Project Voice

As the faculty advisor for Project Voice, he provides mentorship and guidance, leveraging over 15 years of experience in assistive technology and cognitive neuroscience to inspire the student-led research that is the foundation of CINPCT.

As the electrical engineering lead, she designs and builds the hardware for acquiring biological signals, focusing on creating reliable, low-noise systems suitable for real-world patient care environments.

He manages the financial health of the CINPCT conference while also contributing her research skills to the analysis of biometric data, linking fiscal responsibility with hands-on scientific inquiry.

Focusing on human-centered design, she crafts the user experience for Project Voice's technologies, ensuring every interface is intuitive, accessible, and designed with the direct input of the community we serve.

Working as an AI/ML Co-Lead, he specializes in data management and pipeline development, ensuring the team has clean, robust data to train and validate the next generation of assistive AI.

As an AI/ML Co-Lead, he is instrumental in developing the core machine learning algorithms, focusing on model architecture and performance to interpret complex biological signals accurately.

Her research is centered on analyzing complex biometric data streams, including EEG and heart rate variability, to develop more empathetic and responsive assistive devices.