Ph.D. candidate in Mechanical Engineering, specializing in advanced battery management systems (BMS), control, and robotics. Proven expertise in developing and validating real-time state estimation and prognostics algorithms for Li-ion systems, leveraging Extended Kalman Filters and machine learning. Successfully applied model-based design and data-driven techniques to enhance battery health monitoring, fault detection, and energy-optimal control for complex autonomous systems.
Graduate Researcher
Davis, CA, US
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Summary
Led advanced research in battery state estimation, diagnostics, and energy-optimal control for UAVs, contributing to real-time system performance and efficiency.
Highlights
Developed a Dual Extended Kalman Filter (EKF) framework for real-time SoC/SoH estimation, enabling online model adaptation for a satellite-based battery digital twin.
Architected and deployed a robust onboard estimation system for a 3-cell coin cell payload, effectively managing telemetry dropouts and thermal variations in resource-constrained embedded environments.
Applied MILP-based waypoint optimization for energy-minimal multi-rotor missions, achieving 3.9-9.4% energy savings over distance-minimizing approaches, validated through flight experiments.
Conducted comprehensive Li-ion coin cell test matrices spanning C-rates (0.2C-1C) and temperatures (0–40°C), developing automated MATLAB/Python pipelines for data processing and health trending.
Teaching Assistant, Mechanical and Aerospace Engineering
Davis, CA, US
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Summary
Facilitated learning and assessed student performance for core mechanical and aerospace engineering courses.
Highlights
Assisted in instruction for EME 108 (Measurement Systems), EME 109 (Experimental Methods for Thermal Fluids), and EME 50 (Manufacturing Processes), supporting over 100 students per quarter.
Developed and delivered supplementary instructional materials, clarifying complex concepts and improving student comprehension.
Evaluated assignments and provided constructive feedback, contributing to student learning outcomes and academic success.
Undergraduate Research Assistant
Davis, CA, US
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Summary
Contributed to robotic systems development for precision agriculture, focusing on hardware integration, control, and data analysis.
Highlights
Built "BugBot" automated system for optimized dispensing of predatory mites over strawberry fields with UAV swarms, programming Arduino, RaspberryPi, and PX4 microcontrollers.
Collected and analyzed large experimental datasets, providing critical insights for system optimization and project advancement.
Presented findings and weekly progress reports, facilitating informed decision-making and project milestone achievement.
Mechanical & Process Engineering Intern
San Jose, CA, US
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Summary
Supported engineering design, prototyping, and process optimization for production systems in a medical device context.
Highlights
Supported prototype build and validation using SolidWorks and Autodesk Fusion, ensuring design integrity and functionality for new products.
Wrote and debugged PLC ladder logic for production systems, developing systematic troubleshooting approaches that improved operational efficiency and reduced system downtime.
Collaborated with engineering teams to refine manufacturing processes, contributing to streamlined workflows and enhanced product quality.
Tutor, Academic Assistance and Tutoring Services
Davis, CA, US
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Summary
Provided academic support in core engineering subjects, developing educational materials to enhance student comprehension.
Highlights
Tutored undergraduate students in Dynamics, Fluid Mechanics, and Statics, improving their grasp of fundamental engineering principles and problem-solving abilities.
Developed quizzes and supplementary teaching materials, directly contributing to enhanced student comprehension and academic performance.
Provided individualized academic support, addressing specific learning challenges and fostering a deeper understanding of complex subjects.
Member
Davis, CA, US
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Summary
Collaborated on satellite attitude determination and control systems development, applying MATLAB/Python for simulation and analysis.
Highlights
Implemented TRIAD method for satellite attitude determination in MATLAB and Python, enhancing system accuracy for orbital mechanics simulations.
Developed an attitude determination and control systems simulator for a cubesat using Simulink, facilitating design validation and performance testing.
Contributed to critical design reviews and technical discussions, ensuring robust system architectures for satellite projects.
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Ph.D. Candidate
Mechanical Engineering
Grade: 3.8/4.0
Courses
Advanced Controls
State Estimation & Kalman Filtering
Machine Learning
Optimization
Battery Systems
Dynamic Systems Modeling
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Bachelor of Science
Mechanical Engineering
Grade: 3.64/4.0
Awarded By
UC Davis
Recognized for outstanding academic potential and research contributions.
Awarded By
UC Davis
Awarded for academic excellence and commitment to the field.
Awarded By
UC Davis College of Engineering
Achieved top 16% academic standing in the College of Engineering.
Published by
American Control Conference (ACC)
Summary
Research on applying Gaussian Process regression for machine learning-based detection of lithium plating in Li-ion cells.
Published by
AIAA SciTech Forum
Summary
Investigating methods to optimize multirotor drone efficiency by minimizing energy consumption during forward flight with varying payloads.
Published by
Aerospace Science and Technology
Summary
Focuses on optimizing 3D waypoint ordering to achieve energy-optimal operation for multirotor systems.
Published by
IEEE/RSJ IROS
Summary
Explores energy-optimal planning for UAV missions, challenging the assumption that minimum distance equals minimum energy.
Published by
Frontiers in Robotics and AI
Summary
Developed data-driven models for vermiculite distribution using UAVs for precision pest management applications.
SoC/SoH/SoP estimation, Extended Kalman Filter (EKF) design, Capacity fade modeling, Lithium plating detection, Incremental capacity analysis (ICA/DVA), Electrochemical modeling (ECM), Equivalent circuit models.
MATLAB/Simulink, Model-based software design, MiL/SiL validation, Parameter identification, System-level energy dynamics modeling.
Python (NumPy, SciPy, scikit-learn), Gaussian Process regression, Uncertainty quantification, Time-series analysis, Feature extraction from cycling data.
Li-ion cell characterization, Arbin battery cyclers, Test protocol design, HPPC, RPT, Fast-charge degradation studies, Temperature-dependent testing.
MATLAB, Python, C++.