2026 IEEE Brain Discovery and Neurotechnology Workshop

IEEE Brain Discovery and Neurotechnology Workshop
November 11 – 13, 2026
Washington, DC, USA

Registration Opens July 2026

Advances in understanding of the brain both in healthy individuals and those suffering from a disorder is leading to groundbreaking discoveries and engineering solutions. Even so, development and deployment of effective neurotechnology and means of studying the brain through neuroimaging techniques and machine learning requires an integrated approach as well as close collaboration among the neuroengineering community, neuroscientists, and clinical practitioners. The goal of this workshop is to bring together researchers and practitioners across academia, industry, and the clinical profession to highlight innovative neurotechnology and brain research methods, emphasizing their potential to improve understanding of the brain and address a wide range of disorders to improve the human condition.

The workshop highlights plenary speakers in key brain-related fields, and consists of three tracks covering emerging neurotechnologies, machine learning and computer paradigms for brain discovery, and clinical applications and impact. Each track includes keynote and invited speakers who will discuss their work in the context of larger issues in each of these topic areas. Other program highlights are panel sessions on the ethical implications of neurotechnology and the development of standards, clinical priorities and challenges, and future growth and funding areas in these emerging fields. A research poster session and student research challenge will take place during the workshop.

Program Committee

General Chairs
Ravi Hadimani, Virginia Commonwealth University, USA
Christine Edwards, NeuroDynamics, LLC, USA

Program Chairs
Emerging Neurotechnologies:
Grace M. Hwang, Program Director NIH/NINDS, USA
Leo Ko, National Yang Ming Chiao Tung University, Taiwan

Machine Learning and Computer Paradigms for Brain Discovery:
Gina C. Adam, George Washington University, USA
Maryam Parsa, George Mason University, USA
Dimitri Van De Ville, EPFL, Switzerland

Clinical Applications and Impact:
Dean Krusienski, Virginia Commonwealth University, USA
Jose Contreras-Vidal, University of Houston, USA

Workshop Committee
Selin Aviyente, Chair, Michigan State University, USA
Damien Coyle, University of Bath, UK
Gert Cauwenberghs, UC, San Diego, USA
Metin Akay, University of Houston
Bruce Hecht, ASML, USA
Rikky Muller, UC Berkeley, USA
Ljiljana Trajkovic, Simon Fraser University, Canada
Vince Calhoun, TReNDS Center (Georgia State, Georgia Tech, Emory University), USA

Communications
Cynthia Weber, Program Manager, IEEE Brain

Thanks to Our Partners

We would like to thank the IEEE Member Societies and Associations for their support of IEEE Brain.

IEEE Brain Discovery and Neurotechnology Workshop Symposiums

Emerging Neurotechnologies

In recent years a range of new neurotechnology innovations have emerged to enable neuroimaging and neural recording and interfacing at multiple scales in variety of settings—in the lab, in the clinic, and in the wild—including low-cost wearable electroencephalography (EEG), ultra-high density EEG, stereoelectroencephalography (sEEG), advanced functional near infrared spectrography (fNIRS) and functional magnetic resonance imaging (fMRI), functional ultrasound imaging (fUS),  optically pumped magnetometer magnetoencephalography (OPM-MEG), neural lace, neural dust, stent-electrode recording arrays (stentrodes) and endovascular recording techniques, multielectrode arrays, elecrtocorticographic (ECoG) arrays, multi-photon optics for high-throughput/high-resolution functional brain imaging, and optogenetics. This session aims to present examples of the latest scientific studies involving a selection of these approaches as well as discussion surrounding feasibility of development within the next 5-10 years and major opportunities and challenges in deploying these technologies.

