Srikanth Narayanan Email & Phone Number

Arlington, Va, Us

Lead engineer for a small team of algorithm developers focused on advancing the perception stack for rendezvous and proximity operations. Delivered several production-level software stacks.Lead engineer for the autonomous system's vision-based perception stack for the Starliner spacecraft. Responsible for ownership, maintenance, and continuous improvement of the vision algorithm stack (C++), along with the development toolchain.Conducted performance tuning of Star tracker and inertial attitude determination algorithm. Provided mission control support for orbital flight tests and crewed flight test missions for the Starliner.Led the development and organization of all tools and the algorithm codebase using Git. Converted the entire codebase to modern build tools such as CMake, implemented continuous integration (CI) for all repositories, and trained the team on using Git and modern CI tools.Developed an algorithm for the Starliner to track the ISS Node 2 forward and Node 2 zenith docking ports using EO and IR sensors.Delivered a proposal for the autonomy stack architecture for the Lunar Terrain Vehicle.Developed several algorithms for space object tracking, pose estimation, and geometric deduction of segmentation maps for proprietary programs.Delivered a first-of-its-kind machine learning-based flight software stack, by integrating and deploying machine learning models using TensorFlow for proprietary programs. Improved the quality and speed of closed-loop testing by implementing a trajectory planner for a 6DOF robot to emulate spacecraft movement in a lab environment.

Portland, Or, Us

Led a systems team to build a use case scene catalog and functional requirements for a Level 4 autonomous tractor-trailer vehicle.Architected and developed a signal interface library between the Motion Control and Motion Planning modules.Led the development of the Vehicle Platform Fault Manager for a Level 4 tractor-trailer platform.Architected and developed a 3D simulation framework using ROS to evaluate path planning algorithms with tractor-trailer vehicle models.Implemented AUTOSAR CAN time synchronization algorithms and AUTOSAR CRC functions, including H2F, WCDMA8, and Profile 2.0, between the Motion Planning and Motion Control ECUs.Developed and implemented a local planning algorithm using Jerk Minimization Trajectory and a hierarchical state machine as the behavior planner.Developed a simulation framework to evaluate path planning algorithms with tractor-trailer vehicle models.Conducted a perception range and field of view study for the initial prototype truck.Designed and implemented an algorithm to measure the articulation angle between a tractor and trailer. This was a critical development to improve trailer off-tracking in autonomous mode.

Portland, Or, Us

Led the development and implementation of a radar and camera-based Active Brake Assist system for Class 8 trucks (SAE Level 2 system). This truck won the "Best Transportation Technology" award at CES.Led the functional, diagnostic, and reliability validation of radar and camera sensors, identifying and reducing false positive detections.Developed a SIL simulation toolchain to analyze the functional performance of the AEBS algorithm, achieving approximately a 10x speed improvement to previous tools.Performed hazard and risk analysis of false positive scenarios for the advanced emergency braking system, based on ISO 26262 standards.Improved sensor fusion performance of radar and camera sensors in various complex scenarios and environmental conditions.Identified critical use cases for collision scenarios involving pedestrians, improving the coverage of the Active Brake Assist system.Delivered a CAN library for analyzing large data sets, which was extensively integrated across the organization by multiple teams.Created and implemented a Kanban workflow process and task management system using JIRA.Mentored new team members on the software development process, helping them set goals and work toward achieving them.

Portland, Or, Us

Led the development and implementation of radar and camera based Active Brake Assist system for class 8 Trucks.Responsible for defining local market requirement specifications and use case performance scenarios for Active Brake Assist 4 and 5.Developed control models and optimized the warning, braking cascade on Active Brake Assist 4 for North America Market.Developed a distributed simulation tool chain to analyze the performance of Active Brake Assist 4, radar Sensor using field and functional test data. Increased the performance of the simulation speed by approximately 10X.Compiled use cases for testing possible collision scenarios with pedestrians.Developed software code base required to analyse CAN recordings, eliminating dependency on vector tools chain.Established strong relationship with Mercedes Benz trucks to resolve field and functional issues and provide inputs for algorithm improvements.

Aarhus, Dk

Aerodynamics Simulation Software DevelopmentLed the development of Rotor Analysis Toolkit, a simulation software framework that combines aerodynamic solvers to optimize the wind turbine rotor systems design. Achieved a reduction of 20% engineering man-hours (Approx 500h to 750h per Blade) due to faster iterative design.Integrated optimization methods with aerodynamic blade models that provided the optimum pitch schedules for new rotor designs.Collaborated with Aerodynamic Engineers to develop Airfoil performance models and created Python API for seamless access from the simulation framework.Developed rich interactive visualization workbench for wind tunnel test data.Sensor Systems EngineeringLed the design, integration and production deployment of system to sense blade load using fiber optics sensors which added to the product portfolio of turbines in new markets.Conducted extensive sensor testing for regression, hysteresis and endurance (Static, Fatigue and Environmental) that qualified highly reliable controls system hardware.Developed and implemented user-friendly calibration algorithms for load sensors.Led the development of accelerometer and acoustic sensor based structural health monitoring hardware and software for onshore wind turbine composite blades.Successfully integrated monitoring hardware to 2MW turbine platform SCADA system and managed commissioning of hardware to 100 turbines in Brazil, USA and France.Developed and implemented wind farm monitoring algorithms to detect blade fatigue load damage accumulation and established safe operating window for critical turbines.

Aarhus, Dk

The Vestas Graduate program is a two year international technical leadership program, in multiple countries.Drivetrain PlatformsLed the study to evaluate the hardware maturity of Oil Debris Sensors as a Gearbox monitoring system.Analysed oil debris level, vibration and swarf alarms for 3MW drivetrain using time series correlation analysis to quantify an early warning methodology for preventing unscheduled drivetrain maintenance.Generated Toolbox in Matlab for gearbox vibration monitoring algorithm and parsers to read sensor files.Managed and instrumented prototype drivetrain test setup. Measured and analysed durability test vibration performance and oil debris levels.Blades TechnologyLed loads assessment of transport frame on 55 meter carbon fiber blades.Developed Matlab scripts for vibration and strain signal processing (FFT, STFT and Wavelets) and statistical analysis of wind turbine blade data.Executed finite element modeling of adhesive joints and calculations of strain transfer and shear loading on bonded joints for load sensors.

Dearborn, Michigan, Us

Led powertrain design optimisation, cost out and engine component standardisation for powertrain models in Asia Pacific and AfricaAchieved a cost saving of 2.5 million USD over 3 years in optimised components design.Conducted testing of powertrain commodities such as exhaust and intake valves, thermostats, inductive sensors, exhaust gas recirculation actuators and drive belts.Analysed powertrain sensor data and established diagnostics and troubleshooting of prototype electrical hardware for CNG (Compressed Natural Gas) vehicle models.Benchmarking of powertrain components and engaged with supply chain team for commodity cost estimations.

Gurugram, Haryana, In

Led service and parts management for two major cities (Chennai and Hyderabad) in India. Technical support to resolve all field failures for gasoline and diesel powertrain across south region of India and achieved a significant reduction in service complaints and improved customer satisfaction rating.Improved turnaround time on field repairs, dealer management for service, spares and infrastructure.

Msc, Smart Product Design (Mechatronics)

Self Driving Car Engineer, Artificial Intelligence

Deep Learning Nanodegree, Deep Learning

Bachelor Of Engineering, Automotive Systems