Robotics · Autonomy · Estimation

Engineering
Intelligent Machines

I am Sinan Karahan, a technical leader and robotics scientist who transforms advanced mathematical theory into production systems for autonomous vehicles, mobile devices, spacecraft, industrial robotics, and embedded intelligent products.

35+Years in advanced engineering
20Engineers led at XPeng
9+Patent applications filed
Sensor FusionLocalizationRobot ControlNavigationPath PlanningEmbedded SystemsSensor CalibrationAutonomous Driving Sensor FusionLocalizationRobot ControlNavigationPath PlanningEmbedded SystemsSensor CalibrationAutonomous Driving

About

From mathematical foundations to systems that ship.

My career spans robotics, aerospace, autonomous driving, consumer electronics, industrial automation, and university teaching.

I specialize in sensor fusion, filtering and estimation, calibration, localization, robot kinematics and dynamics, motion planning, control, simulation, signal processing, optimization, and machine learning. I have repeatedly moved algorithms from concept and simulation into embedded, real-time, production environments.

My work includes pioneering 9-axis sensor fusion for iPhone, leading production localization for autonomous trucks, directing spacecraft sensor and actuator development, building autonomous driving teams, and teaching graduate-level robotics.

Selected impact

Technologies brought from research into the real world.

Five domains that define the breadth of my work.

Consumer Electronics

Motion intelligence at product scale

Developed the first production 9-axis Kalman Filter sensor fusion system for iPhone and delivered embedded motion, calibration, and activity algorithms across multiple generations of sensor products.

AppleTDK InvenSenseSensor Platforms

Autonomous Driving

Localization, perception, planning, and control

Led and developed multi-sensor systems using GNSS, IMU, LiDAR, radar, camera, and wheel odometry for autonomous vehicles and trucks.

GatikXPengSERES

Space & Aerospace

Navigation, control, and simulation beyond Earth

Directed spacecraft sensor and actuator development, modeled satellite dynamics and orbital systems, and contributed to NASA air-traffic optimization research.

E-SpaceNASA AmesOctant

Robotics

Machines that interact with people and the physical world

Designed kinematics, dynamics, control, trajectory planning, and force-based exercise algorithms for industrial, rehabilitation, animation, and medical robotics.

Research & Education

Teaching and advancing the mathematical core

Ph.D. research in nonlinear systems, graduate robotics instruction at Santa Clara University, and long-standing professional engagement through IEEE, ASME, Sigma Xi, and IFAC.

UC DavisSanta Clara UniversityIEEE

Technical expertise

Deep foundations. Production discipline.

A

Estimation & Sensor Fusion

  • Kalman Filters
  • Extended Kalman Filters
  • Unscented Kalman Filters
  • Particle Filters
  • Bayesian Estimation
  • Sensor Calibration
B

Robotics & Control

  • Robot Kinematics
  • Robot Dynamics
  • Trajectory Planning
  • Path Planning
  • Feedback Control
  • Model Predictive Control
C

Autonomous Systems

  • Localization
  • Navigation
  • Perception
  • Map Matching
  • GNSS / IMU Integration
  • LiDAR / Radar / Camera Fusion
D

Implementation & Simulation

  • C / C++
  • MATLAB / Simulink
  • ROS / ROS 2
  • Embedded Real-Time Systems
  • Monte Carlo Simulation
  • Hardware-in-the-Loop
OptimizationSignal ProcessingMachine LearningOpenCVMotion AlgorithmsAttitude EstimationOrbital DynamicsGNCSensor CharacterizationIndoor PositioningWi-Fi / Bluetooth BeaconsPedestrian Dead Reckoning

Career timeline

Engineering leadership across four decades.

Filter the timeline by domain, then open any role for a concise account of the work, technical focus, and impact.

2024 — Present

Autonomous systems · Localization

Gatik

Technical Lead, Localization

Leads production localization and navigation work for autonomous middle-mile trucks, combining multiple sensing modalities in real-time systems.