Machine Learning and Computer Paradigms for Brain Discovery

Advances in noninvasive neuroimaging technology such as magnetic resonance imaging and magnetoencephalography have enabled the study of both the healthy and disordered human brain with increasing temporal and spatial resolution. Neuroimaging data poses some unique challenges such as low signal-to-noise ratio, small sample size, and high dimensionality. Recent methodological advances in machine learning have enabled the analysis of brain data across multiple scales and modalities. Current challenges and problems of interest include: neuromorphic systems engineering for brain-inspired natural intelligence; development of interpretable deep learning architectures for learning from neural data; network neuroscience for functional/structural connectivity network analysis, i.e., brain connectomics, across time and subjects; variability of brain networks across subjects; multimodal data fusion; classification and prediction of health status or specific outcomes through biomarker identification. This session aims to present examples of the latest research in machine learning and computer paradigms for brain discovery involving a selection of these approaches as well as discussion on challenges and opportunities, including the transition to clinical practice and applications such as preventive predictive actions.

Clinical Applications and Impact

The first demonstration of a technology for a clinical application with impact was deep brain stimulation for Parkinson’s disease. Interestingly, it took less than 25 years for this technology to become established with more than 80,000 patients having received an implant by 2010. Technologies that restore, replace, or enhance human nervous system function are emerging fast but few are used in daily clinical practice or at home. In this symposium, we will be presenting some of the most promising technologies that have broad clinical application prospects and discuss their remaining important challenges. These include optogenetics-based therapies, where recent advances in optogenetic real-time monitoring and therapeutic interventions have opened up the possibility for providing a complementary treatment following brain injury; neuroprosthetics for the restoration of vision, hearing, or motor function; as well as neuromodulation devices such as brain-computer-interfaces, and more.

Plenary Speaker

John Ngai, Director, NIH BRAIN Initiative
The NIH BRAIN Initiative: Inventing the Future

John Ngai, Director, NIH BRAIN Initiative Abstract: The U.S. National Institutes of Health (NIH) Brain Research Through Advancing Innovative Neurotechnologies® (BRAIN) Initiative is an ambitious program whose mission is to develop new technologies and resources to revolutionize our understanding of the human brain and accelerate discovery toward cures for devastating neurologic and neuropsychiatric diseases. The NIH BRAIN Initiative supports research on understanding neural circuit function by developing novel tools and applying innovate techniques to precisely map, monitor and modulate brain circuits. Continuing investments by the Initiative have yielded exciting new tools for probing neural circuit function in diverse experimental models including humans; comprehensive cell atlases of mouse, non-human primate, and human brains; translational projects that shift technology from bench to clinic; first-in-human trials for new treatment paradigms; and a growing brain data ecosystem. Together, these projects are revolutionizing our understanding of neural circuit function, laying the groundwork for future precision circuit therapies for human brain disorders.

John Ngai, Ph.D. is the Director of the National Institutes of Health’s Brain Research Through Advancing Innovative Neurotechnologies®(BRAIN) Initiative. Dr. Ngai earned his bachelor’s degree in chemistry and biology from Pomona College, Claremont, California, and Ph.D. in biology from the California Institute of Technology (Caltech) in Pasadena. He was a postdoctoral researcher at Caltech and at the Columbia University College of Physicians and Surgeons before starting his faculty position at the University of California at Berkeley. Over 27 years as a Berkeley faculty member prior to joining NIH in 2020, Dr. Ngai trained 20 undergraduate students, 24 graduate students and 15 postdoctoral fellows in addition to teaching well over 1,000 students in the classroom. His work has led to publications in the field’s most prestigious journals as well as numerous U.S. and international patents. Dr. Ngai has received many awards including from the Sloan Foundation, Pew Charitable Trusts, and McKnight Endowment Fund for Neuroscience. As a faculty member, Dr. Ngai served as the director of Berkeley’s Neuroscience Graduate Program, Helen Wills Neuroscience Institute, and Functional Genomics Laboratory. He also provided extensive service on NIH study sections, councils and steering groups, including as previous co-chair of the NIH BRAIN Initiative Cell Census Consortium Steering Group. Dr. Ngai oversees the long-term strategy and day-to-day operations of the NIH BRAIN Initiative as it strives to revolutionize our understanding of the brain in both health and disease.

