The first International Conference on Neuromorphic Computing (ICNC2021) will be held in Wuhan, China during October 11-14, 2021 to celebrate the 50th birthday of Memristor, postulated by Leon Chua in his seminal paper: Memristor-the missing circuit element published IEEE Transactions on Circuit Theory.
ICNC2021 aims to provide a high-level international forum for scientists, engineers, and educators to present the state of the art of research and applications in neuromorphic computing. The conference will feature plenary speeches given by world renowned scholars, regular sessions with broad coverage, and special sessions focusing on popular topics. Accepted papers will be submitted for inclusion into IEEE Xplore subject to meeting IEEE Xplore’s scope and quality requirements. The conference will favor papers representing advanced theories and innovative applications in neuromorphic computing.
Prospective authors are invited to contribute high-quality papers to ICNC2021. In addition, proposals for special sessions within the technical scopes of the conference are solicited. Special sessions, to be organized by internationally recognized experts, aim to bring together researchers in special focused topics. A special session proposal should include the session title, a brief description of the scope and motivation, names, contact information and brief biographical information on the organizers. Researchers interested in organizing special sessions are invited to submit formal proposals to [email protected]
Topics areas include, but not limited to: memristive devices for neuromorphic computing, dynamic memories on memristor-based circuits and systems, Circuit and system approaches and implications on neuromorphic computing based on memristor, Emerging technologies for neuromorphic computing, computational neuroscience, Machine intelligence algorithms for programming or training neuromorphic devices, mathematical modeling of neural systems, neurodynamic analysis, neurodynamic optimization and adaptive dynamic programming, embedded neural systems, probabilistic and information-theoretic methods, hybrid intelligent systems, supervised, unsupervised and reinforcement learning, brain imaging and neural information processing, neuroinformatics and bioinformatics, support vector machines and kernel methods, autonomous mental development, data mining, pattern recognition, robotic and control applications, deep learning, efficient simulation techniques for hardware and large-scale networks, machine intelligence algorithms for programming or training neuromorphic devices, automation, optimization.