This is the latest of an ongoing series of interviews with the Editorial Board of our new Open Access journal, Biological Imaging. Next up, we have Professor Elsa Angelini an Executive Editor for the journal and co-lead of the Data Science Group in Institute of Translational Medicine and Therapeutics (ITMAT) at Imperial College, London.

Can you tell us a bit about your background, and what your current research is focused on?

I studied general engineering in France (Ecole Centrale de Nantes) and then biomedical engineering at Columbia University in the US. My first academic position was at Telecom Paris, a French engineering school, where I taught medical imaging and computer vision for 8 years. I then moved back to Columbia University for 5 years and then to the UK, being now at Imperial College London, as co-lead of the ITMAT Data Science group, based in the faculty of Medicine. I also spent a 5-month sabbatical in Australia.

Regarding my research in biological imaging, I worked on compressed-sensing acquisitions for microscopy images. My current research focuses on machine learning for quantitative diagnosis tools, disease phenotyping as well as image enhancement and quantification. I have particular interests in the domain-specific “intelligence” we can add in the raw data acquisition, encoding, preparation, and the formulation of “meaningful” learning tasks, while handling for uncertainty in the annotations, minimizing level of supervision, and taking into account biases in the available training cohorts.

What has been your biggest challenge/greatest achievement in your career so far?

Moving locations twice in 10 years, for family reasons, certainly offered opportunities but also challenges in my career path. My greatest achievement is all the MSc – PhD students – Post docs that I supervised, hoping that I had a positive impact on the scientists and professionals they have become. From their smiles on defense-days and their thank-you notes in their thesis, looks like so far they enjoyed their time working with me… This is certainly the part I enjoy the most in my daily activities (even though it is strange to age while this category of collaborators does not age – which is part of the challenge too). Being a woman never felt as a challenge despite being in a field where we are clearly under-represented, but I hope to have (modestly) inspired younger women to believe in their scientific and career ambitions

Why did you decide to become an Executive Editor?

I have been aware of the ambition of Jean-Christophe Olivo Marin to create a new journal in the field of biological image computing for several years. When this finally became a reality and that he offered me to join his executive board, I did not hesitate one minute. I hope to be able to have a positive impact in this role, which is new to me, with I hope will offer many opportunities to support rigorous science in the field of quantitative imaging for biosciences but to also build more cohesion and a sense of a community in this booming field.

How will Biological Imaging benefit your research field?

This new journal will help bring together a community that does not yet have a major journal nor a major technical meeting, like we have in medical image computing. There are many benefits that can be expected such as sharing algorithms, high-quality review papers of state-of-the-art methods, best-practice in evaluations of new methods, and open discussions on challenges and bottlenecks.

What excites you about Biological Imaging?

We will finally have a technical journal where we can follow new emerging ideas and concepts to handle computing challenges raised by constant innovations and progresses in the way biological images are acquired: higher resolution, faster acquisitions, new sensing strategies, new markers, etc. I also hope to see more biologists and physicists engaging in mathematical and computing models of the underlying physical and biological processes.

Why should authors publish in Biological Imaging?

Biological imaging has more to deliver than what the expert eyes can see. And there is always something new to look at or look for with fantastic promises on so many discoveries. When submitting to our journal, I strive to ensure fair handling and high-quality reviewing of any paper that comes my way, leading to trust among peers, open discussions and sharing as much as is possible to build upon rather than build against what exists.

How will this journal impact bioimaging research?

Hopefully, biologists will enjoy reading and citing papers published in this new journal, while strengthening their understanding on what quantitative methods can bring to biological research. This could lead to more collaborative work and even new research paradigms where domain specialists and data scientists design together image acquisition protocols.

How do authors benefit from Biological Imaging being open access?

Gold open access is obviously the best option to the benefit of the authors, readers and academic institutions. Thanks to a dedicated supporting staff at Cambridge Press, authors can expect high-visibility of published articles and opportunities to grow a community of authors and reviewers that share common goals, values and visions for the future of this field.

Biological Imaging is a single open access forum for important bioimaging research. It publishes original reports, reviews and other article types on techniques and methods that use imaging approaches including: microscopy, image acquisition and processing, data mining and analysis, mathematical modelling and machine learning. Submit your papers here and follow the journal on Twitter, @blg_journal.