ADAS Systems Engineer II

Turning ADAS validation, simulation, and safety into reliable engineering outcomes.

I design, integrate, and validate advanced driver assistance systems with a focus on model-based development, simulation workflows, sensor integration, SIL/HIL validation, and Python-based engineering tools. My work bridges virtual testing and real-world vehicle data to support safer, smarter, and more reliable automotive systems.

ADAS
MATLAB / Simulink
Functional Safety
SIL / HIL
Python
Sensor Fusion
About

Engineering with validation, clarity, and purpose

I am an ADAS Systems Engineer with experience developing, integrating, and validating advanced driver assistance and autonomous driving technologies. My background combines model-based development, vehicle control logic, diagnostic tooling, simulation, and test validation across both virtual environments and real-world vehicle programs.

Engineering Focus

Advanced driver assistance systems, validation workflows, ECU integration, real-time control logic, and safety-oriented engineering practices.

Technical Strengths

MATLAB/Simulink, RoadRunner, ROS, CAN diagnostics, Python automation, data analysis, and cross-functional collaboration with OEM and Tier 1 teams.

What Drives Me

I enjoy turning complex autonomous driving concepts into practical, testable, and road-ready systems that improve reliability and safety.

Experience

Recent roles across ADAS, validation, and tooling

A summary of my recent work across ADAS development, simulation, diagnostics, and engineering tool creation.

May 2025 – Present

ADAS Systems Engineer II · Astemo Americas, Inc.

Farmington Hills, Michigan

  • Designed, developed, and validated ADAS features including Adaptive Cruise Control and Lane Keeping Assist using MATLAB and Simulink.
  • Built simulation workflows with MathWorks RoadRunner and Unreal-connected environments to test control logic in realistic traffic scenarios.
  • Developed a Python/Qt-based Overhead ACC Viewer to synchronize video, CAN signals, and top-down vehicle visualization for faster feature analysis.
Aug 2021 – May 2025

ADAS Engineer · FEV North America Inc.

Auburn Hills, Michigan

  • Supported embedded C/C++ and ROS-based ADAS software integration in Linux environments, helping combine multiple software modules into robust vehicle systems.
  • Executed diagnostics, ECU troubleshooting, and performance analysis using CANoe, CANalyzer, CANape, CDA, and related tools.
  • Contributed to Level 3 autonomous driving programs through sensor integration, DVP execution, CAN data analysis, and standards-aligned validation for EURO NCAP, NHTSA, and ISO 26262 practices.
Oct 2020 – Aug 2021

Autonomous Technologies Intern · LHP Engineering Solutions

Pontiac, Michigan

  • Worked on throttle and steering control logic for obstacle avoidance and adaptive cruise control applications.
  • Developed stereo camera and radar sensor fusion modules in ROS and supported controller validation in SIL/HIL setups.
  • Assisted with Level 2 self-driving vehicle testing, road data collection, and fault reporting across varied routes and climate conditions.
Projects

Featured engineering work

Selected work that best represents my ADAS, simulation, and engineering tool development experience.

Featured Project

Overhead ACC Viewer

Built a Python/Qt application to review ADAS test data by synchronizing video playback, CAN waveforms, and top-down vehicle and lane animations. Added support for MF4 and BLF decoding to improve analysis of ACC-related signals.

Python PyQt ASAMMDF CAN Data
Simulation

Virtual ADAS Validation Environment

Developed and validated control logic for features such as ACC and LKA using MATLAB, Simulink, RoadRunner, and Unreal-connected simulation workflows to test performance in realistic virtual traffic environments.

MATLAB Simulink RoadRunner Unreal
Validation

ADAS Sensor & ECU Validation

Supported integration, diagnostics, and performance testing of ADAS ECUs and sensors including radar, LiDAR, cameras, and ultrasonic systems using structured validation workflows and CAN-based diagnostic tools.

CANoe Diagnostics Sensor Fusion Validation
Skills

Tools I use across development and validation

A focused snapshot of the tools and domains I work with most often.

ADAS & Validation

ACC, LKA, AEB, ADAS Testing (L0–L3), SIL/HIL validation, sensor fusion, ECU validation, DVP execution, Functional Safety, ISO 26262, NHTSA, EURO NCAP

Software & Simulation

MATLAB, Simulink, MathWorks RoadRunner, ROS, Linux, CarMaker, model-based design, vehicle control logic

Diagnostics & Data Tools

CANoe, CANalyzer, CANape, CDA, Kvaser CAN, AB Dynamics, MF4/BLF decoding, data logging and root-cause analysis

Programming & Engineering Tools

Python, C/C++, PyQt/PySide, OpenCV, openpyxl, ASAMMDF, SolidWorks, HyperMesh, ANSYS, MotoHawk, MotoTune

Credentials

Certifications and education

Professional certifications and academic background supporting my engineering work.

Certifications

  • Certified SolidWorks Associate (CSWA)
  • Certified SolidWorks Professional (CSWP)
  • ISO 26262 Functional Safety Training
  • LaunchPad 80 / Autonomous Pedestrian Testing Robot Training
  • Steering & Combined Brake and Accelerator Robot (CBAR) System Training

Education

  • Master of Science in Mechanical Engineering — Fairfield University, Connecticut
  • Bachelor of Science in Mechanical Engineering — JNTUH, Hyderabad, India
Contact

Let’s connect

I’m open to engineering opportunities, collaboration, and professional networking.

Email

sunnyrajmohan16@gmail.com

Send Email

LinkedIn

Connect with me professionally and view my background.

View LinkedIn

Location

Michigan, USA

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