Akinwale Okunola

As a Ph.D. researcher at Virginia Tech, I am passionate about enhancing human-robot collaboration through AI-driven solutions in wearable robotics and construction technology. My work lies at the intersection of cognitive neuroscience, biomechanics, and human-robot interaction to assess the impact of wearable robotics on worker safety, performance, and well-being.

• Cognitive Load & Situational Awareness – Using EEG, eye-tracking, and biosensors to assess how exoskeletons impact cognitive and motor functions.
• AI-Driven Wearable Robotics – Developing adaptive exoskeleton control models using deep learning to personalize assistance based on user biomechanics.
• Gait & Postural Stability – Using pressure insoles to evaluate balance, mobility, and fall risk
• Digital Twins & Human Factors – Leveraging Large Language Models (LLMs) and Digital Twins to enhance user interaction, risk prediction, and real-time decision-making in construction robotics.

I am deeply invested in translating academic insights into real-world applications, ensuring that wearable assistive technologies align with industry needs. By collaborating with engineers, data scientists, and human factors specialists, I contribute to shaping safer, smarter, and more efficient construction environments.

• EEG, EMG, IMU, Eye-Tracking & Wearable Sensor Data Analysis
• Biomechanical & Ergonomic Assessment
• Human-Robot Interaction (HRI)
• AI & Machine Learning for Human Performance Analytics
• Python | MATLAB | Digital Twins

Always open to industry collaborations, R&D roles, and discussions on AI, human augmentation, and cognitive-aware robotics. Let’s connect!