Post-Doctoral Scholar

Mentored by Dr. Helen J. Huang and Dr. Yue Wen

Biomechanics, Rehabilitation, and Interdisciplinary Neuroscience Laboratory

Intelligent Neural Interface and Wearable Robotics Laboratory

University of Central Florida, Orlando, FL

Ph.D. in Mechanical Engineering

University of Central Florida, Orlando, FL

Dissertation: Design and Validation of a Myoelectric Bilateral Cable-Driven Upper Body Exosuit and a Deep Reinforcement Learning-based Motor Controller for an Upper Extremity Simulator

Advisor: Joon-Hyuk Park, Ph.D.

M.S. in Mechanical Engineering

University of Southern California, Los Angeles, CA

B.S. with honor in Mechanical Engineering

Graduated Magna Cum Laude

Florida Institute of Technology, Melbourne, FL

Intelligent Neural Interface and Wearable Robotics Laboratory

Mentor: Yue Wen, Ph.D. — University of Central Florida, Orlando, FL

• Next-Generation Neural Machine Interfaces via Generalizable Artificial Intelligence (Major Project)
  • Developed a plug-and-play, generalizable neural drive decoder for real-time neural-machine interfaces using multi-head convolutional neural networks and high-density surface electromyography signals.
  • Established benchmark comparisons of convolutional architectures, quantifying trade-offs among decoding accuracy, generalizability, computational efficiency, and inference latency.
  • Demonstrated cross-dataset generalization of CNN-based neural drive estimators to unseen participants, muscles, contraction intensities, and experimental sessions without retraining the model.
  • Identified a spatial CNN architecture with the optimal balance between decoding performance and computational efficiency for deployment on resource-constrained neural interface systems.
• Reproducible Algorithms for Motor Unit Decomposition from HD-sEMG (Major Project)
  • Established a neurophysiology-informed benchmark framework to evaluate the consistency and validity of blind source separation (BSS)-based HD-sEMG motor unit decomposition software, revealing substantial variability in decomposition outcomes across open-source implementations.
  • Investigated the physiological reliability of neural drive estimates derived from BSS algorithms by comparing decomposition results against expert-curated motor unit spike trains and neurophysiological validation criteria.
  • Developed a standardized motor-unit editing and quality-control pipeline for correcting false-positive and false-negative discharges in decomposed motor-unit spike trains.
  • Created a public HD-sEMG motor unit decomposition dataset as a reference benchmark for validating future decomposition algorithms and neural interface studies.

Biomechanics, Rehabilitation, and Interdisciplinary Neuroscience Laboratory (BRaIN Lab)

Mentor: Helen J. Huang, Ph.D. — University of Central Florida, Orlando, FL

• Bridging Cortical Dynamics and Human Locomotion through AI-Driven Neural Decoding (Major Project)
  • Developed artificial intelligence methods to decode gait speed directly from cortical activity recorded using high-density EEG.
  • Designed and evaluated a convolutional neural network-based framework for decoding gait speed from a minimally processed EEG signal collected during walking.
  • Systematically investigated the contribution of motion artifact in the EEG signal for decoding the gait speed with a convolutional neural network pipeline.

Wearable Engineering and Assistive Robotics Laboratory

Mentor: Joon-Hyuk Park, Ph.D. — University of Central Florida, Orlando, FL

• Next-Generation Myoelectric Cable-Driven Exosuits for Human Performance Augmentation (Major Project)
  • Designed and built an upper limb exosuit to reduce the risk of work-related musculoskeletal disorders during load-carrying and eye-level tasks.
  • Programmed a proportional myoelectric control system with an admittance controller using LabVIEW and an NI FPGA, integrating surface EMG and IMU sensors to precisely control the upper-limb exosuit in load-carrying and eye-level applications.
  • Developed an IRB protocol for human subject experiments to validate the exosuit's effectiveness in reducing muscle fatigue, and conducted research on human biofeedback while using the exosuit.
• Deep Reinforcement Learning for Human Motor Control and Neuromusculoskeletal Simulation (Major Project)
  • Developed an upper limb neuromusculoskeletal simulation using the MyoSuite model within the MuJoCo physics engine to replicate elbow joint movements with and without exoskeleton assistance.
  • Constructed a novel deep reinforcement learning-based auto-tuner for the human central nervous system's internal model, eliminating the need for experimental data or prior knowledge.
  • Demonstrated the efficiency of the deep reinforcement learning-based auto-tuner in accurately tuning the central nervous system's internal model.
  • Benchmarked the auto-tuner against a deep reinforcement learning agent trained to predict muscle activation, demonstrating higher accuracy and shorter response times.
• Design and Construction of a Cable-Driven Ankle Perturbation System to Study Biomechanics of Balance Control in Healthy Adults
  • Designed and built a system that uses cable force to control ankle acceleration and deceleration in the sagittal plane, inducing slip or trip perturbations during walking.
  • Conducted validation studies demonstrating the system's ability to deliver random, unanticipated slip and trip perturbations of varying intensities at specific points in the gait cycle.
• Evaluation of a Variable Resistance Suit for Muscle Hypertrophy
  • Human Subject Experimentation: Assisted in conducting human subject experiments to validate the efficiency of the proposed system.
  • Research Documentation and Data Visualization: Contributed to writing research literature and creating relevant plots for data analysis and publication.

2025 IEEE/EMBS International Conference on Neural Engineering (NER), San Diego, California, USA

2025 IEEE/RAS-EMBS International Conference on Rehabilitation Robotics (ICORR), Chicago, Illinois, USA

2023 IEEE Conference on Systems, Man, and Cybernetics (SMC), Honolulu, HI, USA

2022 IEEE International Conference on Mechatronics and Automation (ICMA), Guilin, Guangxi, China

Best Student Paper Award at the 2022 IEEE International Conference on Mechatronics and Automation (ICMA), Guilin, Guangxi, China, for the paper: "A Bilateral Six Degree of Freedom Cable-driven Upper Body Exosuit".

Graduate Dean's Dissertation Completion Fellowship offered by the College of Engineering and Computer Science of the University of Central Florida

Student Travel Grant offered by the Institute of Electrical and Electronics Engineers (IEEE)

Graduate Student Travel Fellowship offered by the College of Graduate Study of the University of Central Florida

Delta Zable

Department of Mechanical Engineering, University of Central Florida, Orlando, FL

• Co-advisor of Undergraduate Honor Thesis.
• Thesis: Implementation and Validation of an Open Source Ankle Exoskeleton for Controlled Ankle Resistance During Walking

Keith A. Curieer

Department of Mechanical Engineering, University of Central Florida, Orlando, FL

• Committee Member and Co-advisor of Undergraduate Honor Thesis.
• Thesis: Variational Autoencoder and Sensor Fusion for Robust Myoelectric Controls