Upcoming and Recent Events
CMU Neural Engineering Virtual Seminars
Speaker: Dr. Qifa Zhou, Professor of Biomedical Engineering and Ophthalmology, University of Southern California
Title: Non-invasive Wearable Ultrasound for Vision Restoration
Time: April 1, 2026, Wednesday 1-2PM US Eastern Time
Zoom Link: https://cmu.zoom.us/j/92561295620?pwd=qTBqFb25qMyNGkl3633yJG740CEA00.1
Abstract: In this talk, Dr. Zhou will present his work on focused ultrasound stimulation of the retina, which evokes neuronal activity in visual centers including the superior colliculus and primary visual cortex (V1) in vivo, in both normal-sighted and retinally degenerated blind rats. Neuronal responses induced by a customized spherically focused ultrasound transducer demonstrate high spatial resolution (~75 µm) and temporal resolution (up to 5 Hz) within the rat visual system. Furthermore, his lab has developed a customized high-frequency 2D array capable of generating static stimulation patterns, such as letter forms. His findings indicate that ultrasound-based retinal stimulation in vivo is a safe and effective approach with high spatiotemporal precision, highlighting its potential as a novel, non-invasive visual prosthesis for translational applications in blind patients. In addition, he will introduce his work on non-invasive sonogenetic retinal stimulation and cardiac pacing, as well as high-resolution imaging of blood flow and vascular structures.
About the Speaker: Dr. Qifa Zhou is the Zohrab A. Kaprielian Fellow in engineering and a Professor of Biomedical Engineering and Ophthalmology at the University of Southern California (USC). He also serves as the Director of the Biomedical Ultrasound Research Lab and Director of Translational Studies at Ginsburg Institute for Biomedical Therapeutics at USC. Dr. Zhou has authored over 370 peer-reviewed publications in leading journals, including Science, Cell, Science Robotics, Nature Medicine, Nature Biomedical Engineering, Nature Photonics, Nature Electronics and Nature Materials. His research focuses on developing wearable ultrasonic transducers and 2D arrays for medical image and ultrasound modulation on the retinal stimulation and heart for pacemakers. The ultrasound transducer at USC was ranked No. 1 worldwide in 2025 by ScholarGPS. Dr. Zhou’s honors include the Robert Newcomb Interdisciplinary Team Science Award (2015), the SPIE Photonics West Seno Medical Best Paper Award (2018), the USC Stevens Institute Innovation Technology Transfer Award (2019), the USC Viterbi School of Engineering Senior Research Award (2022), and the USC Viterbi School of Engineering Inspired Award (2024). In 2025, he received the Golden Axon Leadership Award from the World Brain Mapping Society and the Achievement Award at the 16th International Conference on Ultrasound Engineering for Biomedical Applications in 2025. Dr. Zhou is a Fellow of the Institute of Electrical and Electronics Engineers (IEEE), the International Society for Optics and Photonics (SPIE), the American Institute for Medical and Biological Engineering (AIMBE), and the International Association of Advanced Materials (IAAM). Additionally, he is a Senior Member of the National Academy of Inventors. Currently, he is the President of International Congress on Ultrasound (2025-2027).
Computer Science Seminar
Speaker: Dr. Yoga Varatharajah
Title: Domain-guided Machine Learning to Advance Neurological Care
Date: Monday, April 6, 2026
Time: 1:30 PM
Location: Catskill 130
Host: Dr. Thenkurussi (Kesh) Kesavadas
Abstract: Recent advances in wearables, brain implants, and sensing technology have created new opportunities to study the brain and continuously monitor patients' brain health to ascertain individualized treatments for neurological diseases. Continuous streams of physiological data, such as EEG, ECG, and inertial signals, offer a powerful lens into the interactions between the brain and other body systems in free-living, real-world settings, that underlie conditions such as neurodegeneration, cognitive decline, and disorders of autonomic regulation. However, translating these high-dimensional, longitudinal data into meaningful biological insights and actionable clinical decisions remains a major challenge. Machine learning (ML) holds great promise in tackling these challenges; however, the mainstream black-box-ML approaches have proven to be untrustworthy because of label inconsistencies, spurious correlations, and the lack of deployment robustness. In this talk, I will introduce a framework for “Domain-guided Machine Learning” (DGML), which integrates physiological and clinical knowledge into ML models to improve interpretability, robustness, and trustworthiness. I will also highlight applications of DGML in areas such as the development of personalized, data-driven therapeutic strategies, discovery of clinical knowledge, and remote screening and monitoring of neurological diseases.
About the Speaker: Dr. Yoga Varatharajah is an Assistant Professor in Computer Science & Engineering at the University of Minnesota and is affiliated with the Minnesota Robotics Institute and the Mayo Clinic, Rochester. He leads the Health Intelligence Laboratory -- an interdisciplinary team of researchers developing novel ML-based solutions to improve disease diagnosis, clinical decision making, review of patient data, and discovery of new clinical knowledge. He obtained his Ph.D. in Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign. He has been working closely with domain experts at Mayo Clinic and Cleveland Clinic to develop, evaluate, and deploy domain-guided ML models to inform clinical decisions related to neurological diseases. His research has been published at reputed engineering conferences (e.g., Neurips, ML4H, BIBM, ISBI, EMBC, NER) and medical journals (e.g., Scientific Reports, Journal of Neural Engineering, Brain Communications, Epilepsia, Neuroimage) and has resulted in several patents. His work received several honors, including a CSL Ph.D. Thesis Award, a Mayo-Clinic-Illinois Alliance Fellowship, an American Epilepsy Society Young Investigator Award, an NSF CRII Research Initiation Award, an NSF CAREER Award, an NCSA Faculty Fellowship, and several best paper awards and nominations.
