CV

Zachary Bucknor-Smartt

College Station, TX 77845
LinkedIn | Email | (210) 508-0376

Education

Texas A&M University | College Station, TX
PhD Mechanical Engineering, Aviles-Johnson Fellow
Anticipated Graduation: May 2030

Texas A&M University | College Station, TX
BSc. Mechanical Engineering, Undergraduate Thesis Research Scholar
Graduation: May 2025

• Junior/Senior GPA: 3.66/4.0
• Major GPA: 3.5

Relevant Coursework:
Mechanics of Robotic Manipulators, Dynamic Systems and Controls, Numerical Methods & Optimization, Machine Learning, Complex Analysis, Research, and DSA (MIT OCW)

Professional Summary

Dedicated and results-driven mechanical engineering student with a strong focus on software and controls, particularly interested in areas of loco-manipulation, trajectory optimization, model predictive control, adaptive/robust control, and athletic intelligence. Proven ability to lead research initiatives, independently create and lead undergraduate research labs, collaborate on complex multidisciplinary projects, and contribute to peer-reviewed publications.

Research Experience

Human-Empowering Robotics and Control Laboratory

Graduate Research Fellow | August 2025 - Present
Undergraduate Researcher | November 2023 – May 2025

Project 4: Direct User Control of Lower Limb Exoskeletons 2| May 2025 – Present

• Serving as a graduate advisor for 5 undergraduate students with hopes of continuing the scope of my thesis.

Project 3: Trajectory Optimization for Multi-Contact Locomanipulation in Space | August 2025 – Present

• Simulation of stable satellite maneuvers and manipulator control gains for multi-contact impedance control in space.

Project 2: Direct User Control of Lower Limb Exoskeletons | May 2024 – Present

• Develop novel torque control methodologies for knee exoskeletons, resulting in statistically significant claims (p « .001) that biological knee torque may not be what exoskeleton users desire when given direct user control.
• Develop open-source hardware for teleoperation of exoskeletons, “handle-like” hardware is portable to any robotic device and supports force control and teleoperation with IMU, analog buttons, spring-loaded force feedback triggers, and LED’s.
• Implemented high-level control strategies using Extended Kalman Filters to extract environmental information from thigh and shin angles.
• Designed and manufactured a belt-fed constant-length tension system for lower limb exoskeletons.
• Efforts resulted in thesis publication and a “best paper award” at IEEE SIEDS 2025.

Project 2: Direct User Control of Lower Limb Exoskeletons | May 2024 – Present

• Develop novel torque control methodologies for knee exoskeletons, resulting in statistically significant claims (p « .001) that biological knee torque may not be what exoskeleton users desire when given direct user control.
• Develop open-source hardware for teleoperation of exoskeletons, “handle-like” hardware is portable to any robotic device and supports force control and teleoperation with IMU, analog buttons, spring-loaded force feedback triggers, and LED’s.
• Implemented high-level control strategies using Extended Kalman Filters to extract environmental information from thigh and shin angles.
• Designed and manufactured a belt-fed constant-length tension system for lower limb exoskeletons.
• Efforts resulted in thesis publication and a “best paper award” at IEEE SIEDS 2025.

Project 1: Strength Amplification Arm | November 2023 – Present

• Theoretically and empirically prove stability for novel force control methods and communicate viability to scientific community through academic papers.
• Design, prototype, and implement various end-effectors on the Haption 6D HF TAO robot that incorporates human force- torque sensing when coupled with the environment.
• Contribute to the creation of C++ libraries around the SRI M35 series of force torque sensors and the Haption 6D HF TAO robot. Accomplished end effector force transformations utilizing quaternions, data IO, high pass filtering, sensor calibration, and real time single degree of freedom strength amplification.

Stanford Research Institute Interational (SRI International): NASA JPL Contract

Robotics Software and Control Engineering Intern | April 2025 – August 2025

• Implemented fully embedded Cartesian force feedback control of diamagnetically levitated micro-robots.
• Designed and built a high-precision sensor characterization testbed (micrometer-level accuracy) to validate custom linear magnetic encoders for force-controlled diamagnetic levitation robot swarms.
• Modeled and validated complex magnetic levitation dynamics, implemented closed-loop controllers, and simulated multi-robot swarm behavior using Isaac Sim and Magpylib.
• Developed and fabricated custom PCBs (Altium Designer) to perform systematic physical parameter sweeps for optimizing magnetic encoder pattern design.
• Designed multiple iterations of multi-dof Hall effect sensor PCB’s for real-time robot position/phase feedback in all cartesian directions.
• Built a custom Python-based physics simulator to evaluate levitation dynamics and feedback control algorithms prior to high- fidelity simulation.
• Served as a technical point of contact for feedback control of diamagnetically levitated microrobots for NASA JPL, attending meetings and ensuring effective transfer of my software, CAD, and PCB designs so that thermal-vac testing may occur seamlessly.

