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Celebrating the International Day of Women and Girls in Science

Celebrating the International Day of Women and Girls in Science

Milan, 11 February 2023

At the recent Hackathon “Deep Learning in Fiji”, organized by AI4Life and Global Bioimaging at the Human Technopole, several talented and accomplished women engineers made their mark.

As the world celebrated the International Day of Women and Girls in Science during the Hackathon, we took the opportunity to highlight the contributions of the female participants to the hackathon. Read below their trajectories and accomplishments.

Caterina Fuster-Barceló

Caterina is a post-doctoral researcher immersed in AI4Life with Dr Arrate Muñoz Barrutia. In December 2022, she defended a PhD in Computer Science and Technology with a cum-laude mention obtained at Carlos III University of Madrid (UC3M), Spain, under the supervision of Dr Pedro Peris and Dr Carmen Cámara. She possesses a BSc in Telematics Engineering from the University of the Balearic Islands (UIB) and an MSc in Cybersecurity for the UC3M. One of her great passions is sharing the knowledge she obtained these last years with different communities. For this reason, she is participating in Skype A Scientist and has explained her thesis to people from different backgrounds at different conferences that you will find on her website.

Hackathons are a great opportunity to meet personally who you are working with. Being able to talk and work face to face is a rich experience that sometimes we forget how important it is. So glad that I have met those amazing people from all around the globe to share knowledge, skills and drinks!
Caterina Fuster-Barceló

Estibaliz is a mathematician by training and an expert in biomedical image analysis. She did her PhD at Universidad Carlos III de Madrid (Spain) with Prof. Arrate Muñoz-Barrutia and Prof. Denis Wirtz on the study of 3D cancer cell motility. Currently, she’s an EMBO postdoctoral fellow within the group of Prof. Ricardo Henriques at the Instituto Gulbenkian de Ciência in Portugal. She is heavily involved in the bioimage analysis community, more particularly in the development of deepImageJ, ZeroCostDL4Mic, DeepBacs and the BioImage Model Zoo. She also collaborates in the Cell Tracking Challenge and she’s a trainer in NEUBIAS training school for BioImage Analysts, EMBO practical courses on image processing, EMBL-EBI courses for Microscopy Data Analysis, Neurophotonics Summer School at CERVO institute & Universidad Laval, and the DL@MBL. Find out more about her career on her website and Twitter account.

In AI4Life, Estibaliz works on the connection between the resources that build models (ZeroCostDL4Mic) and consume them (deepImageJ), and the BioImage Model Zoo.

Estibaliz Gomez de Mariscal
Fiona Inglis

Fiona is currently a Research Software Engineer developing QuPath, a software for viewing, processing and quantifying microscopic images with a specific focus on large whole-slide images. She was first exposed to the imaging world while working as a slide-scanning imaging technician for the University of Edinburgh, after her first BSc in infectious diseases. 2 years on, she switched her career path to web development as she wanted to pursue programming full-time after enjoying scripting imageJ macros for researchers. Fiona completed another BSc alongside working, this time in Software Development, and then she found out about the opportunity to be part of Pete Bankhead’s growing QuPath team. This role has allowed her to combine her interests and has introduced her to a fantastic community, working together to put cutting-edge AI tools into researchers’ hands.

This was my first hackathon and therefore I planned to absorb as much knowledge as possible from those around me. Being at an in-person event after working remotely for so long was very refreshing and hugely beneficial to knowledge sharing and discussions. I spent the time understanding QuPaths current integration of deep learning, exploring the tools developed by others at the event and ways to increase the compatibility of these tools with each other.

Fiona Inglis

Lucia is a biomedical and computer science engineer, working on AI4Life with Dr Arrate Muñoz Barrutia. She did an MSc in Information Engineering for Health in order to use her skills to make deep learning accessible and easy to use in the Life Sciences field. She is now involved in the development of new tools and resources for biomedical image analysis and the improvement of some currently existing like DeepimageJ.

