Karthik Rengarajan Controls · Autonomy · Research
Cover image: laptop, autonomous vehicle model, sailboat model, and control diagrams.

University of Michigan–Dearborn · Robotic Motion Intelligence Lab

Senior Controls Engineer and Doctoral Candidate

Autonomous systems and robotics are the core of both my D.Eng. research and my industry work: dynamics, control systems, state estimation, motion control, and ISO 26262 functional safety for autonomous and electrified platforms.

Senior Controls Engineer, Nuro D.Eng. candidate, Computer Engineering
Download Resume U-M Email

Profile

Industry controls practice, academic questions.

Education

  • D.Eng., Computer Engineering / ECE, University of Michigan–Dearborn (Jan 2025 – present)
  • M.Eng., Mechanical Engineering — Controls, Texas A&M University, 2018, GPA 3.88/4.0
  • B.Tech., Mechanical Engineering, Amrita University, 2016, GPA 9.38/10.0 · SAEINDIA BAJA, 2013–2016

I am a Senior Controls Engineer and doctoral candidate specializing in autonomous systems and robotics. I develop novel control algorithms and hold a utility-patent portfolio cited by automotive OEMs.

At Nuro I am working on controls development for autonomous systems on the Uber Nuro Lucid Robotaxi program, including ISO 26262 safety requirement specifications, and researching on controls system, state estimation and system modeling. Before that I worked on full-cycle steer-by-wire at Nexteer, longitudinal and power-bridge controls for autonomous trucks at TuSimple, and hybrid powertrain controls at FEV for Stellantis: Jeep Compass and Renegade for the EMEA market, and the award-winning Jeep Wrangler PHEV for the US market.

My research home is the Robotic Motion Intelligence Lab at the University of Michigan–Dearborn, advised by Dr. Alireza Mohammadi. I am researching on advanced control for autonomous sailboat motion planning using nonlinear control and reinforcement learning.

Research focus

Doctoral research and methods.

Advisor: Dr. Alireza Mohammadi. Focus: advanced control strategies for autonomous sailboat motion planning and control using nonlinear control and reinforcement learning.

Marine autonomy

Sailboat motion planning and control

Wind-propelled craft are long-endurance sensing platforms and awkward control plants. I am preparing an Elsevier journal manuscript on this topic and I maintain a nonlinear Python simulator with MPC, MRAC, SMC, PID, and RL path-following.

Chassis and SbW

Steer-by-wire feel and disturbance rejection

Full-cycle SbW features: end of travel, misalignment, ADAS integration, vehicle disturbance rejection, torque-steer and brake-pull mitigation, driver-feel modification, and pinch detection on electronically stowable columns.

Methods

Control systems and state estimation

Sliding mode, backstepping, Kalman and particle filters, and policy learning compared on shared plants — cars in MATLAB/CarSim, sailboats in Python — rather than one-off demos.

Safety

ISO 26262 and verification

Safety requirement specifications on the robotaxi program; MIL, HIL, and in-vehicle V&V.

Patents

Inventions in steering, feel, and safety.

Nine utility patent applications (three granted, one published, one provisional), assigned primarily to Steering Solutions IP Holding Corporation. Cited by General Motors, Honda, and Samsung. Four public records are listed below.

Granted

Surface recognition during differential braking

US 12,391,257 B2 · granted 19 Aug 2025

Uses brake-to-steer commands, wheel response, and slip to infer surface friction so chassis features can adapt instead of assuming one road.

With Clinton L. Schumann and Michael S. Wyciechowski. Assignees: Steering Solutions IP Holding; Continental Automotive Systems.

Google Patents

Granted

Pinch detection for column adjustment actuators

US 12,570,351 B2 · granted 10 Mar 2026

Compares predicted and actual column velocity during powered rake/stow motion and flags pinching from the accumulated mismatch.

With Zaki Ryne. Assignee: Steering Solutions IP Holding Corporation.

Google Patents

Granted

Brake pull and torque-steer driver-feel mitigation

US 12,654,767 B2 · granted 16 Jun 2026 · pub. US 2025/0136174

Learns rack-force impact from brake-pull or torque-steer events and commands the handwheel actuator to oppose the predicted load, including on steer-by-wire.

With Scott T. Sanford. Assignee: Steering Solutions IP Holding Corporation.

Publication

Published application

Understeer / oversteer feel modification

US 2025/0178664 A1

Shapes handwheel torque from yaw-rate and yaw-acceleration error so the driver can feel limit understeer or oversteer through the steering interface.

With Scott T. Sanford, Sarin Kodappully, and Sujay Yegateela.

Google Patents

Repositories

Code I can point to.

Public work lives at github.com/karreng0318. Featured first; Udacity coursework is listed after.

