02 Work

Selected work in deployed hardware and controls-focused systems.

This is the core proof. Mainspring comes first, followed by Berkeley MPC and my Daimler Truck internship. The common thread is engineering at the boundary between physical behavior, controls, and decision-making tools.

Operating and improving a growing fleet of linear generators through troubleshooting, analytics, and internal tooling.

Reliability, telemetry, service operations, controls-aware diagnosis

2024 - Present

The work spans remote troubleshooting, fleet visibility, and Python workflows that help operations, controls, and mechanical teams make faster decisions around deployed energy hardware.

Mode Fleet ops + analytics
Stack Hardware, controls, telemetry
Goal Faster fleet decisions
  • Electromechanical systems
  • Remote fleet triage
  • Telemetry analysis
  • Python tooling

Built energy-aware control and validation workflows for an autonomous EV research platform.

MPC, vehicle energy modeling, validation, autonomy integration

2023 - 2024

I developed a real-time MPC workflow, built the supporting vehicle energy-modeling pipeline, and helped move the work toward on-vehicle validation instead of leaving it as a simulation-only result.

Mode Controls research
Stack MPC, modeling, EV integration
Goal Efficiency-aware autonomy
  • Model predictive control
  • Vehicle energy models
  • Autonomous EV platform
  • Physical validation

Supported EV platform analysis and physical design changes for an electric bus program.

EV packaging, analysis workflows, mechanical design support

2022

I built Python-based EV analysis workflows and supported physical platform changes through bracket and routing design work, combining practical hardware constraints with cleaner engineering analysis.

Mode EV platform internship
Stack Mechanical design, Python, packaging
Goal Better analysis and physical integration
  • Electric vehicle platforms
  • Mechanical packaging
  • Python analysis tooling
  • Design iteration