Robotics and Automation Design Laboratory (Bush Combat Development Complex)

Undergraduate Researcher | May 2024 – August 2024

• Developed state of the art strength amplification controllers in C++ for manipulators (Haption 6D HF TAO + Kuka Iiwa) in multiple degrees of freedom using “virtual” spring-mass-damper systems characterized by human-environment compliance.
• Utilized Python to perform system identification on MIMO robot systems to characterize compliance, force transfer, and true end-effector position.
• Led undergraduate students in authoring a journal paper and thesis in novel exoskeleton control.

Rani Therapeutics

Robotics R&D Engineering Intern | May 2023 – August 2023

• Designed a 3-axis gantry robot for microscale operations using Python, OpenCV, SolidWorks, and C++.
• Automated drug filling and vacuuming operations, increasing speed with Dijkstra’s Algorithm and ensuring safety by eliminating human involvement.

Vehicle Systems & Control Laboratory

Undergraduate Researcher | August 2023 – November 2023

• Collaborated with PhD students on real-time intention prediction for upper-limb rehabilitation robots using Convolutional Neural Networks.
• Conducted literature reviews on intelligent and fuzzy control to implement learning algorithms.

Publications and Presentations

1. *Z. Bucknor-Smartt, J. Mustafa, W. Bannick, L. Graves, M. Korwani, G. C. Thomas, “Direct User Control of Knee Exoskeletons”, TAMU OakTrust Thesis Repository, April 3rd 2025
2. *Z. Bucknor-Smartt “Direct User Control of Knee Exoskeletons”, IEEE SIEDS 2025, University of Virginia, May 2nd 2025, BEST PAPER AWARD
3. A. Petrakian, Z. Bucknor-Smartt, C. Scott, G. C. Thomas, “Amplifying Human Strength Through a Virtual Sprung Inertia”, IEEE International Conference on Rehabilitation Robotics, May 12th, 2025.
4. A. Petrakian, Z. Bucknor-Smartt, G. C. Thomas, “Formulating Controllers for Human Strength Amplification”, Texas Regional Robotics Symposium, April 30th, 2024 (Conference Poster).
5. Z. Bucknor-Smartt, “Amplifying Human Strength Through a Virtual Sprung Inertia”, Gulf Coast Undergraduate Research Symposium, Rice University, November 9th, 2024 (Symposium Research Speech).
6. I. Lansdowne, Z. Bucknor-Smartt, J. Foltyn, J. Kong, M. Guttman, “TURTLE’s Low Cost, Open-Source Quadruped”, Texas Regional Robotics Symposium, April 30th, 2024 (Conference Poster).
7. Z. Bucknor-Smartt, “An Introduction to Computer Vision: Object and Edge Detection”, TAMU HowdyHack, September 28th, 2023 (Technical Seminar).

Experience

Texas A&M University

Course Grader | January 2025 – May 2025

• Graded MEEN 408/612, a stacked undergraduate/graduate course on robot kinematics, dynamics, and control algorithms.
• Undergraduate grader + TA for MEEN 408/612, a stacked undergraduate/graduate course focusing on forward, inverse, and differential kinematics of robot manipulators, path planning, motion planning, dynamics of robot manipulators and control algorithms; PD/PID control, computed torque algorithm.
• Facilitate grading operations, robot simulation in Drake for class projects, as well as setup and operation of 15 UR5E robots.

Mechanical Engineering Peer Teacher | January 2024 – September 2024

• Authored notes and provided tutoring in feedback control, calculus, and differential equations.

Mechanical Engineering Ambassador | March 2023 – Present

• Delivered presentations to prospective students, led tours, and provided research advice for graduate students.

Activities & Projects

Los Alamos National Laboratories Aggies Invent

Chief Technical Officer, Team NewClear Solutions | November 2024

• Led a team to develop a multi-DOF teleoperation system for nuclear waste management, securing 2nd place.

T.U.R.T.L.E Robotics

President | August 2022 – Present

• Directed a 250+ member robotics organization, teaching weekly robotics classes and managing lab operations.

Team Lead: Partial Hand Amputee Prosthesis | August 2023 – Present

• Designed an EMG-controlled prosthetic hand, achieving 96% live prediction accuracy with PID control.

Skills

Technical Skills: Python, C++, Embedded C, MATLAB, Isaac Sim, Simulink, R, Drake, Gazebo, OpenCV, TensorFlow, Scikit-learn, ROS2, SolidWorks, Multisim, LabView, Git, Linux, Human Subject Experiments (authoring IRB protocols), human signal processing (EMG), Academic Writing Knowledge Areas: Force Control, Real Time Feedback Control Systems, System Identification, Bayesian State Estimation, Autonomy, Machine Learning, Robot Dynamics, Legged Locomotion, Manipulation Certifications: OSHA, CSWA, Additive Manufacturing, Sustainable Engineering