Keynote Speakers

Dan Rizzuto, Co-Founder, President, and Chief Technology Officer, Nia Therapeutics
Restoring Human Memory: Closed-Loop Brain-Computer Interfaces for Cognitive Recovery

Dan Rizzuto, Co-Founder, President, and Chief Technology Officer, Nia Therapeutics Abstract: Memory loss affects over 27 million Americans — caused by traumatic brain injury, neurodegenerative disease, and aging — yet no therapies exist to improve memory formation and retrieval. This talk will trace a decade-long arc from discovery to the clinic. Working with neurosurgical patients, we combined direct brain recording, stimulation, and artificial intelligence to identify the electrophysiological biomarkers that predict successful memory formation. In sham-controlled studies, AI-guided, closed-loop stimulation of white matter tracts in lateral temporal cortex improved human verbal memory performance by 28%. I will describe how these findings are being translated into an implantable, cloud-connected, closed-loop brain-computer interface for cognitive restoration.

Dr. Dan Rizzuto is the Co-Founder, President, and Chief Technology Officer of Nia Therapeutics, where he is building the world’s first personalized neurostimulation system to treat memory loss due to brain injury and degenerative disease. He developed Nia’s core technology at the University of Pennsylvania, demonstrating that personalized neurostimulation can significantly improve human memory performance. Dan earned his doctorate in the neuroscience of human memory at Brandeis University and completed postdoctoral training in brain-machine interfaces at Caltech. He has previously led large-scale neurotechnology development at Northstar Neuroscience, the Swedish Neuroscience Institute, and the Allen Institute for Brain Science.

Ranu Jung, Distinguished Professor and Founding Executive Director, The Institute for Integrative and Innovative Research

Ranu Jung, Ph.D., VCRI, Director of Institute for Integrative and Innovative Research

Distinguished Professor Ranu Jung is a trailblazing figure in neural engineering and visionary builder who cherishes challenges. She arrived in Northwest Arkansas to lay the foundation for the Institute for Integrative and innovative Research (I³R) by shaping its vision and mission, creating collaborative spaces, and fostering community and industry partnerships. Jung is driven by a deep sense of purpose to make a positive societal impact. From the first neuromorphic chip successfully connected to the spinal cord of a lamprey – to the first wireless, implantable, intrafascicular neural-interface system for restoring sensations to individuals with upper limb amputation, her teams have pioneered neurotechnology to bridge the gap between scientific discovery and clinical application. Jung holds a PhD and MS in Biomedical Engineering from Case Western Reserve University, a Bachelor’s with Distinction in Electronics & Communication Engineering from NIT Warangal, India, and an Honorary Doctorate from Aalborg University, Denmark.

Viktor Jirsa, Director, Inserm Institut de Neurosciences des Systèmes, Aix-Marseille-Université
From Brain Maps to Brain Twins

Viktor Jirsa Abstract: Neuroimaging has transformed brain description, yielding ever-richer maps of structure, function, and connectivity. Yet description does not explain. Virtual brain twins address this gap by augmenting brain maps with generative mechanism and an inference loop estimating latent parameters with quantified uncertainty. The Virtual Epileptic Patient (VEP) illustrates the workflow for drug-resistant focal epilepsy: a connectome from DTI, co-registered with MRI and CT, carries region-specific neural mass models, and epileptogenicity is estimated by Bayesian inversion, yielding posteriors and diagnostics. Having completed prospective clinical trial evaluation (EPINOV), the workflow generalizes to aging, neurodegeneration, and schizophrenia, deployed through EBRAINS.

Viktor Jirsa is Director of the Inserm Institut de Neurosciences des Systèmes at Aix-Marseille-Université in Marseille, France. Dr. Jirsa received his PhD in 1996 in Theoretical Physics and has since then contributed to the field of Theoretical Neuroscience through the development of large-scale brain network models based on realistic connectivity. His work has been foundational for network science in brain medicine and the use of personalized virtual brain models in clinical applications. He is Scientific Director of the clinical trial EPINOV, evaluating the use of virtual brain technology in epilepsy surgery. Dr. Jirsa serves as Chief Science Officer of the European digital neuroscience infrastructure EBRAINS (https://ebrains.eu) and Coordinator of the Virtual Brain Twin consortium (https://www.virtualbraintwin.eu/). He has been awarded several international prizes for his research including the first HBP Innovation prize (2021) and has published more than 200 scientific articles.

