List of Accepted Demos
| Demo | Authors | Affiliation |
|---|---|---|
| Agentic AI Makes Real-Time Neural Data Conversational for Epilepsy Patients | Zack Goldblum, Haoer Shi, Brian Litt | University of Pennsylvania |
| An Open-Source Ecosystem for Models of Multi-Modal Brain and Body Data | Mehdi Azabou, Vinam Arora, Milo Sobral, Laura Suarez, Nanda Krishna, Avery Ryoo, Ximeng Mao, Liam Paninski, Guillaume Lajoie, Blake Richards, Eva Dyer | Columbia University, ARNI, UPenn, Mila |
| cVEP-based brain-computer interface | Pierre Guetschel, Jordy Thielen, Michael Tangermann, Matt Wilson, Martijn Schreuder | Donders Institute |
| Eleuto : A non invasive computer interface for paralyzed users | Geeve George | The Hong Kong University of Science and Technology |
| ezmsg and LSL: Prototyping an iBCI from modular components | Chadwick Boulay, Preston Peranich, Konrad Pilch, Kyle McGraw, Griffin Milsap | Blackrock Neurotech Inc |
| Lab Smarter with PLASMA and MotionSenseHRV | Yuyi Chang, Fang Yu Chang, Agatha Lenartowicz, Emre Ertin | Department of Electrical and Computer Engineering, The Ohio State University (YC, EE) Semel Institute for Neuroscience and Behavior, University of California Los Angeles (FC, AL) |
| Lightning Pose: improved animal pose estimation via semi-supervised learning, Bayesian ensembling | Matthew Whiteway, D Biderman, C Hurwitz, K Sikka, L Aharon, N Greenspan, RS Lee, A Vishnubhotla, R Warren, F Pedraja, D Noone, MM Schartner, JM Huntenburg, A Khanal, GT Meijer, JP Noel, A Pan-Vazquez, KZ Socha, AE Urai, Internation Brain Lab, JP Cunningham, NB Sawtell, L Paninski | Columbia University |
| Meta Reality Labs neural wrist band | Meta Reality Labs | Meta |
| Neuro ID | Arnault Caillet, Apolline Mellot, Thomas Semah | Yneuro |
| NeuroStrip: A Direct‐to-Skin Wearable for Real-Time Neural Interface | Jeff Kitchen, Zafar Faraz, James Schorey, Christina Maher | Control Bionics |
| Real-time EEG Based Control of a 19 Degree of Freedom Prosthetic Hand | Soham Mehra, Nick Cadavid, Pranai Reddy | Morph Labs |
| Real-time reconstruction of human visual perception from fMRI | Rishab S. Iyer, Ross P. Kempner†, Cesar Kadir Torrico Villanueva†, Jacob S. Prince†, Elizabeth A. McDevitt*, Paul S. Scotti*, Kenneth A. Norman* († indicates core contributors; * indicates joint senior authors) | Princeton Neuroscience Institute, Icahn School of Medicine at Mt Sinai, Harvard University Department of Psychology & Sophont |
| Real-time visualization and inference of Kernel Flow TD-NIRS data using the NVIDIA Holoscan SDK and Jetson Thor | Ryan Field, Gabe Lerner, Julien Dubois, Victor Szczepanski, Mimi Liao, Tom Birdsong, Julien Jomier | Kernel & NVIDIA |
| Standardized XR Tools for Capturing Brain and Behavior Data in Context | Maryse Thomas, Tab Memmott, Ryan Hanson, Annabel Fan, Kyla Alsbury-Nealy, Blake Richards, Benjamin Alsbury-Nealy | SilicoLabs, Wearable Sensing, McGill University, Mila |
| WotNow: Multimodal AI Coach with Affective Computing | Sameer Yami, Benjamin He, Navani Udgaonkar, Rahul Pandit, Sukanya Sriram, Ganesan Sriram | Augment Me, Inc. |
Call for Demos
Submissions Open
July 15, 2025
Submission Deadline
September 12, 2025 AoE
Accept/Reject Notification
September 22, 2025
Workshop
December 6, 2025
Upcoming
Important Dates
-
Submissions OpenJuly 15, 2025
-
Submission DeadlineSeptember 12, 2025 AoE
-
Accept/Reject NotificationSeptember 26, 2025
-
WorkshopDecember 6-7, 2025Upcoming
We invite submissions for interactive demos that showcase novel methods, devices, or applications of AI for neural and physiological data. The goal of the demo session is to inspire attendees, foster hands-on learning, and highlight the real-world impact of advances in the field.
We Especially Encourage:
- Real-time systems that decode or visualize biosignal data
- Demonstrations of new recording hardware
- Demonstrations of new recording wearable devices
- Prototypes of clinical or consumer neurotechnology
- Interactive data visualization tools
- Software tools for large-scale biosignal analysis
- Brain-computer interface demonstrations
- Vision-based tools used to analyze large-scale video data