Magazine - Computer
Important Dates Submission Deadline: 18 December 2025 Publication Date: August 2026 Neuromorphic computing is rapidly emerging as a transformative paradigm for intelligent systems, leveraging biologically inspired principles to overcome traditional performance and scalability bottlenecks. Recent breakthroughs in hardware, including mixed-signal neuromorphic processors, photonic computing elements, and non-volatile memory devices such as spintronics and memristive arrays, are enabling ultra-low-power, event-driven architectures tailored for real-time edge intelligence and post-Moore innovation. Simultaneously, advances in computational models, including spiking neural networks, synaptic plasticity mechanisms, and hybrid analog-digital frameworks, are redefining how learning and adaptation can be embedded natively in hardware. The tight co-design between physical substrates and algorithmic behavior offers new frontiers for energy efficiency, robustness, and contextual learning across domains ranging from autonomous sensing to cognitive robotics. This special issue of IEEE Computer Magazine will illuminate the convergence of architectural innovation and adaptive algorithms within neuromorphic systems. It aims to capture multidisciplinary progress in design methodologies, hardware-software integration, fabrication technologies, and real-world deployments. Contributions will showcase both foundational research and scalable implementations, fostering deep collaboration across academia, industry, and government labs. The issue will be of particular interest to researchers and practitioners in AI hardware acceleration, embedded and cyber-physical systems, post-Von Neumann architectures, and cognitive computing. Topics The topics of interest include, but are not limited to: Mixed-signal neuromorphic ICs and event-based sensor integration Photonic neuromorphic computing and ultra-fast signal processing Spintronic and memristor-based memory devices for neuromorphic learning In-memory and 3D memory architectures for post-Moore scalability Spiking neural networks: training, optimization, and deployment STDP, Hebbian learning, and biologically plausible adaptation Edge-intelligence platforms for robotics, IoT, and autonomous systems Benchmarking methodologies and co-simulation frameworks for neuromorphic evaluation Software toolchains for neuromorphic development and cross-layer co-design Ethical and societal implications of brain-inspired computation Submission Guidelines For author information and guidelines on submission criteria, visit…
Submissions Due: 18 December 2025
Magazine - Computer
Important Dates Submission Deadline: 13 April 2026 Publication: December 2026 A governance system can be understood as the full set of institutional arrangements, including rules and agents who create them, that regulate transactions within and across the boundaries of economic systems (Hollingsworth, Schmitter & Streeck, 1994). These arrangements encompass both state and non-state organizations and operate through formal and informal rules, norms, and beliefs. In the context of artificial intelligence (AI), governance systems determine how data is collected, shared, and safeguarded, how algorithms are trained and deployed, and how accountability is ensured (Shin & Ahmad, 2025). Effective AI governance is therefore critical to balancing innovation with ethical, legal, and social considerations. New AI-related regulative institutions are rapidly expanding to address these concerns. Some focus narrowly on specific activities, such as employment, while others provide comprehensive frameworks covering the full spectrum of AI use. For instance, in April 2023, New York City introduced definitive guidelines governing the use of automated employment decision tools in hiring and promotion (Paretti, Ray, Freedberg & McPike, 2023). At the same time, broader regulatory initiatives are underway in major jurisdictions including China, the EU, Japan, the U.K., and the U.S., each seeking to establish rules that ensure AI systems are safe, transparent, and accountable. In many cases, normative frameworks and rules have emerged to fill regulatory gaps, especially where formal agencies remain underdeveloped or absent (Kshetri, 2024). These mechanisms are typically prescriptive rather than coercive, guiding behavior without the force of law. Such institutions include voluntary guidelines and codes of conduct, technical standards, and certification programs, all of which provide structure and accountability in the absence of comprehensive regulation. As AI technologies rapidly expand across sectors such as healthcare, finance, education, defense, and government, the need to safeguard responsible use, transparency, and accountability has become more…
Submissions Due: 13 April 2026
Magazine - Computer
Important Dates Submissions deadline: 15 December 2025 Publication: July 2026 IEEE Computer magazine welcomes papers that examine how to detect and counteract disinformation and misinformation. Our goal is to identify and distill patterns and anti-patterns from which to learn, both as practitioners and as researchers.The rise of Generative AI has revolutionized the way we work, learn, and communicate. From code synthesis to language translation, generative tools promise efficiency and creative support. Yet, there is also a growing threat with generating and spreading disinformation and misinformation. For software engineers and computer scientists, this represents not just a technical challenge, but a profound ethical responsibility. A few examples illustrate how disinformation and misinformation are fueled by IT systems, and how the software community can counteract.A secretive network of around 3,000 “ghost” accounts on GitHub has been manipulating pages on the code-hosting website to promote malware and phishing links. Cybercriminals created fake forks of legitimate repositories. They injected malicious runtime code that, upon import, executed shell commands fetched from external URLs on project initialization. This fake repository operated like trusted software but delivered hidden malware. Code that looks safe may contain logic bombs, backdoors, or spyware. Countermeasures include verifying repository integrity such as commit, use static code analysis tools for any code being downloaded, and performing enhanced sandboxed execution before deploying or sharing code.Attackers are increasingly cloning senior managers’ voice via deepfake technology to spread disinformation in companies and across. A popular misuse is creating a sense of urgency that money must be transferred to a potential client or partner to receive a contract. A well-phrased hallucination might sound more believable than an awkward but accurate human answer. Countermeasures include implementing biometric voice anomaly detection, demanding multi-channel authentication workflows, and monitoring transaction behavior for signs of impersonation fraud. A remedy against a variety…