Emerging Neurotechnologies Track

Deblina Sarkar, Associate Professor, Massachusetts Institute of Technology, and Career Development Chair Professor, MIT Media Lab
Autonomous and Surgery-free Brain Implants for Focal Neuromodulation

Deblina Sarkar Abstract: Bioelectronic implants for brain stimulation provide critical tools for treating brain diseases as well as investigating fundamental biology but require invasive surgery. In this talk I will discuss a new class of implants, wherein intravenously introduced bioelectronic devices travel through the body’s global internal roadways i.e., the circulatory system, and autonomously implant (without any external guidance) in the target brain region, circumventing the need for any surgery. I will present how this enables targeted focal neuromodulation of deep brain regions in rodents. To achieve this, we built subcellular-sized wireless energy harvesting electronics with high power conversion efficiency and integrated them with cells to create unique cell-electronics hybrids. Thus, we fused electronic functionality with the biological transport and targeting capabilities of living cells. This technology can form the foundation for autonomously implanting bioelectronics with unprecedented access to the human body without surgery, opening new avenues for healthcare and research.
[1] A nonsurgical brain implant enabled through a cell–electronics hybrid for focal neuromodulation, Nature Biotechnology (2025)
Deblina Sarkar is an Associate Professor at Massachusetts Institute of Technology and Career Development Chair Professor at MIT Media Lab. She is also the founder of Cahira Technologies Inc which builds autonomous and surgery-free brain-computer interfaces. Her research fuses engineering, applied physics, and biology to develop disruptive technologies for nanoelectronic devices and create new paradigms for life-machine symbiosis. Her inventions include, among others, autonomous and non-surgical brain implant, bioelectronic technology to treat drug-resistant brain cancer, a 6-atom thick channel quantum-mechanical transistor overcoming fundamental power limitations, an ultra-sensitive label-free biosensor, technology that reveals previously undiscovered biological nanostructures and ultra-miniaturized antenna that can work wirelessly even from inside a living cell. She is the recipient of numerous awards and recognitions, including Innovative Young Engineer Recognition from National Academy of Engineers, the NIH Director’s New Innovator Award, the highest and rarely achieved impact score from NIH, the MIND Prize, the Science News 10 Scientists to Watch, the Distinguished Scientist Award, the NSF CAREER Award and others.

Mark J. Schnitzer, Professor, Depts. of Applied Physics, Biology, & Neurosurgery, and Investigator, Howard Hughes Medical Institute, Stanford University
Imaging Neural Interactions Between Brain Areas at Cellular Resolution

Mark Schnitzer Abstract: The mammalian brain shapes animal behavior through the concerted interactions of neural ensembles, within and across brain areas. Traditional neural recording techniques commonly lacked the capabilities to monitor such interactions at cellular resolution and with cell-type specificity across large neural populations. I will present emerging optical technologies for probing brain area interactions through imaging studies of neuronal calcium and voltage dynamics ensembles in cortical and subcortical brain regions of awake behaving rodents. One such technology is a robotic two-photon microscope, termed the ‘Octopus microscope’, with eight independently controllable imaging arms for imaging neuronal calcium dynamics in up to eight brain areas at once. Another innovation is an ultra-sensitive optical mesoscope for imaging neuronal voltage waves; with this instrument, we observed three new forms of traveling voltage waves, as well as coupling between voltage waves of distinct frequencies and propagation directions. A third technique, TRU-FACT (Total Registration Under Functional Activity, Connectivity, and Transcriptomics), delineates the genetic and projection classes of individual neurons monitored in behaving animals. Overall, by revealing the mesoscale dynamics, cell types, and interactions between regions in the mammalian brain, these technologies will help neuroscientists challenge and revise prevailing conceptions for how the brain generates perceptions, cognition, and actions.

