
SDSC Hackathon: ORD for the Sciences


Valerio started his career working for 7 years as a particle-physics researcher at CERN. There, he used state-of-the-art techniques to extract information from data, especially to search for traces of dark matter in particle collisions. Since 2016, he has worked in 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 Mai 2022 as a Principal Data Scientist with the mission of accompanying industrial partners and other institutions through their data science journey.


Luis is originally from Spain, where he completed his bachelor's studies in Electrical engineering, and the Ms.C. on signal theory and communications, both at the University of Seville. During his Ph.D. he started focusing on machine learning methods, more specifically message passing techniques for channel coding, and Bayesian methods for channel equalization. He carried it out between the University of Seville and the University Carlos III in Madrid, also spending some time at the EPFL, Switzerland, and Bell Labs, USA, where he worked on advanced techniques for optical channel coding. When he completed his Ph.D. in 2013, he moved to the Luxembourg Center on Systems Biomedicine, where he switched his interest to neuroscience, neuroimaging, life sciences, etc., and the application of machine learning techniques to these fields. During his 4 and a half years there as a Postdoc, he worked on many different problems as a data scientist, encompassing topics such as microscopy image analysis, neuroimaging, single-cell gene expression analysis, etc. He joined the SDSC in April 2018. As Lead Data Scientist, Luis coordinates projects in various domains. Several projects focus on the application of natural language processing and knowledge graphs to the study of different phenomena in social and political sciences. In the domains of architecture and engineering, Luis is responsible for projects centered on the application of novel generative methods to parametric modeling. Finally, Luis also coordinates different projects in robotics, ranging from collaborative robotic construction to deformable object manipulation.


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
ORD For The Sciences Hackathon
Explore the potential and impact of Open Research Data on the sciences!
Co-organized by the Swiss Data Science Center (SDSC) and EPFL Open Science and hosted on EPFL’s dynamic campus, this event brings together professionals from academia, industry, and the public sector to unlock the power of open research datasets and infrastructures.
By embracing open principles, fostering collaboration and driving change, we aim to create a vibrant ecosystem that accelerates innovation and benefits society. The ORD for the Sciences Hackathon is a unique opportunity to join forces with research communities in this shared mission. Together, we’ll harness ORD to shape the future of open research.
Why Participate?
Participants will have the chance to engage with a vibrant scientific community by sharing and enhancing their datasets. This is an opportunity to:
- Optimize and expand your datasets for more efficient use.
- Build models and analyses that reveal new insigtts in existing datasets.
- Improve the understanding and utilization of datasets.
Goals
- DEVELOP simple Proof of Concept (PoC) projects using open datasets.
- APPLY solutions to real-world challenges from academia, industry, and the public sector.
- SHARE code, knowledge, best practices, and ideas for use cases.
- CONNECT with data science and ORD professionals.
What to Expect
- Two days of intense hands-on development, exploring the potential of open research data and infrastructure within a collaborative team.
- A dynamic atmosphere in first-class facilities, where you can network, explore synergies, and engage in insightful discussions.
- Leverage cutting-edge datasets and tools to carry out projects following FAIR principles.
- The opportunity to work with the latest models and technologies, driving real innovation.
SDSC’s Renku platform will be presented and made available to enable participants to collaborate seamlessly and use GPU resources. Renku is an open-source knowledge infrastructure in the making, designed for collaborative and reproducible data science; use it during the hackathon to collaborate with your team and become part of the community to help grow and improve it!
The Opportunity Ahead
The ORD Hackathon will enable participants to capitalize on the resources available with a new mindset. Through concrete use cases, you will experience firsthand how ORD can impact and benefit the sciences.
20 teams will work on 15 projects across two tracks:
• Research Data Infrastructures (RDI): fostering new RDI prototypes
• Data Science: building tools, models, and knowledge
Previous Hackathon
Check out this video from our last hackathon, dedicated to Generative AI applications.
Details
Event Details
In-person event. Max 100 participants. Participation is free, registration mandatory.
Registration is closed.
Programme
AGENDA
DAY 1: Thursday, October 24th, 2024
08:00 - 09:00 Check-in & Badges
09:00 - 09:10 Introduction: Gilles Dubochet, Head of Open Science, EPFL, and Oksana Riba-Grognuz, Head of ORD Engagement and Services, SDSC
09:10 - 09:20 Swiss ORD Mandate: Angelika Kalt, Director of SNSF and President of ORD Strategy Council
09:20 - 10:00 Keynote: Why do Open Data matter? by Florin Hasler, Director of Opendata.ch
10:00 - 13:00 Group Session
13:00 - 14:00 Lunch
14:00 - 22:00 Group Session
18:00 - 20:00 Apéro
DAY 2: Friday, October 25th, 2024
09:00 - 12:00 Group Session
12:00 - 13:00 Lunch
13:00 - 15:00 Group Session + project submission
15:00 - 18:00 Presentations, Voting & Prizes
Food and drinks will be provided for the two days.
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Dr. 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. There, he used state-of-the-art techniques to extract information from data, especially to search for traces of dark matter in particle collisions. Since 2016, he has worked in 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 Mai 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.
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