Submissions Due: 15 December 2025
Magazine - Computer
Important Dates December 15, 2025 (Submission deadline) March 15, 2026 (Feedback to authors) April 15, 2026 (Submission of revised papers) May 15, 2026 (Final notification to authors) Algorithmic artists, a.k.a generative artists, use code as a medium to produce artworks. When the code executes, it can drive any number of processes, from generating visuals and/or sound, to responding to user interactions or choreographing movements of robotic elements, among others. The code also includes some non-deterministic elements such as random numbers, live data processing or inputs from the audience. There exists a large number of software engineering concerns in relation to this artistic practice, spanning maintenance, evolution, programming abstractions and performance. For example, the "correctness" of the artistic output is non-trivial to measure as output aesthetics are difficult to formally quantify. The maintenance, preservation and restoration of algorithmic artworks is challenging, as they may rely on outdated runtimes or libraries, on online resources that quickly become unavailable, or on technology that is no longer available. It is challenging to balance performance for real-time interactions and domain-specific abstractions that support artistic expression with code. With this special issue, we aim to open a conversation between software engineers, generative artists and caretakers of these artworks, about the latest advancements at the intersection of software technology and algorithmic art. We encourage the development and application of software technology to strengthen all aspects of the software engineering lifecycle in algorithmic art projects. We encourage the authors to make their code and data publicly accessible. Code analysis for art maintenance and understanding maintenance of art-related code reverse engineering art-related code binary analysis of art-related code emulation for art-related code transpiling art-related code documenting art-related code case studies of software-based art preservation capture and replay for software-based artworks Software technology for generative art open source software and…
Submissions Due: 15 December 2025
Magazine - Computer
About Computer (Magazine) Computer, the flagship publication of the IEEE Computer Society, publishes peer-reviewed articles written for and by computer researchers and practitioners representing the full spectrum of computing and information technology, from hardware to software and from emerging research to new applications. The aim is to provide more technical substance than trade magazines and more practical ideas than research journals. Computer seeks to deliver useful information for all computing professionals and students, including computer scientists, engineers, and practitioners of all levels. Computer publishes diverse types of editorial content. Our Cover Features, Computing Practices, Perspectives, and Research Features provide a strong mix of case studies, opinion pieces, and solutions to technical problems. Authors can submit manuscripts for publication as Computing Practices, Perspectives, or Research Features on any topic within Computer‘s scope at any time. Submission Guidelines For author information and guidelines on submission criteria, please visit the Computer Author Information page. Please submit papers through the ScholarOne system, and be sure to select the special issue name. Manuscripts should not be published or currently submitted for publication elsewhere. Please submit only full papers intended for review, not abstracts. Important Submission Instructions: As of 19 November 2024, Computer Magazine will use the IEEE Author Portal for all new submissions. If you have not yet started the submission process, please use the IEEE Author Portal to submit your article. If you have started a draft of your submission OR if you submitted your paper prior to the IEEE Author Portal launch, you will finish the peer review life cycle of submission(s) currently under review through https://ieee.atyponrex.com/journal/sw-cs. You do not need to submit a new manuscript. All new and future submissions will be submitted entirely through the IEEE Author Portal. In addition to submitting your paper to Computer, you are also encouraged to upload the data related to your paper to IEEE DataPort.…
Magazine - Computer
Publication: May 2025 Topics relevant to computing professionals and scientists can be timely (sometimes fads of short duration), timeless, or both. In Computer, we seek a balance between timeless and timely computing technology articles. Software testing theory and practice nestles precisely in this sweet spot. In this forthcoming Special Issue of Computer, we will explore where software of all kinds of systems testing is today in both theory and practice. We seek papers that will explore the following and closely related questions: What are the most significant advances in testing in the last decade or decades? Has the cost of testing (as ratio of overall software cost) increased or decreased? How can time to market be minimized without compromising testing phases? How much more testing is practical for reducing security vulnerabilities, beyond testing basic functionality? Are we any better at knowing when to stop testing? Where do formal methods fit in with testing? What are the best ways to approach the test oracle problem? Many advanced testing methods exist for certain critical mission systems such as avionics. How can these techniques be applied efficiently in other industries? How have changes in management methods affected the use of testing? Does consumer software have adequate testing? How can traditional software test methods be applied to hardware description languages? What is the state of the art in automated testing? Testing of object-oriented vs in-OO software What are the latest developments in testing metrics? What are the latest Special approaches to testing open-source software, particularly for security testing and detection of auto-generated code? Many test methods for conventional software don't apply well to AI/ML. What methods can help? Submission Guidelines For author information and guidelines on submission criteria, please visit the Computer Author Information page. Please submit papers through the ScholarOne system, and be…
Submissions Due: 30 October 2024