Mark Schnitzer is an Investigator of the Howard Hughes Medical Institute (HHMI) and Anne T. & Robert M. Bass Professor in the Stanford Departments of Applied Physics, Biology, and Neurosurgery. After receiving a physics Ph.D. from Princeton, he started his research group in 1999 at Bell Laboratories, where he pioneered the use of micro-optics for fluorescence imaging at cellular resolution in live mammals. Schnitzer joined the Stanford faculty in 2003 and HHMI in 2008. His laboratory invents optical technologies to image brain activity at cellular resolution and uses these innovations to study neural circuit dynamics. Key inventions include tiny microscopes small enough to be mounted on the head of a freely behaving mouse. This technology won The Scientist’s Top Innovation of 2013 and 2019 Method of the Year from Nature Methods. Schnitzer has made notable service contributions and was a co-author of the BRAIN 2025 report, blueprint for the NIH BRAIN Initiative, and the U.S. National Academy of Sciences 2022 Decadal Survey of Biological Physics. Schnitzer is a recipient of a Vannevar Bush Fellowship, the highest award from the U.S. Dept. of Defense for basic research. His past trainees include 26 professors or group leaders now leading their own labs.

Hong Chen, Professor, Department of Biomedical Engineering and Department of Neurosurgery, Washington University
Neurosonics: Unlocking the Brain with Ultrasound to Transform Brain Health

Hong Chen, PhD Abstract: The brain remains one of the most challenging organs to access, monitor, and treat because of the protective skull, the blood-brain barrier, and the complexity of neural circuits. At the interface of engineering and medicine, ultrasound offers a powerful platform for overcoming these barriers: it can penetrate deep into the body, be focused with millimeter-scale precision, and interact with tissue through a range of biophysical mechanisms. In this talk, I will introduce Neurosonics as a growing field that uses ultrasound as a noninvasive interface with the brain. I will highlight emerging applications in brain disease diagnosis, targeted therapy, and neural modulation, illustrating how engineering innovation can create new opportunities to understand the brain and improve brain health.

Hong Chen, PhD, is a Professor in the Department of Biomedical Engineering and the Department of Neurosurgery at Washington University in St. Louis. She leads the Chen Ultrasound Lab, where her research focuses on developing ultrasound technologies for noninvasive brain access, diagnosis, and therapy. Dr. Chen is a recipient of the NIH Director’s Pioneer Award and the Provost’s Research Excellence Award at Washington University. She is a Fellow of the American Institute for Medical and Biological Engineering and the Acoustical Society of America, and a Senior Member of the National Academy of Inventors.

Clinical Applications and Impact Track

Jan Kubanek, Associate Professor, Washington University School of Medicine
Noninvasive Modulation of Deep Brain Circuits in Humans Using Focused Ultrasonic Waves

Jan Kubanek Abstract: Transcranial focused ultrasound can modulate deep brain circuits in humans in a focal, noninvasive, and selective manner. This talk will outline strategies for applying this modality to the human brain in an effective and safe manner. Moreover, the talk will discuss applications to causal brain mapping and for circuit-directed treatments targeting psychiatric and neurological disorders.

Jan Kubanek is an Associate Professor at Washington University School of Medicine. His lab has developed systems for controlled delivery of ultrasound into the brain of non-human primates and humans. The technology has been applied in clinical studies to target deep brain regions involved in chronic pain, depression, opioid addiction, and essential tremor. He is also a co-founder of SPIRE Therapeutics Inc., which aims to scale the technology for the benefit of researchers, clinicians, and patients.

Machine Learning and Computer Paradigms for Brain Discovery Track

Frances S. Chance, Sandia National Laboratories
Neural-Inspired Computational Primitives for Energy-Efficient Computation

Frances Chance Abstract: Biological neurons are computationally richer than simple ANN-style linear algebra operations. We hypothesize that this additional complexity will enable compact, scalable and energy-efficient computation in neuromorphic approaches. My current research seeks to identify key computational primitives of biological nervous systems and develop energy-efficient neuromorphic emulations of key single-neuron operations. I will discuss ongoing work to leverage these neuromorphic primitives for energy-efficient artificial intelligence models, and how these models may be implemented “at-the-edge” for brain discovery.