In the past years, she has been involved in projects related to neurodegeneration and rare blood diseases, trying to understand these conditions and find new ways to diagnose them. She is committed to inspiring new generations to pursue STEM careers and making science easy to understand for people not in the field. For that matter she has been part of some initiatives like #JuntosXElCancer, creating didactical biomedical engineering content related to cancer research; and she has also been part of CEEIBIS, the national committee for biomedical and health engineering, organizing talks and events for students that want to pursue a career in this field. Know more about Lucia on her website.

During these days, I have been Improving deepImageJ plugin, to make it easier to use and creating new ImageJ plugins for image processing, using both classical and deep learning tools.
Lucia Moya-Sans
Lucia Moya-Sans
Beatriz Serrano-Solano

Beatriz Serrano-Solano is a software engineer with a PhD in Computational Biology from the University of Málaga (Spain). After successfully defending her thesis, she embarked on a journey to Germany where she continued her academic pursuits as a postdoctoral researcher at EMBL Heidelberg. There, she participated in scientific projects for the European project EOSCpilot and later EOSC-Life. Later, and for a bit more than two years, she served as the community manager for the European Galaxy project, showcasing her expertise in project management and community building. Today, she holds the position of Scientific Project Manager at Euro-BioImaging, where she is involved in the European project AI4Life.

In AI4Life, Beatriz leads the work package for Communication, Outreach and Training, being also heavily involved in the organisation of the Open Calls and Challenges that will take place during the 3 years of the project.

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Press Release

Press release

25.10.2022

Bridging Artificial Intelligence and Machine Learning with Bioimage Analysis

The AI4Life project launched today, marks an exciting chapter in the computational and life science research communities. The 4 million Horizon Europe funded project aims to create accessible, harmonized, and interoperable AI tools and methods for solving today’s microscopy image analysis problems.

THE GAP

Machine learning (ML) has accelerated frontier research in the life sciences, but democratized access to such methods is not a given. Limited access to necessary hardware/software and expertise combined with insufficiently documented methods hinder life science researchers from harnessing the power of such tools. Furthermore, while modern Artificial Intelligence (AI)-based methods typically generalize well to unseen data, no standard exists for sharing and fine-tuning pretrained models between different analysis tools. Compounding the issue, existing user-facing platforms operate entirely independently, often failing to comply with FAIR data and Open Science standards. Furthermore, the staggering pace of AI and ML development make it impossible for the non-specialist to stay up to date. Hence, urgent services and infrastructures to solve such problems are required to expand cutting edge life science research.

THE BRIDGE

The 10-partner consortium will build an open, accessible, community-driven repository of FAIR pre-trained AI models and develop services to deliver these models to life scientists, including those without substantial computational expertise. AI4Life will provide direct support and ample training activities to prepare life scientists for responsible use of AI methods. Additionally, AI4Life will drive community contributions of new models and interoperability between analysis tools. AI4Life will also facilitate Open calls and public Challenges aimed at providing state-of-the-art solutions to unsolved image analysis problems in life science research. 

AI4Life brings together AI/ML researchers, developers of open-source image analysis tools, providers of European-scale storage and compute services, and European life science Research Infrastructures – all united behind the common goal to enable life scientists to benefit from the untapped, tremendous power of AI-based analysis methods.

THE CORE OBJECTIVES

  • Democratize availability of AI-based image analysis methods
  • Establish standards for the submission, storage, and FAIR access of reference data, reference annotations (ground-truth), trained AI models, and trainable AI methods
  • Simple model deployment, sharing and dissemination through a new developer-facing service
  • Organize Open calls and Challenges for image analysis problems
  • Empower common image analysis platforms with AI integration
  • Organizing outreach and training events

THE TEAM

Our multidisciplinary team of experts in computational and life sciences as well as 4 European Research Infrastructures.

10

PARTNERS

3

YEARS

8

COUNTRIES

4M

EUROS