Dr. Manuela Ferrario is an Associate Professor of Bioengineering at Politecnico di Milano. She joined the Editorial Board of Scientific Reports in 2018 and is a Senior Editorial Board Member.   

Her research focuses on biomedical signal processing, physiological modeling, and data-driven approaches for critical care. Her work integrates machine learning and systems physiology to better understand cardiovascular and autonomic regulation, particularly in conditions such as sepsis and shock. She is especially interested in extracting clinically actionable insights from complex, multimodal data, including omics and continuous monitoring signals. Through interdisciplinary collaborations, her goal is to support precision medicine and improve decision-making in intensive care settings. 

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We recently invited Dr Manuela Ferrario for a Q&A where they answered questions about their research and what it is to work as an Editorial Board Member at Scientific Reports. Some of the questions they answered are below:

What do you like most about being an Editorial Board Member for Scientific Reports?   

What I value most is the opportunity to engage with a wide range of research topics beyond my immediate field. This broad exposure helps me stay intellectually curious and continuously expand my perspective on emerging methods and applications. It is also rewarding to contribute to maintaining high scientific standards and to support the dissemination of robust and impactful research across disciplines. 

We know that finding reviewers is one of the hardest parts of an editorial role. Do you have any tricks on finding reviewers? If you were to give a piece of advice to other Editors, what would that be?    

Identifying suitable reviewers can be challenging, particularly in niche areas where there is a high degree of collaboration between researchers and potential conflicts of interest arise. I usually search databases such as PubMed or Google Scholar to find authors of recent and relevant publications. Looking at reference lists and related articles is also helpful. Expanding the search to slightly adjacent fields can reveal qualified reviewers who can offer a new perspective while still having the necessary expertise. 

Investing time in identifying the right reviewers is essential. Well-matched reviewers are more likely to accept the invitation and provide constructive, high-quality feedback. When possible, relying on trusted experts you know or have interacted with can increase acceptance rates. While the process may take longer initially, it ultimately leads to a more efficient and effective peer review process. 

How important is reproducibility in research? As an Editor, how do you help authors report reproducible results? 

Reproducibility is essential— methodology is the true core of any manuscript. As an Editor, I focus first on whether the methods are appropriate, clearly described, and positioned with respect to the existing literature. I also encourage transparency in data handling, model development, and validation, as these are key elements that allow other researchers to reproduce and build upon the work. 

Do you think Scientific Reports help reduce publication bias, and if yes – how?   

In principle, yes. A model that prioritizes methodological rigor over perceived impact can help reduce publication bias. However, this strongly depends on the responsibility of editors and reviewers. The involvement of multiple roles—editors, reviewers, and managing editors—provides checks and balances, but consistent application of these principles is key to achieving this goal in practice.   

What would you like to share with your fellow researchers on publishing in an inclusive journal?    

Publishing in an inclusive journal means that sound science is valued regardless of perceived impact. This places responsibility on authors to clearly define their research question, rigorously position their work within the literature, and ensure transparency in methods and results, especially through data and code sharing. Inclusivity is not about lowering standards—it is about applying them consistently and fairly across different topics and approaches. 

What are responsible ways to integrate AI into the peer review process, and how can editors feel empowered to explore these new tools to provide helpful solutions for authors, editors, reviewers, and AI experts? 

AI can serve as a helpful support tool in the editorial process by assisting with plagiarism detection, identifying overlapping or duplicated content, evaluating reporting quality, and suggesting potential reviewers. However, it should not replace expert human judgment. Transparency—particularly through the sharing of data and code—remains essential to maintain trust and reproducibility. While AI can improve efficiency and support editors, it also introduces potential risks, including the possibility of inheriting or amplifying biases present in its training data or algorithms. For this reason, editors should use AI critically, ensuring that final scientific and editorial decisions remain under human responsibility.   

How has the landscape in inclusive publication changed over the last 10 years?   

Over the past decade, inclusive publishing has shifted from a focus on selectivity and perceived impact toward a stronger emphasis on methodological rigor, transparency, and accessibility. There is greater recognition that valuable research can come from diverse disciplines, regions, and approaches. Open access, data sharing, and clearer reporting standards have contributed to this evolution. At the same time, the rapid growth in submissions has introduced new challenges in maintaining consistent quality and fairness. Inclusivity today means not only broadening participation but also ensuring that all contributions are evaluated with the same rigorous and transparent criteria.   

Lab page: People - DEIB  
Google Scholar: ‪Manuela Ferrario‬ - ‪Google Scholar‬