Frances Chance received her MS and PhD from Brandeis University, and her BS from the California Institute of Technology. She is currently a Distinguished Member of the Technical Staff in the Center for Computing Research at Sandia National Laboratories. Her research applies knowledge of biological nervous systems and neural circuit operations to develop and constrain novel neural-informed algorithms and brain-based technologies.

Jingyu Liu, Associate Professor at Computer Science, Neuroscience, and the TReNDS Center, Georgia State University
Enhancing Identification of Nonlinear Associations Between Neuroimaging and Genomics for Cognition.

Jingyu Liu Abstract: Research in imaging genomics aims to uncover the hidden relationships between brain phenotypes and genetic variation in the context of neurocognitive processes and psychiatric disorders. Linear approaches, such as genome-wide association studies of brain imaging-derived endophenotypes, have produced numerous important discoveries. Recent advances in deep learning have shifted the field toward modeling complex nonlinear imaging-genetic relationships. This talk will introduce an artificial neural network framework based on contrastive learning that enhances nonlinear imaging-genomic associations, and present its applications in elucidating the neural and genetic basis of working memory capacity in older adults and characterizing brain development during adolescence.

Dr. Jingyu Liu received her Ph.D. degree in Electrical Engineering from University of New Mexico, USA, in 2004, and Postdoctoral training at Olin Neuropsychiatry Research Center, Hartford, CT. She is currently Associate Professor at Computer Science, Neuroscience, and the TReNDS center, Georgia State University. Dr. Liu’s research focuses on identifying genetic and epigenetic influences on, or associations with, brain anomalies linked to mental illness, as well as on elucidating mechanisms underlying normal brain development. Brain based phenotypes are derived from MRI, EEG, and MEG, while molecular features include single nucleotide polymorphisms, copy number variation, DNA methylation, and gene expression profiles. Her work involves developing advanced computational methods to uncover latent relationships between brain endophenotypes, molecular and cellular genetic and epigenetic features, and environmental and behavioral assessments.

General Program

Wednesday, November 11, 2026

12:00 – 1:00 Registration Open, Exhibit and Poster Setup
1:00 – 2:30 Live Demonstrations and Student Engagement Activities
2:30 – 3:45 Panel – Using your Brain: Pathways and Career Opportunities
4:00 – 6:00 SPECIAL EVENT: The Aging Brain
IEEE AgeTech and IEEE Brain Mini-Symposium
6:15 – 6:30 Welcome from the IEEE Brain Chair
Introduction to IEEE Brain and Sponsoring Members
6:30 – 8:00 Welcome Reception, Poster Introductions, and Exhibits

Thursday, November 12, 2026

8:00 Registration Open, Coffee Break and Light Breakfast
8:30 Welcome and Opening Remarks, 2026 Workshop Chairs
8:45 – 11:00 Track 1: Emerging Neurotechnologies
Keynote: Dan Rizzuto, CEO, Nia Therapeutics
Deblina Sarkar, MIT and MIT Media Lab
Mark J. Schnitzer, Howard Hughes Medical Institute, Stanford University
Hong Chen, Washington University
11:00 – 11:15 Break
11:15 – 12:15 Plenary Address: John Ngai, Director, NIH BRAIN Initiative
The NIH BRAIN Initiative: Inventing the Future
12:15 – 1:15 Lunch, Posters and Exhibits Open
1:15 – 2:30 Panel – Engineering Trust: Implementing NeuroTech Standards at the Design Level
2:30 – 5:00 Track 2: Machine Learning and Computer Paradigms for Brain Discovery
Keynote: Viktor Jirsa, Director, Inserm Institut de Neurosciences des Systèmes
Frances Chance, Sandia National Labs
Jingyu Liu, Georgia State University
Guorong Rudy Wu, UNC School of Medicine
5:00 – 5:15 Break
5:15 – 6:15 Poster Introductions
6:15 – 7:45 Reception, Live Demonstrations, Posters and Exhibits Open

