random Forest classifier on MFCC features with local inference, reaching strong held-out metrics that then failed on real recordings while misflagging ambient noise. The generalization gap, not the accuracy number, is the finding.

Status
2026
Topics
audio ML, sim-to-real, embedded

All projects

Achievements

Detect & Defend — European Defence Tech Hackathon

Built DetMesh, a multimodal counter-UAS system combining audio, RF, and vision for drone detection. The work later became Umbris.

Result
1st place
Year
2026

Spaceshield Hack

AgloMeter, a data-driven analysis of transport exclusion and accessibility. Led the team as project manager.

Result
1st place, Space category
Year
2026

All achievements