2013 - Hellman Fellow
His primary areas of investigation include Memristor, Crossbar switch, Nanotechnology, Neuromorphic engineering and Electronic circuit. His study in Memristor is interdisciplinary in nature, drawing from both Resistor, Thin film, Dopant and Memistor. His studies in Memistor integrate themes in fields like Inductor, Capacitor and Electrical element.
As a part of the same scientific study, Dmitri B. Strukov usually deals with the Crossbar switch, concentrating on CMOS and frequently concerns with Integrated circuit, Logic gate and Nanoelectronics. His Nanotechnology research incorporates themes from Optoelectronics, Joule heating, Condensed matter physics and Resistive switching. His Artificial neural network research is multidisciplinary, incorporating elements of Transistor and Electronics.
His main research concerns Memristor, Electronic engineering, Neuromorphic engineering, Electronic circuit and CMOS. The study incorporates disciplines such as Nanotechnology, Resistive random-access memory, Memistor, Artificial neural network and Optoelectronics in addition to Memristor. His Resistive switching research extends to Nanotechnology, which is thematically connected.
His Electronic engineering research incorporates elements of Integrated circuit, Electrical engineering, Analog computer and Flash memory. His research investigates the connection with Electronic circuit and areas like Crossbar switch which intersect with concerns in Multilayer perceptron. His CMOS study integrates concerns from other disciplines, such as Field-programmable gate array, Embedded system and Nanoelectronics.
Dmitri B. Strukov spends much of his time researching Neuromorphic engineering, Electronic circuit, Memristor, Electronic engineering and Mixed-signal integrated circuit. His biological study spans a wide range of topics, including Non-volatile memory, Computer hardware and Efficient energy use. Dmitri B. Strukov has researched Electronic circuit in several fields, including Synaptic weight and CMOS.
His Memristor study incorporates themes from Reinforcement learning, Nanotechnology and Crossbar switch. His work carried out in the field of Electronic engineering brings together such families of science as Amplifier, Analog computer and Electrical efficiency. His Artificial neural network study combines topics from a wide range of disciplines, such as Electrical engineering and Process.
His primary scientific interests are in Electronic circuit, Electronic engineering, Neuromorphic engineering, Memristor and Crossbar switch. His work deals with themes such as AND gate and Logic gate, which intersect with Electronic circuit. His Electronic engineering research includes themes of Artificial neural network, Resistive switching and Electronics.
Dmitri B. Strukov studied Neuromorphic engineering and Efficient energy use that intersect with Mixed-signal integrated circuit, Flash memory and Non-volatile memory. His Memristor research includes elements of Field-programmable gate array, CMOS and Stochastic neural network. His study looks at the relationship between Crossbar switch and fields such as Computer hardware, as well as how they intersect with chemical problems.
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The missing memristor found
Dmitri B. Strukov;Gregory S. Snider;Duncan R. Stewart;R. Stanley Williams.
Memristive devices for computing
J. Joshua Yang;Dmitri B. Strukov;Duncan R. Stewart.
Nature Nanotechnology (2013)
Training and operation of an integrated neuromorphic network based on metal-oxide memristors
Mirko Prezioso;Farnood Merrikh-Bayat;Brian Hoskins;Gina C. Adam.
Switching dynamics in titanium dioxide memristive devices
Matthew D. Pickett;Dmitri B. Strukov;Julien L. Borghetti;J. Joshua Yang.
Journal of Applied Physics (2009)
Memristor―CMOS Hybrid Integrated Circuits for Reconfigurable Logic
Qiangfei Xia;Warren Robinett;Michael W. Cumbie;Neel Banerjee.
Nano Letters (2009)
CMOL FPGA: a reconfigurable architecture for hybrid digital circuits with two-terminal nanodevices
Dmitri B Strukov;Konstantin K Likharev.
Exponential ionic drift: fast switching and low volatility of thin-film memristors
Dmitri B. Strukov;R. Stanley Williams.
Applied Physics A (2009)
High precision tuning of state for memristive devices by adaptable variation-tolerant algorithm
Fabien Alibart;Ligang Gao;Brian D Hoskins;Dmitri B Strukov.
Pattern classification by memristive crossbar circuits using ex situ and in situ training
Fabien Alibart;Elham Zamanidoost;Dmitri B. Strukov.
Nature Communications (2013)
Coupled Ionic and Electronic Transport Model of Thin‐Film Semiconductor Memristive Behavior
Dmitri B. Strukov;Julien L. Borghetti;R. Stanley Williams.
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