Friday, November 13, 2026

8:00 Registration Open, Coffee Break and Light Breakfast
8:30 Welcome, 2026 Workshop Chairs
8:45 – 11:00 Track 3: Clinical Applications and Impact
Keynote: Ranu Jung, Executive Director, The Institute for Integrative and Innovative Research
Jan Kubanek, Washington University School of Medicine
11:00 – 11:15 Break
11:15 – 12:30 Panel – Neurotechnology: Clinical Opportunities and Lived Experience
12:30 – 1:30 Lunch, Posters and Exhibits Open
1:30 – 2:30 Plenary Address
2:30 – 3:45 Panel – Looking Forward: The Future of Brain Research and Neurotechnology Innovation
3:45 – 4:00 Break
4:00 – 6:00 Awards, Closing Remarks, and Light Reception

All times are US Eastern Time.

Panel Descriptions

Using your Brain: Pathways and Career Opportunities
There are many pathways to building a successful career in brain research, neuroengineering, neuroimaging, computational neuroscience, and neurotechnology. Hear from industry representatives, government scientists, and academics about their experiences, the skills that have shaped their careers, and emerging opportunities across this rapidly evolving field.

Engineering Trust: Implementing NeuroTech Standards at the Design Level
As brain research and neurotechnology continue to advance, integrating technical and ethical standards during the design and pre-market phases is becoming increasingly important for scientific rigor, safety, and real-world impact. This educational session will explore how standards in neuroethics, data quality, reproducibility, brain-machine interfaces, and neuroengineering can strengthen research, improve user trust, and support more effective translation and deployment.

Neurotechnology: Clinical Opportunities and Lived Experience
Advances in brain research and neurotechnology are creating new opportunities to improve diagnosis, treatment, and quality of life, although important clinical and implementation challenges remain. Hear from clinicians, researchers, patients, and advocates about unmet needs, meaningful outcomes, and how scientific discoveries and emerging technologies can be translated into clinical care and everyday life.

Looking Forward: The Future of Brain Research and Neurotechnology Innovation
Where is the field today, and which scientific questions and emerging opportunities should shape its next phase? Join funders, government leaders, technologists, and researchers for a discussion of the discoveries, capabilities, and strategic investments most likely to deepen our understanding of the brain and lead to meaningful innovation.

CFP Now Open

We invite participants of the 2026 IEEE Brain Discovery and Neurotechnology Workshop to contribute interactive poster presentations and live demonstrations.

Posters enable you to present your current research to experts and receive valuable feedback, while live demonstrations allow presentation of a device or concept in addition to the poster. These sessions encourage networking and discussion among peers and offer the possibility of forming new collaborations. At least one author of the accepted submission will be required to register for the Workshop and to present a one-minute introductory slide prior to their scheduled session. Authors may also choose to submit a full-length version of their poster to the special issue in IEEE Transactions on Human-Machine Systems for possible publication. Paper submission information can be found here.

Posters and live demonstrations by students (undergraduate and graduate) and post-docs as first authors will be considered for the Best Poster and Best Demonstration Awards. Limited travel awards are also available to provide support for presenting students to attend the workshop.

Please use this FORM to submit your poster or live demonstration abstract.

Early abstract submissions due August 21, 2026. Call for abstracts open until October 13, 2026.

Groundbreaking solutions with the potential to improve quality of life and address neural disorders require an integrated approach among stakeholders. The goal of this workshop is to bring the engineering, clinical, and neuroscience communities together to focus on collaborative opportunities. Program highlights include plenary keynotes; symposiums on emerging neurotechnologies, machine learning and computer paradigms for brain discovery, clinical applications; panels; posters; live demonstrations; exhibits. Registration fees include all workshop activities, breaks, and receptions.

Registration Opens August 2026
Registration Fees (All fees are USD)

Early Rates (through October 1)
IEEE Member: $375 IEEE Student: $50
Non-Member: $425 Non-Member Student: $75
Regular Rates
IEEE Member: $425 IEEE Student: $50
Non-Member: $475 Non-Member Student: $75

Sponsorship
IEEE Brain invites industry and university sponsors to exhibit at the workshop. Please see the 2026 Sponsorship Form and email brain@ieee.org for more information.