Aime Aguilar
Aime J. Aguilar is a Ph.D. student in Electrical Engineering with a focus on neuroengineering at the University of Houston. Her research focuses on mobile brain-body imaging, brain-computer interfaces, and the use of EEG to study music, movement, culture, and human creativity. She is committed to advancing inclusive neurotechnology, data standards, and responsible innovation, with a particular interest in supporting women and underrepresented communities in science and engineering.
Brandi L. BeCoats
Brandi L. BeCoats, M.S., CCC-SLP fourth year Ph.D. student in Communication Sciences and Disorders at the University of Houston and a licensed speech-language pathologist. She is a member of the Speech, Language, Aphasia, and the Brain Lab under the mentorship of Drs. Heather Dial and Lynn Maher. She earned both her Bachelor of Science in Health Sciences and her Master of Science in Speech-Language Pathology from Tennessee State University and has spent her clinical and academic career focused on improving outcomes for adults with neurogenic communication disorders. At the University of Houston, she serves as a clinical educator training graduate students to work with adult neurogenic populations and has supervised the university clinic's aphasia conversation groups for the past four years. Her research focuses on clinical education practices for group-based interventions and auditory comprehension disorders in aphasia, two critical but historically understudied areas of the field that she approaches with a shared commitment to developing innovative, individualized solutions for both training and patient care. She has presented her research at multiple national conferences and received the 2024 ASHA Convention Meritorious Research Award for her work on clinical training. She was selected to conduct mentored research at the Center for Brain Recovery at Boston University, which enabled her to develop a project examining how semantic context influences speech sound processing in people with aphasia using event-related potentials (ERP), a neurophysiological measure that bridges the gap between observed behavioral profiles and the underlying neural processes that drive them. She continues this work as a graduate mentor in the NSAP program.
Komal Kukkar
Komal K. Kukkar, PT, MS, is a doctoral candidate in Kinesiology at the University of Houston (Parikh Lab), where he maintains a 4.0 GPA and holds a Presidential Fellowship. He is a licensed physical therapist with over seven years of clinical experience treating neurological and orthopedic conditions, and he brings that clinical lens directly into his research. His doctoral work integrates high-density EEG, corticomuscular coherence, functional cortical connectivity, TMS/iTBS, and machine and deep learning to investigate the cortical mechanisms underlying sensorimotor control in chronic stroke survivors and aging populations. He has authored or co-authored 14 publications and presented his work at the Society for Neuroscience annual meetings in 2022, 2023, 2024, and 2025. Komal is also the developer of EEG_Clustering, an open-source EEGLAB-integrated MATLAB application for EEG analysis and visualization, and is currently building the EEG Impossible Atlas, a quantitative framework for assessing source detectability across 170 brain regions. He has mentored more than a dozen NSF- and NIH-funded undergraduate and post-baccalaureate trainees, many of whom have gone on to graduate programs at institutions including Johns Hopkins, Carnegie Mellon, and UT Austin. His long-term goal is to advance the applicability of motor memory research in stroke, dementia, and aphasia — leveraging neuroimaging, machine learning, and neuromodulation to develop more effective, individually tailored rehabilitation strategies.
Maxine Annel Pacheco-Ramírez
Maxine Annel Pacheco-Ramírez is a PhD Candidate in Electrical and Computer Engineering at the University of Houston, where she works at the IUCRC BRAIN Center in the Noninvasive Brain-Machine Interface Systems Laboratory under Dr. José L. Contreras-Vidal. She holds a B.Eng. in Biomedical Engineering from Tecnológico de Monterrey, where she graduated with the highest GPA of her class.
Her research sits at the intersection of neuroscience, affective computing, and human experience, using EEG to decode how the brain responds to music, dance, art, and emotion in real-world, ecologically valid settings. From concert halls to clinical environments, her work advances Mobile Brain/Body Imaging (MoBI), brain-computer interfaces, and EEG-based emotion recognition.