  • Develops localization software using GNSS, IMU, LiDAR, camera, and wheel odometry.
  • Applies probabilistic estimation and sensor-fusion methods to production autonomous-driving systems.
  • Works across algorithm design, simulation, software implementation, testing, and vehicle integration.
LocalizationGNSSIMULiDARCameraROS 2Kalman Filters
2022 — 2023

Space systems · GNC

E-Space

Director, GNC Sensors and Actuators Design

2019 — 2022

Sensors · Embedded algorithms

TDK InvenSense

Director, Algorithms

2018 — 2019

Autonomous driving · Technical leadership

XPeng Motors

Principal Research Scientist

2017 — 2018

Autonomous driving · Localization

SERES

Autonomous-Driving Research and Development

2016 — 2017

Industrial robotics · Control

Carbon Robotics

Director of Robotics and Control

2014 — 2016

Touch sensing · Embedded algorithms

NextInput

Algorithm and Sensor Development

2014 — 2015

Autonomous aerial systems

Nixie

Navigation and Control Development

2012 — 2014

Motion sensing · Production algorithms

InvenSense

Algorithm Leadership

2010 — 2012
2009 — 2010

Context awareness · Mobile sensing

Sensor Platforms

Sensor-Fusion and Context Algorithms

2006 — 2009

Aerospace research · Optimization

NASA Ames Research Center

Principal Research Scientist

Earlier career

Robotics · Simulation · Education

Foundational Roles

Hansen Medical, Motion Factory, Santa Clara University, UC Davis, and others

Technical portfolio

Systems built where estimation meets reality.

Selected engineering programs organized by technical challenge rather than employer. Descriptions stay at a public, non-confidential level while showing the methods, system constraints, and leadership scope behind the work.

01

Production autonomy

Localization for autonomous trucks

Reliable vehicle-state estimation across real roads, imperfect sensors, and production constraints.

Challenge

Fuse complementary sensing modalities while maintaining accuracy, continuity, observability, and diagnosability in real time.

Approach

Probabilistic estimation using GNSS, IMU, LiDAR, cameras, and wheel odometry, supported by simulation, replay, testing, and vehicle integration.

Role

Technical leadership spanning algorithm architecture, software implementation, validation strategy, and cross-functional system integration.

GNSSIMULiDARCameraROS 2Kalman Filtering
02

Embedded intelligence

Production 9-axis motion estimation

Orientation and motion estimation combining accelerometer, gyroscope, and magnetometer measurements in resource-constrained consumer devices.

Engineering focusCalibration, robustness, embedded implementation, validation, and production deployment.
9-Axis FusionCompass CalibrationCoreMotionEmbedded Algorithms
03

Space systems

Spacecraft GNC sensors and actuators

Sensor and actuator design viewed as part of a complete guidance, navigation, and control architecture.

Engineering focusPerformance modeling, characterization, calibration, estimation, simulation, and requirement flow-down.
GNCAttitude EstimationSensorsActuatorsSimulation
04

Robotic systems

Medical and rehabilitation robotics

Robotic mechanisms and control systems designed around human interaction, physical constraints, and safety.

Engineering focusKinematics, dynamics, nonlinear systems, force interaction, control, and a NIH-funded 6-DOF physical-therapy robot.
6-DOF RoboticsDynamicsControlHuman-Robot Interaction
05

Industrial robotics

Planning and control for robotic platforms

System-level development connecting mathematical models to physical robot behavior and product constraints.

Engineering focusKinematics, dynamics, trajectory generation, optimization, simulation, controls, and hardware integration.
Motion PlanningTrajectory GenerationOptimizationControl
06

Technical organization

Building multidisciplinary autonomy teams

Leadership across localization, perception, planning, control, simulation, and vehicle integration.

Engineering focusTechnical direction, architecture, hiring, mentoring, execution, and alignment between research and production.
LeadershipArchitectureSimulationVehicle Integration

Technology matrix

From mathematical model to deployed system.

Estimation

Kalman filters, nonlinear estimation, sensor fusion, calibration, state estimation, localization, attitude estimation

Robotics

Kinematics, dynamics, motion planning, trajectory generation, control, simulation, optimization

Sensing

IMU, GNSS, LiDAR, cameras, magnetometers, wheel odometry, force and touch sensors

Implementation

C++, Python, MATLAB/Simulink, ROS and ROS 2, Linux, embedded and real-time systems

Engineering philosophy

First principles. Measurable behavior. Production discipline.

I approach intelligent machines as complete systems: sensing, estimation, planning, control, software, hardware, and validation must reinforce one another.

Strong algorithms matter. Strong interfaces, observability, testability, and failure handling are what make them dependable.

Professional activities

Research, teaching, and technical community.

  • Adjunct Professor of graduate robotics at Santa Clara University
  • IEEE Lifetime Member
  • Member of ASME and Sigma Xi
  • Research background spanning robotics, nonlinear systems, aerospace optimization, and sensor fusion

Contact

Let’s build the next intelligent system.

Open to senior technical leadership, robotics, autonomous systems, localization, estimation, sensor fusion, and consulting opportunities.