Research Assistant at Neuromuscular Rehabilitation Engineering Laboratory (NREL): Focused on investigating neuromuscular control mechanisms in able-bodied individuals and those with impairments, and developing engineering frameworks for wearer-robot symbiosis in assistive devices like robotic prosthetics and exoskeletons.Project 1: Developed a user-controlled interface and reinforcement learning-based algorithm to fine-tune control parameters for robotic knee prostheses.Achievements: Enabled user-preferred tuning for robotic knee prostheses, effectively tuning 12 control parameters, and confirming users' ability to consistently identify their preferred knee profile.Impact: Provided insights into gait biomechanics with potential applications in home or clinical settings.Project 2: Employed machine learning to analyze real-time sensor data, optimizing exoskeleton control parameters for improved gait balance and user stability.Achievements: Successfully modulated step width without affecting step length or gluteus medius EMG activity.Impact: Suggested the potential for enhancing walking balance in assistive and rehabilitation applications.Project 3: Integrated reinforcement learning to optimize real-time exoskeleton control parameters through simulation and physical testing.Achievements: Achieved a step width adjustment error of 1.2 cm by tuning PID parameters via reinforcement learning.Impact: Advanced the development of assistive applications to enhance mediolateral gait balance in individuals with neurological impairments, the elderly, and amputees.

• Lectured courses in Process Control for Process Engineers and Microcontrollers, delivering comprehensive education that enhances student knowledge and skills, resulting in improved student competency and career readiness.• Assisted Prof. Gancho Vachkov with courses such as Control Theory 1, Control Theory 2, and Process Control, supporting the teaching and exam process and ensuring high-quality education delivery, which strengthens the academic program quality.• Actively engaged in establishment of "Internet of Things" laboratory, with the goal of setting up a state-of-the-art facility for IoT research and education, enabling advanced research and hands-on learning, fostering innovation and student engagement.• Worked on a collaborative project with Kyungsung University (South Korea) to develop CCTV Video Analysis Technology for the surveillance and safety management of oil and gas facilities, improving monitoring and safety systems, and enhancing security and operational efficiency.• We collected, preprocessed, and analyzed real plant operation data from the Stabilization unit in a petrochemical plant. Upon collected data we published a paper on a unique type of fuzzy model with an incomplete grid-type fuzzy rule base, which is crucial for the proposed plant monitoring system. The system effectively detected different operations using a moving window approach and calculating dissimilarity degrees based on real data.

• Designed algorithm in MATLAB to accurately identify curvy obstacles using ultrasonic sensors, enhancing obstacle detection accuracy and improving vehicle safety.• Tested the algorithm with Simulink to ensure reliability in various driving conditions, validating detection capabilities, and achieving robust performance in real-world scenarios.• Conducted pilot field tests with hardware interfaces and data acquisition systems to verify algorithm effectiveness in real-world conditions to ensure practical applicability.

• Engaged in designing PCB circuits for digital car clusters• Troubleshooted hardware and software issues to diagnose and resolve technical problems.• Documented technical specifications to maintain detailed records and manuals