Autonomous-driving simulation engineer

From real-world datato reproducible evaluation loops.

I focus on closed-loop simulation, system-level evaluation, and long-tail scenario mining—connecting problem discovery, reproduction, and regression into one repeatable workflow.

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01DiscoverProblems worth analyzing
02DefineBoundaries and repro conditions
03ReproduceReplay or closed-loop simulation
04ValidateMetrics, comparison, regression

NOWCurrently building: an open-loop simulation pipelineOpen to autonomous-driving simulation roles

Work

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2026 - presentIndependent engineering: architecture, rule engine, and evaluation tooling

Trigger Engine: turning long-tail driving behavior into reviewable cases

A configurable rule engine for Waymo Open Dataset that mines high-value interactions from trajectories, maps, and traffic-light state, then exports frame-level evidence to a static viewer.

5 review tags / 183 events (viewer sample)
cut_in_confirmed: 21 scenes (viewer sample)

activePythonWaymo Open DatasetYAML DSL

2026 - presentIndependent engineering: reconstruction artifacts, NuRec runtime, and downstream evidence

NeuralSceneBridge: neural-scene reconstruction for downstream simulation

A reproducible scene-0061 NuRec reconstruction artifact, renderer handoff, dynamic-actor edit, and RGB/LiDAR diagnostic built around SensorsimService.

scene-0061 / 223 tracks / 6 cameras
V01-V03 replay/edit probes / V04 LiDAR diagnostic

activePythonNVIDIA NuRec / NREgRPC

2026 - presentIndependent engineering: CARLA/ROS2 open-loop testing, real inference integration, multimodal evaluation, and failure diagnosis

ClosedLoopBench: open-loop testing for real driving algorithms

A CARLA / ROS2 test bench that runs real TransFuser++ inference on synchronized replay data, uses A/B evaluation to diagnose dynamic LiDAR editability, and defines the blocked path to closed loop.

Current delivery: CARLA / ROS2 open-loop test + real TransFuser++ inference
M8: 39 scored frames x 3 routes / 68 dynamic actors

activePythonCARLAOpenSCENARIO / OpenDRIVE

Blog

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Aug 07, 2026From Detection Collapse to Root Cause: Debugging Dynamic LiDAR EditabilityA complete record of the ClosedLoopBench M8 debug path: controlled variables, coordinate fixes, cross-input A/B tests, 39-frame scale-up evaluation, and the live probe that exposed the dynamic LiDAR pose bug.

News

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Jul 14, 2026Hello, worldA fresh start for notes on autonomous-driving simulation, system evaluation, and data analysis.site