Open Pulse Mini Hackathon


As an EPFL Life Science Engineer, my main interest is to do science with an impact. FAIR principals guide my work style, and I strive for user-centric infrastructure to encompass data science in the biomedical and governmental spheres. I have experience in Global Health, working with multi-hospital surveillance system for pandemics, as well as training data scientist (thegraphcourses.org). My core side-interests lie in ocean conservation notably cetacean conservation, biodiversity, and untreated health problematics from lower and middle income countries. I have solid hard skills in problem-solving, data engineering in AI/ML, and have developed soft skills in creativity and social integration. I have acquired domain knowledge in a diversity of fields: from biology-related sciences such as human gut microbiology, epidemiology, and environmental sciences, as well as social sciences such as anthropology and psychology. I am always happy to engage with new people on innovative and impactful thematics so please do reach out!


Robin joined the SDSC in 2022. He received an MSc. in Management, Economics & Consumer Studies from the University of Wageningen in the Netherlands. After his studies, he developed himself into a consultant in the area of ontology & linked data modelling, working mostly in the domain of local and national infrastructure projects. He has a great interest in standardization efforts in the field of semantic web technology standards and is actively working at SDSC with clients and collaborators to stimulate their adoption.


Carlos Vivar Ríos joined the SDSC in 2023, where he is part of the Open Research Data and Engagement Unit (ORDES). As a multidisciplinary data engineer, he brings a diverse background in biology, cognitive sciences, and bioinformatics from the University of Malaga. His multifaceted professional career spans several disciplines, including genomics at RIKEN in Yokohama, multidimensional image analysis in microscopy at the University of Lausanne (UNIL), and cellular biology modeling at INRIA in Lyon. Carlos has been involved in a variety of projects, such as analyzing astrocyte calcium dynamics, de novo sequencing Solea senegalensis, drug repurposing for Alzheimer's based on GWAS studies, conducting geospatial analysis for linguistic corpora, and assessing drought through remote sensing. He is dedicated to advancing reproducible research methods and actively supports the open science movement.


Oksana is a disruptive innovator bringing her positive energy to projects. Driven by her curiosity and can-do attitude she excels in industrial and academic contexts. Oksana earned her PhD in Life Sciences and Bioinformatics from the University of Lausanne after two MSc in Bioinformatics and in Information Systems from the University of Geneva. For more than 10 years, she has been committed to actively promoting the value of data science and advocating the best practices for reproducible and ethical research. She believes that Swiss Data Science Center is a key player in building a competitive data economy in Switzerland leveraging its innovative potential and renown commitment to quality.

Presentation
Open Pulse is an open research data toolset developed by EPFL Open Science and the SDSC. It automates the discovery and monitoring of open-source software outputs and their impact, laying the groundwork for making these contributions visible, measurable, and valued within research institutions. Unlike traditional metrics that focus on volume—such as downloads or citations—Open Pulse emphasizes community engagement and collaboration as the true measures of impact. By introducing meaningful quality metrics, it reveals which open-source software projects thrive, how communities interact, and the level of FAIRness, offering a clearer picture of open-source software contributions’ true value.
Target audience:
We welcome researchers, software developers, science administrators, data scientists, research software engineers, IT & library professionals, and anyone involved or interested in producing, maintaining, or assessing open-source software in research.
No coding expertise is required. Conceptual, strategic, and community insights are just as valuable as technical skills. If you care about how open-source software is recognized, evaluated, or sustained in academia, this is your chance to shape the future of open science.
Details
Date: 25.11.2025
Time: 09:00 - 15:00
Location: EPFL Lausanne, room BC 05
Programme
During a focused half-day sprint, you will join an interdisciplinary team of 3–4 participants to dive into the Open Pulse interface and tackle themed challenges - or pursue your own project idea related to open-source software.
Your team can prototype dashboards, interactive notebooks, simulations, or other creative outputs that show how Open Pulse metrics can inform research evaluation, strengthen engagement, and guide institutional strategy. You’ll have the opportunity to present your solution in a lightning demo session, receive practical guidance and peer feedback, and celebrate standout contributions during a prize ceremony.
Other events

AI for Decision Makers – Executive Course at ETH Zürich


Prof. Olivier Verscheure is the director and founder of the Swiss Data Science Center (SDSC). Olivier also co-leads a joint training program between EPFL and HEC Lausanne, specifically designed for senior executives. Since 2018, Olivier has been a member of the Board of Directors of Lonza, a global leader in the life sciences sector. This company provides products and services to the pharmaceutical, biotechnology, and specialized healthcare industries.Olivier began his career at IBM Research after earning his Ph.D. in computer science from EPFL. He held several research and leadership positions at the IBM T. J. Watson Research Center in New York and co-created and co-directed the IBM Research center in Dublin, Ireland, before joining the EPFL in 2016.


