CV
Education
PhD, Computer and Electrical Engineering (In-progress)
Cumulative GPA: 4.0/4.0
Relevant Coursework: Graduate Introduction to Robotics, Probability and Stochastic Processes, Detection and Estimation Theory, Linear Systems
Bachelor of Science, Computer and Electrical Engineering ()
Cumulative GPA: 3.86/4.0
Relevant Coursework: Digital Logic, Circuits II, Electronics, HW/SW System Integration, Control Systems
Research and Educational Experience
- Implemented C++ lidar data processing code for reducing energy consumption by 20% in autonomous vehicle following.
- Developed a lidar-based road surface profiling system to provide a lookahead signal to a control system for increasing ride safety and comfort.
- Mentored a simulation-based subteam (4–7 students) testing and verifying AV subsystems using MathWorks tools; delivered three industry presentations.
- Integrated AV subsystems using ROS, coordinate transforms, and path planning tools during competition events.
- Designed and completed an experiment to compare the ability of IMU and flex sensors to measure knee flexion.
- Collected and processed sensor data in real-time through Arduino and MATLAB.
Engineering Experience
- Implemented unit tests for a small satellite GNSS component.
- Organized wire harness for EGSE of Roman Space Telescope (RST) deployment, propulsion, and GSE subsystems.
- Automated safe-to-mate testing of RST wire harness connectors.
- Developed and implemented hooks for testing scoring algorithms optimizing task allocations in a MATLAB satellite simulation.
- Analyzed rocket/spacecraft trajectories using Python scripting.
- Wrote subsystem/unit-level tests for avionics components.
- Performed component testing and wire-harness troubleshooting.
- Led a team of 6–10 students developing hardware/software for spacecraft payload.
- Developed embedded software (Python, C/C++) from scratch.
- Tested SDRs and GNSS boards using Linux and scripting.
Publications
M. H. Schmelzle, L. Schexnaydre, N. Spike, D. Robinette, and J. Bos, “Facilitating Project-Based Learning Through Application of Established Pedagogical Methods in the SAE AutoDrive Challenge Student Design Competition,” presented at the WCX SAE World Congress Experience, SAE International, Apr. 2024. doi: 10.4271/2024-01-2075.
L. Schexnaydre, A. Poovalappil, M. Schmelzle, D. Robinette, and J. P. Bos, “Using automated vehicle positioning to improve efficiency in vehicle platooning,” in Autonomous Systems: Sensors, Processing, and Security for Ground, Air, Sea, and Space Vehicles and Infrastructure 2023, SPIE, Jun. 2023, pp. 202–211. doi: 10.1117/12.2664430.
A. Poovalappil, A. Robare, L. Schexnaydre, P. Santhosh, M. Bahramgiri, J. Bos, B. Chen, J. Naber, D. Robinette, “On-Road Investigation of Energy Saving Opportunity for Autonomous Light-Duty Vehicles through Automated Vehicle-Following in Safe Distance Scenarios,” presented at the WCX SAE World Congress Experience, SAE International, Mar. 2025. doi: 10.4271/2025-01-8029.
Presentations
L. Schexnaydre, “Efficient Perception Algorithms Can Save Energy for Autonomous Vehicles,” Graduate Research Colloquium, Michigan Technological University, Mar. 26, 2024.
L. Schexnaydre and A. Burr, “Tracking Lower Limb Movement Using an Integrated Sensor Approach,” Mid-Michigan Symposium for Undergraduate Research Experiences, Michigan State University, Jul. 24, 2018.
Skills
- Programming Languages: C/C++, Python, MATLAB
- Technologies: Git, Linux, Bitbucket, Github, LaTeX, ROS, Point Cloud Library