Calls for Papers
Open special issues,
guest-edited
Three special issues currently accepting submissions: a topical issue of Springer Nature’s SN Computer Science and two issues in MDPI journals. All three journals are indexed in Scopus, and the two MDPI titles also in the Web of Science. Contributions are welcome from researchers at any career stage. Each call links through to the publisher’s official page, where the authoritative scope, deadlines, and submission terms are maintained.
Now Accepting
Current calls
Listed by deadline, soonest first. Article processing charges, peer-review terms, and any updates to the closing date are set by the publisher — always check the official page before preparing a submission.
15 January 2027
Generative AI in Computing Education: Tools, Assessment Integrity, and System Studies of Adoption
SN Computer Science (Springer Nature) · ISSN 2661-8907 (online), 2662-995X (print) · Topical issue
Large language models can now complete most introductory programming assignments, write unit tests, explain compiler errors and refactor student code — and students use them whether or not a course allows it. Adoption has run ahead of study, and the research so far is fragmented: tool papers seldom measure learning, integrity studies seldom follow behaviour over time, and curriculum papers seldom report enough engineering detail to build on.
This topical issue asks for rigorous computer-science work that closes those gaps. It treats a computing programme as a system — with feedback loops, delays of several years between a first-year policy change and graduate competence, and unintended consequences — rather than as a set of separate course decisions. Engineering work that faces deployment at institutional scale is particularly in scope: privacy, cost, latency and reproducibility, including in low-bandwidth and low-compute settings. The aim is a collection that computing departments can act on, and one that establishes system modelling and simulation as a credible method in computing education research.
- Dr. Mathias M. Fonkam — Pennsylvania State University, Harrisburg, USA
- Dr. Narasimha Rao Vajjhala — Department of Computer Science, American University in Bulgaria
- Systems and tools — the design, architecture and evaluation of LLM-based tutors, feedback generators, code-comprehension aids, assessment pipelines, and provenance and integrity detection
- Empirical studies — in courses and programmes, with measured learning outcomes
- System studies of adoption — causal loop diagrams, stock-and-flow models and computer simulation that turn debates about generative-AI policy into testable models of curricular adoption
31 January 2027
Artificial Intelligence in Socio-Technical Systems
Systems (MDPI) · ISSN 2079-8954 · Section: Artificial Intelligence and Digital Systems Engineering
Artificial intelligence and data science are increasingly embedded in systems where social structures and technical infrastructure evolve together — healthcare, agriculture, education, energy distribution, governance, and smart cities. This issue asks what actually happens when they meet: how machine learning, natural language processing, and computer vision interact with organisational policy, human behaviour, ethical frameworks, and regulation once deployed in the field.
Both empirical and theoretical contributions are welcome, provided they take a holistic, systems-thinking view rather than treating the algorithm in isolation. Case studies from underrepresented regions and open-source implementations are particularly encouraged.
- Dr. Mathias Fonkam — College of Information Sciences and Technology, Pennsylvania State University, USA
- Dr. Narasimha Rao Vajjhala — Department of Computer Science, American University in Bulgaria
- AI-driven decision support in public services
- Explainable and fair AI for social good
- AI in cybersecurity and identity management
- Systems-dynamics modelling of AI and data-science engagements
- Human–AI collaboration in software development
- The effect of large language models on learning and critical thinking
Six papers are already published in this issue and freely available — the call remains open until the deadline above. Read them on the call page ↗
From this issue: Talking Face Generation in Socio-Technical Systems: A Systematic Review of Deep Learning Architectures, Deployment Contexts, and Governance Frameworks — Salahudeen et al. (2026), DOI 10.3390/systems14101198
From this issue: Machine Learning and Data Science for ESG Compliance Measurement in Financial Software Engineering Projects: A Single-Case Socio-Technical Systems Analysis — Strang & Vajjhala (2026), DOI 10.3390/systems14080990
17 April 2027
Digital Supply Chains Management and Sustainability
Sustainability (MDPI) · ISSN 2071-1050
Artificial intelligence, blockchain, the Internet of Things, big-data analytics, cloud computing, and digital twins have changed what is visible and controllable across a global supply network. At the same time, regulation, stakeholder expectation, and the UN Sustainable Development Goals are pushing organisations to build Environmental, Social, and Governance principles into every part of supply chain operations. This issue sits at that intersection.
Substantial gaps remain in how digital capability is actually converted into measurable sustainability outcomes — data interoperability, cyber risk, the digital divide between supply chain partners, the ethics of algorithmic decision-making, and the measurement of sustainability performance once a chain has been digitalised. Recent pandemic and geopolitical disruption has made the case for resilient, digitally enabled, sustainable architectures more urgent. Original research, systematic reviews, and case studies are all welcome.
- Dr. Narasimha Rao Vajjhala — Department of Computer Science, American University in Bulgaria
- Prof. Dr. Kenneth David Strang — Department of Business, University of the Cumberlands, USA; W3-Research
- Machine learning for supply-chain optimisation and demand forecasting
- Blockchain-enabled traceability, transparency, and ESG compliance
- IoT and sensor technologies for real-time monitoring and impact reduction
- Big-data analytics in sustainable procurement, logistics, and distribution
- Digital twins and simulation for resilient, sustainable chain design
- Cyber risk and security governance in digitalised supply ecosystems
- ESG measurement frameworks and digital reporting tools
- Industry 4.0 and 5.0 in sustainable manufacturing
- Digital transformation for SME supply chains in developing economies
- Circular economy and reverse logistics on digital platforms
From this issue: Regulatory Volatility in Digital Supply Chains: An Information Systems Analytics Study of Decision-Maker Risk Perceptions and Sustainability-Related Outcomes — Strang & Vajjhala (2026), DOI 10.3390/su18189359
Indexing & Ranking
Where these journals sit
Quartiles are often quoted without saying which system produced them. The three in common use disagree, because they rank different journal populations against different metrics. The figures below name their source.
SN Computer Science
- Scopus: indexed since 2020. On CiteScore 2025 it is Q1 in Computational Theory and Mathematics and Q2 in its five other categories.
- SJR (Scimago, built on Scopus): 0.445 for 2025 — Q2 in four categories, Computational Theory and Mathematics among them, and Q3 in Artificial Intelligence and in Computer Science Applications.
- Also indexed in dblp, the ACM Digital Library and Google Scholar.
- Hybrid journal: open access is optional.
Sustainability
- Scopus: indexed since 2009; CiteScore 8.9. Q1 on CiteScore in most of its subject categories.
- SJR (Scimago, built on Scopus): 0.750 for 2025 — Q1, its best quartile, in Geography, Planning and Development, held since 2020; Q2 in its six other categories.
- Web of Science: SCIE and SSCI. Journal Impact Factor 4.1.
- h-index 242 · open access · semimonthly.
Systems
- Scopus: indexed since 2013; CiteScore 5.4 — Q1 in Modeling and Simulation.
- SJR (Scimago, built on Scopus): Q2 across its categories — a stricter read than CiteScore gives.
- Web of Science: SSCI. Journal Impact Factor 3.8 (2025), five-year 3.4; JCR Q1 in Social Sciences, Interdisciplinary.
- Also in Ei Compendex and dblp · open access · monthly.
In short: all three are Q1 journals on Scopus’s own CiteScore metric in at least one subject category, and the two MDPI titles are also Q1 somewhere in the Web of Science JCR — but the stricter SJR quartile puts Sustainability at Q1 in one category and Q2 in the rest, and Systems and SN Computer Science at Q2 at best. Quartile always depends on the metric and the subject category, so it is worth quoting both together. Figures are as published by the sources in 2026 and are revised annually.