Beyond the lab, Maxine serves as NSF AccelNet Coordinator for the Movement, Music and Brain Health network (Award #2412731) and Treasurer of the BRAIN-AccelNet Student Network (BASN), roles through which she leads international research coordination across institutions in the U.S., Europe, and beyond. She has co-organized workshops and summer schools in San Francisco, Geneva, Houston, and Florence, and has presented her research at venues including the EBRAINS Summit (Brussels), the Society for the Neuroscience of Creativity (Paris and Philadelphia).
She is published in Scientific Data (Nature Portfolio) and has contributed to projects spanning MD Anderson Cancer Center, Rice University, UCSF, UCL, EBRAINS and the University of Geneva.
Lianne Sánchez-Rodríguez
Lianne Sánchez-Rodríguez is a PhD student in Electrical Engineering at the University of Houston, where she works at the IUCRC BRAIN Center in the Non-invasive Brain-Machine Interface Systems Laboratory under Dr. José L. Contreras-Vidal. She holds an M.S. in Applied Biomedical Engineering from Johns Hopkins University and a B.S. in Computer Engineering from the University of Puerto Rico at Mayagüez.
Her research bridges brain-computer interfaces, embedded systems, EEG signal processing, neurorehabilitation, and generative AI. She leads Mindspring, an EEG-based music generative AI project that uses brainwave data to create personalized music experiences for therapeutic and creative applications. She also contributes to Brain on Arts studies, collecting and analyzing multimodal data from musicians, artists, and composers during live performance settings. Lianne’s work also includes the NeuroExo project, which aims to improve at-home stroke neurorehabilitation through a low-cost, portable, and easy-to-use EEG-based brain-computer interface system. In this role, she has developed embedded system protocols, optimized data acquisition performance, collected multimodal human-subject data, and performed longitudinal EEG analyses with stroke and healthy participants.
Beyond the lab, Lianne currently serves as the IAB Liaison for the NSF IUCRC BRAIN Center, supporting communication and engagement between students, researchers, and industry advisory board members. She has also mentored senior design, REU, and REM students at the University of Houston, providing guidance in embedded systems, software engineering, technical documentation, and applied neurotechnology.
Prior to her doctoral studies, Lianne gained professional engineering experience across the medical device, defense, and embedded systems sectors. She worked with Biosense Webster, Johnson & Johnson, through the Medical Devices Engineering Development Program, supporting product development, manufacturing builds, supplier coordination, root-cause investigations, and launch readiness activities. She also completed engineering experiences at MIT Lincoln Laboratory and the Department of Defense, where she developed rapid prototyping workflows, Raspberry Pi-based tools, and Arduino robotics applications.
She has contributed to peer-reviewed publications in Sensors, presented her work at the Society for Neuroscience and IUCRC BRAIN Center meetings, and received recognitions including the International Brain Research Organization Training Award, the SfN Trainee Professional Development Award, an AIMBE Public Policy Institute travel award, the Grace Hopper Celebration Scholarship, and the University of Puerto Rico Mayagüez ECE Department Best Student Award.
Supraja Vaidhyanathan
Supraja Vaidhyanathan is a graduate mentor for the NSAP program in Dr. Jinsook Roh’s lab. As a second-year PhD candidate, her work focuses on understanding how rehabilitation can support recovery after stroke. She is interested in using brain and muscle signals to better understand movement and improve stroke rehabilitation approaches. Outside of work, she enjoys painting, crafting, and reading.
Saba Yazdekhasti
Saba Yazdekhasti is currently a Ph.D. candidate in Kinesiology, specializing in Motor Behavior. Her master’s studies and clinical experience in Orthotics and Prosthetics have given her a solid foundation for her current research. After serving as a teaching assistant for the Biomechanics course, her research work also extends to interactions between the nervous and musculoskeletal system. Her work reflects a deep understanding of the complexities involved in optimizing human performance in several aspects, such as sensorimotor function, development of biomechanics within the field of sport science, and human locomotion in healthy and clinical populations.