Spanish National Research Council · University of Seville
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Funding for the research activities carried out at IMSE-CNM comes primarily from the participation in competitive tender processes. The research is then conducted out via agreements, projects and contracts with national and international public organizations and private companies and organizations.

Hybrid Enhanced Regenerative Medicine Systems
PI: Teresa Serrano Gotarredona
Type: Research project
Reference: 824164
Funding Body: European Union
Start date: 2019
End date: 2023
Funding: 438.511,25 €
Abstract: Brain disorders are the most invalidating condition, exceeding HIV, cancer and heart ischemia, with significant impact on society and public health. Regenerative medicine is a promising branch of health science that aims at restoring brain function by rebuilding brain tissue. However, repairing the brain is one of the hardest challenges and we are still unable to effectively rebuild brain matter. Epilepsy is particularly challenging due to its dynamic nature caused by the relentless brain damage and aberrant rearrangements of brain rewiring. To overcome the biological uncertainty of canonical regenerative approaches, we propose an innovative solution based on intelligent biohybrids, made by the symbiotic integration of bioengineered brain tissue, neuromorphic microelectronics and artificial intelligence, to effectively drive self-repair of dysfunctional brain circuits and we validate it against animal models of epilepsy. HERMES fosters the emergence of a novel biomedical paradigm, rooted in the use of biohybrid neuronics (neural electronics), which we name enhanced regenerative medicine. To this end, HERMES will promote interdisciplinary cross-fertilization within and outside the consortium; it will extend the concepts of enhanced brain regeneration to philosophy, ethics, policy and society to foster the emergence of a new innovation eco-system. Intelligent biohybrids will represent a major breakthrough to advance brain repair research beyond regenerative medicine and neurotechnology alone; it will bring new knowledge in neurobiology, cognitive neuroscience and philosophy, and new neuromorphic technology and AI algorithms. HERMES will bring a giant conceptual leap that will shift the concept of biomedical interventions from treating to healing. In turn, it will potentially generate major returns on health care and society at large by bringing previously unimaginable possibilities to defeat disorders that represent today a global major burden of disease.

Event-based cognitive vision system. Extension to audio with sensory fusion
PI: Teresa Serrano Gotarredona
Type: Research project
Reference: TEC2015-63884-C2-1-P
Funding Body: Ministerio de Economía y Competitividad
Start date: 01/01/2016
End date: 30/06/2020
Funding: 197.956,00 €
Abstract: The global goal of the COGNET project is to advance in the theoretical and technological development of event-based sensing and processing systems and demonstrate its potential to solve practical problems in a more efficient way than conventional technologies do. In particular, in the COGNET project we will address event-based vision and audition sensing, event-based vision and audition recognition systems and their off-line and on-line training, and the fusion of visual and auditive information to perform multisensory recognition tasks in real time. In COGNET, we are trying to demonstrate the superior performance of the event-based technology in two practical problems. The first one is binocular-based high-speed vehicle obstacle detection with few milliseconds response time, and the second one is visually guided speech recognition in a noisy environment.

NEUral computing aRchitectures in Advanced Monolithic 3D-VLSI nano-technologies
PI: Teresa Serrano Gotarredona web
Type: Research project
Reference: 687299
Funding Body: European Union
Start date: 01/01/2016
End date: 30/06/2019
Funding: 483.220,00 €
Abstract: We propose to fabricate a chip implementing a neuromorphic architecture that supports state-of-the-art machine learning algorithms and spike-based learning mechanisms. With respect to its physical architecture this chip will feature an ultra low power, scalable and highly configurable neural architecture that will deliver a gain of a factor 50x in power consumption on selected applications compared to conventional digital solutions; and a monolithically integrated 3D technology in Fully-Depleted Silicon on Insulator (FDSOI) at 28nm design rules with integrated Resistive Random Access Memory (RRAM) synaptic elements;
We will complete this vision and develop complementary technologies that will allow to address the full spectrum of applications from mobile/autonomous objects to high performance computing coprocessing, by realising (1) a technology to implement on-chip learning, using native adaptive characteristics of electronic synaptic elements; and (2) a scalable platform to interconnect multiple neuromorphic processor chips to build large neural processing systems. The neuromorphic computing system will be developed jointly with advanced neural algorithms and computational architectures for online adaptation, learning, and high throughput on-line signal processing, delivering:
1. An ultra-low power massively parallel non von Neumann computing platform with non-volatile nano-scale devices that support on-line learning mechanisms.
2. A programming toolbox of algorithms and data structures tailored to the specific constraints and opportunities of the physical architecture.
3. An array of fundamental application demonstrations instantiating the basic classes of signal processing tasks.
The neural chip will validate the concept and be a first step to develop a European technology platform addressing from ultra-low power data processing in autonomous systems (Internet of Things) to energy efficient large data processing in servers and networks.