A quantum computer is a computer that exploits quantum mechanical phenomena. On small scales, physical matter exhibits properties of both particles and waves, and quantum computing leverages this behavior using specialized hardware. Classical physics cannot explain the operation of these quantum devices, and a scalable quantum computer could perform some calculations exponentially faster than any modern "classical" computer. In particular, a large-scale quantum computer could break widely used encryption schemes and aid physicists in performing physical simulations; however, the current state of the art is largely experimental and impractical, with several obstacles to useful applications.
Reproducibility, closely related to replicability and repeatability, is a major principle underpinning the scientific method. For the findings of a study to be reproducible means that results obtained by an experiment or an observational study or in a statistical analysis of a data set should be achieved again with a high degree of reliability when the study is replicated. There are different kinds of replication but typically replication studies involve different researchers using the same methodology. Only after one or several such successful replications should a result be recognized as scientific knowledge.
Neuromorphic computing is an approach to computing that is inspired by the structure and function of the human brain. A neuromorphic computer/chip is any device that uses physical artificial neurons to do computations. In recent times, the term neuromorphic has been used to describe analog, digital, mixed-mode analog/digital VLSI, and software systems that implement models of neural systems. The implementation of neuromorphic computing on the hardware level can be realized by oxide-based memristors, spintronic memories, threshold switches, transistors, among others. Training software-based neuromorphic systems of spiking neural networks can be achieved using error backpropagation, e.g., using Python based frameworks such as snnTorch, or using canonical learning rules from the biological learning literature, e.g., using BindsNet.
Ian Tremere Foster is a New Zealand-American computer scientist. He is a distinguished fellow, senior scientist, and director of the Data Science and Learning division at Argonne National Laboratory, and a professor in the department of computer science at the University of Chicago.
The expression computational intelligence (CI) usually refers to the ability of a computer to learn a specific task from data or experimental observation. Even though it is commonly considered a synonym of soft computing, there is still no commonly accepted definition of computational intelligence.
In computer science, interactive computing refers to software which accepts input from the user as it runs.
IPython is a command shell for interactive computing in multiple programming languages, originally developed for the Python programming language, that offers introspection, rich media, shell syntax, tab completion, and history. IPython provides the following features:
Vera Nikolaevna Kublanovskaya was a Russian mathematician noted for her work on developing computational methods for solving spectral problems of algebra. She proposed the QR algorithm for computing eigenvalues and eigenvectors in 1961, which has been named as one of the ten most important algorithms of the twentieth century. This algorithm was proposed independently by the English computer scientist John G.F. Francis in 1959.
Dinesh Manocha is an Indian-American computer scientist and the Paul Chrisman Iribe Professor of Computer Science at University of Maryland College Park, formerly at University of North Carolina at Chapel Hill. His research interests are in scientific computation, robotics, self-driving cars, affective computing, virtual and augmented reality and 3D computer graphics.
Christopher Ray Johnson is an American computer scientist. He is a distinguished professor of computer science at the University of Utah, and founding director of the Scientific Computing and Imaging Institute (SCI). His research interests are in the areas of scientific computing and scientific visualization.
Gerhard Klimeck is a German-American scientist and author in the field of nanotechnology. He is a professor of Electrical and Computer Engineering at Purdue University School of Electrical and Computer Engineering.
Mark S. Lundstrom is an American electrical engineering researcher, educator, and author. He is known for contributions to the theory, modeling, and understanding of semiconductor devices, especially nanoscale transistors, and as the creator of the nanoHUB, a major online resource for nanotechnology. Lundstrom is Don and Carol Scifres Distinguished Professor of Electrical and Computer Engineering and in 2020 served as Acting Dean of the College of Engineering at Purdue University, in West Lafayette, Indiana.
The Task Force on Rebooting Computing (TFRC), housed within IEEE Computer Society, is the new home for the IEEE Rebooting Computing Initiative. Founded in 2013 by the IEEE Future Directions Committee, Rebooting Computing has provided an international, interdisciplinary environment where experts from a wide variety of computer-related fields can come together to explore novel approaches to future computing. IEEE Rebooting Computing began as a global initiative launched by IEEE that proposes to rethink the concept of computing through a holistic look at all aspects of computing, from the device itself to the user interface. As part of its work, IEEE Rebooting Computing provides access to various resources like conferences and educational events, feature and scholarly articles, reports, and videos.
Ümit V. Çatalyürek is a professor of computer science at the Georgia Institute of Technology, and Adjunct Professor in department of Biomedical Informatics at the Ohio State University. He is known for his work on graph analytics, parallel algorithms for scientific applications, data-intensive computing, and large scale genomic and biomedical applications. He was the director of the High Performance Computing Lab at the Ohio State University. He was named Fellow of the Institute of Electrical and Electronics Engineers (IEEE) in 2016 for contributions to combinatorial scientific computing and parallel computing.
Amitabh Varshney is an Indian-born American computer scientist. He is an IEEE fellow, and serves as Dean of the University of Maryland College of Computer, Mathematical, and Natural Sciences. Before being named Dean, Varshney was the director of the University of Maryland Institute for Advanced Computer Studies (UMIACS) from 2010 to 2018.
Mark McMahon Wilde is an American quantum information scientist. He is an Associate Professor in the School of Electrical and Computer Engineering at Cornell University, and he is also a Fields Member in the School of Applied and Engineering Physics and the Department of Computer Science at Cornell.
Sandip Tiwari is an Indian-born electrical engineer and applied physicist. He is the Charles N. Mellowes Professor of Engineering at Cornell University. His previous roles were Director of National Nanotechnology Users Network, Director of the National Nanotechnology Infrastructure Network, and research scientist at IBM T. J. Watson Research Center. He is best known for his pioneer research in the fields of SiGe transistor and nanocrystal memory.
Manish Parashar is a Presidential Professor in the School of Computing, Director of the Scientific Computing and Imaging (SCI) Institute and Chair in Computational Science and Engineering at the University of Utah. He also currently serves as Office Director in the US National Science Foundation’s Office of Advanced Cyberinfrastructure. Parashar is the editor-in-chief of IEEE Transactions on Parallel and Distributed Systems, and Founding Chair of the IEEE Technical Community on High Performance Computing. He is an AAAS Fellow, ACM Fellow, and IEEE Fellow.
Luca P. Carloni is a professor and chair of the Department of Computer Science at Columbia University in the City of New York.. He has been on the faculty at Columbia since 2004. He is an international expert on electronic computer-aided design.
Jarek Gryz is a computer scientist, data analyst, author, and academic. He is a professor in the Department of Electrical Engineering and Computer Science and a member of the Cognitive Science Program in the Department of Philosophy at York University in Toronto, Canada.
