Meet the brilliant minds behind Dcode AI, dedicated to building a universal language for the brain.
CEO
A visionary and pioneer in the neurotech space, Tan has a proven track record of democratizing neuroscience research. By building the world's largest repository of non-invasive brain data, she has laid the groundwork for Dcode AI's core mission: to create a universal language for the brain. Her leadership guides the company in developing a foundational model that is not only scientifically groundbreaking but also globally accessible.
Chief Scientist
A physicist with over two decades of dedicated expertise in EEG research, Geoff is the scientific anchor of Dcode AI. He brings deep, hands-on experience in EEG devices, data, and machine learning. As Chief Scientist, he spearheads the validation of Dcode AI's universal foundation model, ensuring its robustness and scientific integrity. His work is critical to delivering a technology that can genuinely transform the neurotech landscape.
VP Engineering
With over 20 years of experience in neurotechnology, Patrick is a veteran in building and scaling complex tech solutions. As VP of Engineering, he leads the development of Dcode AI's core platform, translating groundbreaking research into a functional, reliable, and scalable product. His extensive background in the field is instrumental in ensuring Dcode AI's technology is poised to meet the demands of a rapidly evolving industry.
Foundation Model Lead
Soheila is a key architect of Dcode AI's core technology. As the Foundation Model Lead, she leverages her Ph.D. and a unique blend of academic and industry experience to build an ethically sound, robust, and scalable universal EEG model. Her expertise in differentially private data analysis and medical imaging ensures that Dcode AI's technology is powerful, secure, and ready for real-world applications in health and research.
AI Researcher
Navid is a leading AI Researcher at Dcode AI, responsible for some of its most significant technological breakthroughs. He is the lead author of seminal papers on EEG2Rep and EEG-X, which introduce cutting-edge transformer-based architectures for robust EEG representation. His work is foundational to the company's ability to create a platform that can generalize across different devices, tasks, and people.
AI Researcher
Jiazhen specializes in creating efficient, scalable AI architectures for complex data. As an AI Researcher, his contributions include co-authoring the "EEG Mamba paper," a groundbreaking work on using a Mamba-based architecture for long-context EEG modeling. His research enables the Dcode AI platform to process large-scale brain data with unparalleled speed and memory efficiency, paving the way for a highly performant universal foundation model.
Senior Research Engineer
Nam is a key contributor to the company’s foundational research, with deep expertise in self-supervised learning and time series modeling. A co-author of the EEG2Rep paper, he is directly responsible for developing the advanced AI architectures that allow the foundation model to learn robust representations from noisy, real-world EEG data. His work is essential to the scientific validation and core functionality of the platform.
Senior ML Ops Engineer
Cuong ensures that Dcode AI's powerful research models are ready for the real world. As a Senior ML Ops Engineer, he is an expert in bringing machine learning models from the lab into production. His work in building scalable and reliable systems for data management, model deployment, and monitoring is fundamental to Dcode AI’s product roadmap, making the universal foundation model accessible to developers and researchers globally.
ML Ops Engineer
Quoc ensures that Dcode AI's powerful research models are ready for the real world. As an ML Ops Engineer, his expertise is in bringing machine machine learning models from the lab into production. He is skilled in designing and developing scalable and reliable systems for model deployment, monitoring, and performance tracking , using tools like MetaFlow, VertexAI and TensorBoard. Quoc’s work is fundamental to Dcode AI’s mission of building a scalable and efficient foundation model, making it accessible to developers and researchers globally.
The global neurotechnology market is projected to reach over $50 billion by 2034, driven by the increasing demand for solutions to neurological disorders. Despite this growth, the market remains highly fragmented by device type and data protocol, creating a significant barrier to innovation. Dcode AI's universal foundation model is poised to solve this problem by creating a standardized language for the brain, unlocking new applications and accelerating breakthroughs in research, health, and consumer neurotech.
Interested in learning more about Dcode AI and our mission to build a universal language for the brain? We are actively engaged in discussions with strategic partners and investors.
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