¹ú²úÂÒÂ×

To mark the recent launch of three new journals in the field of computational science, we asked the Editors-in-Chief to introduce their journal and explain how it will address the needs of the researcher community. For this post, we interviewed Fernando Chirigati, Editor-in-Chief of Philip F. Yuan, Editor-in-Chief of , and Xinyue Ye, Editor-in-Chief of

What was it that first made you interested in computational science, and how has this interest evolved during your career?

Fernando Chirigati: I have always been fascinated by computer science and by what computers can do. I still remember when my parents bought my first computer: I was not only excited to have my hands on this new machine, but also very curious about how it actually worked! It didn’t take me too long to realize that my career would be related to computer science. I eventually decided to do my undergrad in computer engineering, which involved both the software and the hardware aspects. It was during my undergrad and through an internship that I started to become interested in how computers and computational techniques can be used to advance other fields. This eventually led me to pursue a Ph.D. in computer science, focused on computational reproducibility, data mining, and urban science.

Philip F. Yuan: I founded DigitalFUTURES Association in 2011. It has attracted global academics to promote discussion about contemporary issues in architecture, emphasizing the latest computational design and fabrication technologies. With the growth of digital culture, I’ve been practicing human-machine collaborative tectonics through the process of generation, simulation, optimization and construction. This has addressed broader ethical and social issues within our evolving technological culture, gradually forming a new frontier of disciplines that focus on the three future scenarios of smart habitat, virtual habitat, and space habitat.

Do you think interdisciplinary work and reproducibility are important areas that are addressed by this new journal launch? How does the new title meet these needs within the community?

Philip F. Yuan: Yes. Comparison with SCI journals in the similar field reveals that there are significant interdisciplinary intersections among Structure and Materials, Environment and Energy, Mathematics and Computability, Behaviour and Sociology, but there lack multidisciplinary intersections. Architectural intelligence has become a novel academic frontier, and the number of papers published about architectural intelligence rose approximately 38 times during 2001 to 2021. Thus, Architectural Intelligence appears to fill the gap for interdisciplinarity. 

Xinyue Ye: Computational Urban Science integrates the relational and physical spaces in the built environment, facilitating the convergence of computational and urban sciences methods as well as various disciplines. The development of more powerful computing technology, emerging big and open data sources, and theoretical perspectives on social-spatial process has revolutionized the way in which we investigate urban social-spatial interactions because reproducibility is the core of successful computational urban science.

Fernando Chirigati: Computational science is inherently interdisciplinary, since it’s all about using techniques and models from computer science and mathematics to address challenges in other scientific fields. What we do is to foster discussion of topics relevant to the entire community by bringing all computational scientists and enthusiasts together, in a single place. Reproducibility is also an important aspect of the journal. Because code is at the heart of all of our papers, we see the code as an essential aspect when determining whether a manuscript is suitable for publication with us: for every manuscript that goes to peer review, we do our best to ensure that at least one referee can provide feedback on the corresponding code. The goal here is to verify whether results are reproducible, and whether the provided code is a reusable resource to the community.

What makes your journal different from other journals in the field?

Xinyue Ye: A discussion of how computational and urban science could be further synthesized has oftentimes been limited due to the lack of forum and outlet for such publications. It is this lacuna that this new journal aims to fill. Computational Urban Science focuses on the intersection of computational sciences and urban sciences in building intelligent and resilient cities. Moreover beyond academia government agencies practitioners as well as engaged citizens are increasingly recognizing the linkages between the social and physical dimensions of the built environment, and they also serve as the readership of this journal.

Fernando Chirigati: It is not surprising that there is computational science work spread out across different journals – after all, different scientific areas use computational techniques in various ways. However, there are not many journals out there that put different computational science works together in a single place, where the focus is on the computational aspect. Nature Computational Science will fill this gap by providing a platform that includes not only original research articles, but also opinion pieces from this unique community. The goal here is to allow different fields of science to learn from each other.

Philip F. Yuan: Architectural Intelligence is guided by scientific design thinking and evidence-based architectural research methods. It reconstructs the architectural knowledge system, establishing a new paradigm for sustainable digital futures. It employs art and science, as well as data-oriented algorithms and establishes a new agenda through which architecture design, civil engineering, environmental engineering, computer science, social science, and other relevant disciplines generate novel knowledge.

What do you think have been the most important recent developments in this subject field, and are there areas that you predict could be particularly exciting in the near future?

Fernando Chirigati: Machine learning has certainly come to revolutionize different scientific areas. While I think researchers should use machine learning techniques with caution – such as by reducing unintended biases and by making sure that results are reproducible and interpretable – this area has had some exciting new developments that has played a big role in science. Looking ahead, I can see the quantum computing and the neuromorphic computing fields having interesting developments!

Xinyue Ye: Computational science has been creating a new paradigm through which all scientific disciplines query the world as well as dramatically increasing productivity in business, industry and management by creating cyberspace. For example, human actions and interactions in the digital form can manifest themselves as highly dynamic real-time social systems in the urban world, which enable governments to formulate appropriate policies for the relevant groups and communities. Going forward, more studies are needed to depict the interconnected patterns and relationships between cyberspace and physical space as well as perceived space.

Philip F. Yuan: We are living in an era when the physical-digital concepts in architecture need to be re-imagined. From digital twins to meta-universes, a series of technological trends have projected the future of architectural production and inhabitation on the planetary scale. In the recent World Robot Conference, MetaPrinter, the world’s first robotic printer developed by my team for the customized production of NFT architectural artworks, employed the support of blockchain technology to achieve fully encrypted design storage, file transfer, and production process. We need to fundamentally rethink the relationship between architecture, nature and human society in the phygital future. How can the phygital nature of architectural production and inhabitation offer a new model of sustainability rather than just merely providing more engineering solutions?

Is there potential for research published in the journal to reach beyond the scientific community and into policy?

Fernando: Absolutely! An example is a computational social science paper that we published on the effect of physical proximity on communication. Based on an 18-month study of 2,834 researchers in a North American university during the pandemic, lack of physical proximity due to lockdown resulted in a 39% drop in ‘new ties’ amongst researchers, which are considered to be vital for information spread. This can ultimately help organisations seeking the right balance of home and onsite working.

Philip F. Yuan: Yes. We have a special "commentary" section in every issue. The intention behind this section is to invite theoretical scholars of the field, and through their insightful "comments", to open the dialogs between science research and social policy. Among our inaugural articles is Mario Carpo’s recent which I believe could have profound impacts on our research field as well as our future society. 

Xinyue Ye: Our journal values the social and policy impacts of the research, as demonstrated in the following recent .

How does Springer help to amplify reach and visibility once an article has been published?

Philip F. Yuan: The first batch of articles of Architectural Intelligence will be promoted via our Launch Articles promotion designed for newly launched journals. The campaign is designed to announce the start of the journal publishing content and will circulate the first few articles among the research community. We will also spread the word via ¹ú²úÂÒÂ×’s social media accounts, especially our WeChat and Weibo accounts which have a significant amount of followers in China and beyond.

Fernando Chirigati: Nature Computational Science will use its dedicated to amplify the visibility of our manuscripts, and readers who subscribe to our mailing list will receive notifications with our monthly issues’ content. In addition, we also press release some of our papers, depending on their subject.

The latest issue of each journal can be found via the following links:  and