Workshop Accomplishments

The workshop is the longest-funded NSF workshop, with over 25 years of continuous support. The workshop has resulted in many new collaborations and scientific publications from participants, and has trained over 2000 participants. See this unfiltered list of recent google scholar citations mentioning "Telluride Neuromorphic". A few of the articles, papers and books resulting from workshop collaborations are highlighted below, see also Videos from past workshops to see a few examples of real time demonstrations.

Former workshop participants have founded startups (e.g. Intan Technologies, (intel) Nervana, Pixium Vision, inilabs, inivation, Chronocam, insightness, TeraDeep), have taken leadership positions at large industry (Amazon, Google, Intel, Comcast, Qualcomm), or are now professors at leading Universities (e.g. Yale, Purdue, Stanford, UCSD).

Past workshop participants have 2 out of the top 10 cited papers over the last decade at the IEEE Journal of Solid State Circuits. The cross-disciplinary nature of the workshop is shown by participants technical program organization at major scientific/technology conferences spanning electronics, computer vision, AI, robotics, and neuroscience, including ISSCC, ISCAS, BioCAS, CVPR, NIPS, SFN, and ARVO. Workshop organizers and participants have over 200,000 scientific citations.

Articles and publications from workshop collaborations

The Journal Frontiers in Neuromorphic Engineering

Neuromorphic EngineeringNeuromorphic systems carry out robust and efficient neural computation using hardware implementations that operate in physical time. Typically they are event- or data-driven, they employ low-power, massively parallel hybrid analog/digital VLSI circuits, and they operate using the same physics of computation used by the nervous system. Although there are several forums for presenting research achievements in neuromorphic engineering, none are exclusively dedicated to this increasingly large research community. Either because they are dedicated to single disciplines, such as electrical engineering or computer science, or because they serve research communities which focus on analogous areas (such as biomedical engineering or computational neuroscience), but with fundamentally different goals and objectives. The mission of Neuromorphic Engineering is to provide a publication medium dedicated exclusively and specifically to this field. Topics covered by this publication include:  Analog and hybrid analog/digital electronic circuits for implementing neural processes, such as conductances, neurons, synapses, plasticity mechanisms, photoreceptors, cochleae, etc.  Neuromorphic circuits and systems for implementing real-time event-based neural processing architectures.  Hardware models of neural and sensorimotor processing systems, such as selective attention systems, coordinate transformation systems, auditory and/or visual processing systems, sensory fusion systems, etc.  Implementations of neural computational systems found in insects, birds, mammals, etc.  Embedded neuromorphic systems, including actuated or robotic platforms which process sensory signals and interact with the environment using event-based sensors and circuits. To ensure high quality and state-of-the-art material, publications should demonstrate experimental results, using physical implementations of neuromorphic systems, and possibly show the links between the artificial system and the neural/biological one they model.

Recent publications from collaborators at Telluride