Leo Gao

Motivated high school engineering researcher seeking a hands-on summer internship in intelligent physical systems, robotics, or sustainable energy laboratories. Passionate about conducting research, performing experiments, and engaging in the design and optimization of integrated sensing and control systems. A strong foundation in engineering principles, combined with a commitment to innovation and sustainability, positions this candidate as an asset for any forward-thinking team. Prepared to contribute fresh ideas and a collaborative spirit to impactful projects.

Gao, Jianle (Leo).

“Multiscale Modeling of Friction Coefficients: A Review from Nanocontacts to Macroscopic Sliding.”

• Accepted Full Paper — AIMMEE 2025 (CPS Proceedings; CPCI submission pending)
• Single-author independent research study in multiscale physical modeling
• Conducted comparative analysis of atomistic, continuum, and hybrid friction frameworks
• Synthesized nanoscale and macroscopic modeling approaches across multiple physical scales

• Hydrogen-Based Renewable Energy System — Research Lead
• Massachusetts Science & Engineering Fair (MSEF)
• Designed and built a prototype renewable energy system integrating triboelectric nanogenerator (TENG), solar, and wind modules
• Developed MOSFET-based switching architecture for dynamic load control and energy routing
• Engineered system-level control logic for power regulation and storage pathways
• Conducted experimental voltage stabilization and performance testing
• Evaluated efficiency trade-offs between direct electrical output and hydrogen storage modeling
• Iteratively refined system architecture through debugging and component-level optimization
• FIRST Tech Challenge (FTC) Robotics — Team Captain & Lead Systems Engineer
• Boston Trinity Academy
• Led full-stack robot development including mechanical design, embedded control systems, and software integration
• Designed adjustable-angle flywheel mechanism optimized for multi-distance scoring
• Implemented PID-based velocity control for precision flywheel stabilization
• Built AprilTag-based computer vision system for real-time localization and autonomous alignment
• Integrated OpenCV vision pipeline with drivetrain control for closed-loop positioning
• Utilized pose estimation to compute field-relative coordinates and dynamically adjust robot trajectory
• Oversaw technical planning, subsystem coordination, and hardware procurement
• Achieved 3rd Place — Boston FTC Regional Competition