Python

Sailboat_Sim

Nonlinear sailboat plant with heading controllers (Riccati, MRAC, SMC, PID) and PPO/SAC/TD3 path following, optional JONSWAP-style waves, and evaluation sweeps over wind headings.

Repository

MATLAB

PID vs LQR vs SMC vs MRAC

Side-by-side trajectory-tracking comparison for an autonomous car: classical, optimal, sliding-mode, and model-reference adaptive control on one plant.

Repository

C++

Simple_BMS_Cpp

Small battery-management experiment in C++ — a compact place to keep embedded-style control and estimation habits sharp.

Repository

Fork

Isaac Lab

Local work on NVIDIA Isaac Lab, the robot-learning framework on Isaac Sim, for simulation-heavy autonomy experiments.

Repository

Coursework

Self-driving car nanodegree

Lane finding, traffic-sign classification, behavioral cloning, and a kidnapped-vehicle particle filter — the Udacity sequence that sits under the industrial work.

Lanes Signs Cloning Localization

Writing

Papers and reports.

2026

Journal manuscript on autonomous sailboat guidance and control

Karthik Rengarajan and Alireza Mohammadi. Manuscript in preparation for submission to an Elsevier peer-reviewed journal.

In preparation
2026

Conference paper on advanced control systems

Co-author on an accepted conference abstract; full manuscript under review before presentation.

Abstract accepted
2026

Peer review, MECC 2026

Small amount of manuscript review for the Modeling, Estimation, and Control Conference.

Reviewer
2026

Condition Monitoring of Motorcycle Front Suspension Using Vibration Analysis and Machine Learning

Undergraduate final thesis, published as an open research report on Zenodo/CERN in May 2026 (v1). Experimental work from 2016: accelerometer features, model training, and classification of fork-oil faults.

Zenodo

Career path

From mechanical engineering to autonomous vehicle controls.

Education, then industry roles in electrified powertrain, autonomous trucks, steer-by-wire, and robotaxi motion control. Doctoral study runs in parallel from 2025.

  1. Amrita University
  2. Texas A&M
  3. FEV
  4. TuSimple
  5. Nexteer
  6. Nuro
  1. Education

    B.Tech., Mechanical Engineering · Amrita University

    GPA 9.38/10.0. Participated in SAEINDIA BAJA for three years (2013–2016). Foundation in mechanical systems that later supported dynamics and control work.

  2. Education

    M.Eng., Mechanical Engineering — Controls · Texas A&M University

    College Station, TX. GPA 3.88/4.0. Specialization in control systems.

  3. Industry

    Control Systems Engineer, Electrified Powertrain · FEV North America

    Auburn Hills, MI. Controls work for Stellantis on hybrid powertrains for Jeep Compass and Renegade (EMEA) and the award-winning Jeep Wrangler PHEV (US). Hybrid torque management, motor-speed PID for engine and clutch slip on PHEV/MHEV programs, start-stop focal point, DVP&R across MIL/SIL/HIL with dSPACE and ETAS-INCA, DFMEA during requirements development. Related patents were filed after I left.

  4. Industry

    Vehicle Controls Engineer, Integration · TuSimple

    Tucson, AZ. Longitudinal control, power management, and power-bridge controls for autonomous heavy-duty trucks.

  5. Industry

    System Controls Engineer II · Nexteer Automotive

    Auburn Hills, MI. Full-cycle steer-by-wire: end of travel, misalignment, ADAS integration, disturbance rejection, sliding-mode and backstepping chassis strategies in CarSim-MATLAB, torque-steer and brake-pull mitigation, pinch detection, AUTOSAR integration with Vector DaVinci and C. Utility patent portfolio from this period.

  6. Education

    D.Eng., Computer Engineering / ECE · University of Michigan–Dearborn

    Doctoral candidate advised by Dr. Alireza Mohammadi. Research on autonomous sailboat motion planning and control using nonlinear control and reinforcement learning.

  7. Industry

    Senior Controls Engineer · Nuro

    Working on controls development for autonomous systems on the Uber Nuro Lucid Robotaxi program. ISO 26262 safety requirement specifications, and researching on controls system, state estimation and system modeling.

Certifications

Safety, dynamics, and software training.

ISO 26262

Automotive Functional Safety Professional, SGS TUV (2021).

Dynamics

SAE Fundamentals of Vehicle Dynamics (2025).

Battery management

Coursera Algorithms for Battery Management Systems: SOC, SOH, and Li-ion parameter estimation (2020).

Udacity C++

C++ Nanodegree (2022).

Udacity Self-Driving Car Nanodegree

Self-Driving Car Engineer Nanodegree (2021).

Contact

Get in touch

Please reach out by email for professional or academic inquiries.

kartreng@umich.edu Download Resume