A major contributor to this article appears to have a close connection with its subject.(April 2019) |
Massimiliano Versace | |
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Born | Italy | 21 December 1972
Nationality | Italian |
Alma mater |
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Known for | Deep Learning Neural networks NASA SyNAPSE |
Awards | Fulbright Scholar |
Scientific career | |
Fields | Artificial Intelligence Deep Learning |
Institutions | Boston University Neurala |
Thesis | Spikes, synchrony, and attentive learning by laminar thalamocortical circuits (2007) |
Doctoral advisor | Stephen Grossberg |
Website | maxversace |
Massimiliano Versace (born December 21, 1972, in Monfalcone, Italy) is the co-founder and the CEO of Neurala Inc, [1] [2] [3] [4] [5] a Boston-based company building Artificial Intelligence emulating brain function in software and used in automating the process of visual inspection in manufacturing. [6] He is also the founding Director of the Boston University Neuromorphics Lab. [7] Massimiliano Versace is a Fulbright scholar and holds two PhDs in Experimental Psychology from the University of Trieste, Italy and Cognitive and Neural Systems from Boston University, USA. He obtained his BSc from the University of Trieste, Italy.
Versace grew up in Monfalcone, Italy and came to the United States in 2001 as a Fulbright scholar. He holds a masters in psychology from the University of Trieste and two PhDs (Experimental Psychology, University of Trieste, Italy—Cognitive and Neural Systems, Boston University, USA). As Artificial Intelligence Professor at Boston University, he founded the Neuromorphics Lab, [8] [7] [9] [10] and in 2009-2011 the lab led a main research thrust in the DARPA SyNAPSE in collaboration with Hewlett-Packard designing artificial nervous systems, based on deep learning, implemented on novel memristor-based devices. In December 2010, Versace published a cover-featured articled on the IEEE Spectrum [11] describing the roadmap to develop a large scale brain model making use of memristor based technologies.
The model designed by Versace and his colleagues, termed Modular Neural Exploring Traveling Agent (MoNETA) [11] was the first large-scale neural network model to implement whole-brain circuits to power a virtual and robotic agent compatibly with memristor-based hardware computations. A cover page article in IEEE Computer [12] features the software platform and modeling implemented by the joint HP and Boston University teams, and the March 2012 edition of IEEE Pulse [13] features his lab work on brain modeling. From 2011 to 2016, Versace and his team at Neurala [14] worked with NASA and successfully built deep learning models able to learn power navigation and perception for exploring novel environments in real-time. [15] [16] [17] [18] [19] [20] [21]
His work has also been featured in TIME Magazines, [22] New York Times, [23] Nasdaq, [24] The Boston Globe, [25] Xconomy, [26] IEEE Spectrum, [27] Fortune, [28] CNBC, [29] The Chicago Tribune, [26] TechCrunch, [30] VentureBeat, [31] Associated Press, [32] Geek Magazine, [33] and is a TEDx [21] speaker.
In 2006, with two colleagues from Boston University, he co-founded Neurala [14] Inc. to bring this technology to market [34] in applications ranging from robots, to drones, and other smart devices. [35] [36] [37] [38]
Versace is a recipient of the Fulbright Fellowship in 2001. Career and company awards include:
Versace is also recipient of the CELEST Award for Computational Modeling of Brain and Behavior in 2009, and was awarded top cited article 2008–2010 in Brain Research .
Massimiliano Versace's pioneered research in continual learning [4] [43] [44] [21] neural networks, in particular applied to cortical models of learning and memory, and how to build intelligent machines equipped with low-power, high density neural chips that implement large-scale brain circuits of increasing complexity. His Synchronous Matching Adaptive Resonance Theory (SMART) model [45] [38] shows spiking laminar cortical circuits self-organize and stably learn relevant information, and how these circuits be embedded in low-power, memristor-based hybrid CMOS chip and used to solve challenging pattern recognition problems. His work has been featured on Fortune, [46] Inc, [47] Tech Crunch, [48] IEEE Spectrum, [49] Venture Beat, [50] among others.
Robotic control is the system that contributes to the movement of robots. This involves the mechanical aspects and programmable systems that makes it possible to control robots. Robotics can be controlled by various means including manual, wireless, semi-autonomous, and fully autonomous.
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Stephen Grossberg is a cognitive scientist, theoretical and computational psychologist, neuroscientist, mathematician, biomedical engineer, and neuromorphic technologist. He is the Wang Professor of Cognitive and Neural Systems and a Professor Emeritus of Mathematics & Statistics, Psychological & Brain Sciences, and Biomedical Engineering at Boston University.
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A memristor is a non-linear two-terminal electrical component relating electric charge and magnetic flux linkage. It was described and named in 1971 by Leon Chua, completing a theoretical quartet of fundamental electrical components which also comprises the resistor, capacitor and inductor.
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SyNAPSE is a DARPA program that aims to develop electronic neuromorphic machine technology, an attempt to build a new kind of cognitive computer with form, function, and architecture similar to the mammalian brain. Such artificial brains would be used in robots whose intelligence would scale with the size of the neural system in terms of the total number of neurons and synapses and their connectivity.
A cognitive computer is a computer that hardwires artificial intelligence and machine learning algorithms into an integrated circuit that closely reproduces the behavior of the human brain. It generally adopts a neuromorphic engineering approach. Synonyms include neuromorphic chip and cognitive chip.
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Hai (Helen) Li is a Chinese-American electrical and computer engineer known for her research on neuromorphic engineering, the development of computation systems based on physical artificial neurons, and on deep learning, techniques for using deep neural networks in machine learning. She is Clare Boothe Luce Professor of Electrical and Computer Engineering and chair of the Electrical and Computer Engineering department at Duke University.
BrainChip is an Australia-based technology company, founded in 2004 by Peter Van Der Made, that specializes in developing advanced artificial intelligence (AI) and machine learning (ML) hardware. The company's primary products are the MetaTF development environment, which allows the training and deployment of spiking neural networks (SNN), and the AKD1000 neuromorphic processor, a hardware implementation of their spiking neural network system. BrainChip's technology is based on a neuromorphic computing architecture, which attempts to mimic the way the human brain works. The company is a part of Intel Foundry Services and Arm AI partnership.
The Caravelli-Traversa-Di Ventra equation (CTDV) is a closed-form equation to the evolution of networks of memristors. It was derived by Francesco Caravelli, Fabio L. Traversa and Massimiliano Di Ventra to study the exact evolution of complex circuits made of resistances with memory (memristors).