Silvia holds an MSc in Computer Science from EPFL and a PhD in Computer Science from the University of York, UK. She has been a senior research fellow at the University of Trento and later at Politecnico di Milano, Italy. Here, she had the chance to work on Marie Curie and ERC projects relating to natural language processing. From 2012 to 2019, she was a Senior Manager and NLP expert at ELCA Informatique Switzerland, whose AI department she helped create and expand. Silvia joined the Swiss Data Science Center in 2019 and is currently its Chief Transformation Officer, in charge of the team leading organizations to digital transformation.


Anna joined SDSC as a Data Scientist focusing on industry collaborations in July 2019. She completed her PhD in Bioinformatics at the University of Luxembourg, where she analysed large-scale heterogeneous datasets and leveraged multiple disciplines: Statistics, Network Analysis, and Machine Learning. Before joining SDSC, Anna worked as a Data Scientist at Deloitte Luxembourg, with a focus on computer vision and time-series analysis.Currently, Anna is a Principal Data Scientist based at the ETH Zurich office, where she leads biomedical collaborations with industry partners. Anna works on a range of projects: protein properties prediction, biomanufacturing optimization, statistical model evaluation and others.


Matthias Galipaud obtained his PhD in evolutionary biology in 2012 from the University of Burgundy in Dijon (France), and held postdoctoral positions as a mathematical biologist at the university of Bielefeld (Germany) and the university of Zurich, where he researched the evolutionary theories of aging and mate choice. In 2020, he became a data scientist, developing machine learning solutions for startups in Switzerland and Australia before joining the SDSC Innovation Team in November 2022.


Dan received an MSc in civil and environmental engineering from UC Berkeley and a Ph.D. from EPFL, where he developed models combining machine learning and geographic information systems to estimate renewable energy potentials on a large scale. After serving as a researcher/data scientist at Unisanté (Lausanne) and completing a one-year postdoc at the Quebec Artificial Intelligence Institute (Mila) in Montréal, Dan joined the SDSC Innovation team. His work has generally been focusing on crafting and tailoring machine learning methods and deep learning architectures for a variety of domains, most notably the spatio-temporal modeling and forecasting of environmental and energy related variables, as well as multiple applications in public health research.

Synthetic Data for Biomedical Applications


Before joining SDSC, Arshjot Khehra received his MSc in Artificial Intelligence from USI Lugano, where he completed his thesis on hierarchical graph reinforcement learning. Previously, he worked for 4+ years across India and Singapore gaining data science experience in insurance, logistics, and manufacturing sectors. He also holds a BSc in Industrial Engineering from PEC Chandigarh. Over the course of his career, Arshjot worked on a wide array of projects, such as, handwritten text recognition and generation, voice matching across phone call recordings, policy lapse rate prediction for customer retention, and automated insurance claim processing.


Matthias Galipaud obtained his PhD in evolutionary biology in 2012 from the University of Burgundy in Dijon (France), and held postdoctoral positions as a mathematical biologist at the university of Bielefeld (Germany) and the university of Zurich, where he researched the evolutionary theories of aging and mate choice. In 2020, he became a data scientist, developing machine learning solutions for startups in Switzerland and Australia before joining the SDSC Innovation Team in November 2022.


Valerio started his career working for 7 years as a particle-physics researcher at CERN. In 2016, he moved to consulting, applying data science in several industries. First, he joined the Quant team of Ernst & Young in Geneva. Later, he created his own company, SamurAI sàrl, providing consulting services for his clients. He also has a passion for teaching very complex subjects in simple terms. That is why he particularly enjoys offering training programs to private companies and universities. Valerio joined the SDSC in May 2022 as a Principal Data Scientist with the mission of accompanying industrial partners and other institutions through their data science journey.

Data Science for the Sciences


Guillaume Obozinski graduated with a PhD in Statistics from UC Berkeley in 2009. He did his postdoc and held until 2012 a researcher position in the Willow and Sierra teams at INRIA and Ecole Normale Supérieure in Paris. He was then Research Faculty at Ecole des Ponts ParisTech until 2018. Guillaume has broad interests in statistics and machine learning and worked over time on sparse modeling, optimization for large scale learning, graphical models, relational learning and semantic embeddings, with applications in various domains from computational biology to computer vision.
Contact us
Let’s talk Data Science
Do you need our services or expertise?
Contact us for your next Data Science project!

