Personalized Health Technologies 2024
Nora earned her Ph.D. in Computer Science/Bioinformatics from the University of Tübingen, where she focused on the in silico design of peptide-based vaccines using combinatorial optimization and machine learning. During her postdoctoral fellowship at Memorial Sloan Kettering Cancer Center in New York, and later as a staff scientist at the New York Genome Center, she worked on metagenomics, infectious diseases, and cancer. In 2015, Nora joined NEXUS Personalized Health Technologies at ETH Zurich where her focus shifted towards the management of clinical and biomedical research data. In May 2024, she joined the Swiss Data Science Center as Head of Biomedical Data Science.
Cyril joined the SDSC in 2022. He holds a Ph.D. in computational biology from Sorbonne University and the Institut Pasteur in Paris. There, he developed tools to detect changes in the 3D conformation of chromosomes and analyzed how it is altered during infection by bacterial pathogens. Before that, he received an MSc. in Bioinformatics from the University of Lausanne, where he worked on evolutionary genomics in insects. Over time, Cyril developed a strong interest in open and transparent scientific research. He is eager to promote good software and data management practice in research.
Stefan has a background in Biology and decided to move towards evolutionary bioinformatics for both his MSc and PhD.Over the years, he developed a passion for the entire data analysis process: from collecting data, to analyzing and presenting results. Presentations, particularly opportunities for public speaking, are activities he enjoys since he values communication a lot. In order to follow this passion and deepen his knowledge on systems to collect and manage data, he joined SDSC in 2023 as a Biomedical Data Engineer.Outside work, Stefan is an avid reader of sci-fi books (but not only!), enjoys swimming, running, and biking both competitively and casually and enjoys plenty of activities with friends, especially when beer is involved.
Daniel worked as a postdoctoral researcher on critical event prediction for the University Hospital in Zurich. In addition, Daniel has worked as a postdoctoral researcher in Lausanne, delivering algorithms for Bayesian inference in big panel data. Previously in Paris, he developed models for automated scientific discovery. He obtained a Ph.D. from the University of Edinburgh, funded by a Microsoft Research scholarship. His interest relates primarily to attacking applied biomedicine problems from different angles, frequentist statistics, Bayesian statistics, and Machine Learning.
Quentin graduated with an engineering degree in mathematics and computer science from École des Ponts ParisTech in 2019. After a 6-month experience at the Center for Data Science of the New York University working on applied Machine Learning for medical imaging, he did a PhD in Statistics at Gustave Eiffel University (Paris). During his PhD, Quentin worked on random graphs and selective inference. His recent cross-disciplinary collaborations involve applications in biology and hydrology.
Rok obtained a B.A. in Physics from Washington University in St. Louis in 2003. After obtaining his PhD in theoretical Astrophysics from the University of Washington in 2010, Rok spent several years as a Postdoctoral researcher at the Institute for Computational Science, University of Zürich. Seeking new challenges, he moved to the ETH Scientific IT Services group, where he helped researchers across different ETH domains solve their (big) data analysis problems. He specialized in optimizing and scaling up data analysis tasks by mapping them to high-performance computing resources. Since July 2017 he has been at the Swiss Data Science Center developing Renku, the Center's data science platform.
Benjamín Béjar received a PhD in Electrical Engineering from Universidad Politécnica de Madrid in 2012. He served as a postdoctoral fellow at École Polytechnique Fédérale de Lausanne until 2017, and then he moved to Johns Hopkins University where he held a Research Faculty position until Dec. 2019. His research interests lie at the intersection of signal processing and machine learning methods, and he has worked on topics such as sparse signal recovery, time-series analysis, and computer vision methods with special emphasis on biomedical applications. Since 2021, Benjamin leads the SDSC office at the Paul Scherrer Institute in Villigen.
Lin Zhang joined the SDSC as a senior data scientist. She completed her PhD at ETH Zurich in 2023, with a focus on simulation in medical imaging with deep learning. Before that, she obtained a bachelor degree in electrical engineering from the Technical University Munich, and a master degree in biomedical engineering from ETH Zurich. Her research interests include deep generative models, domain adaptation and applications of machine learning in healthcare.
Presentation
The 4th edition of the Personalized Health Technologies conference, organized by Nexus Personalized Health Technologies of ETH Zurich, will welcome more than 200 experts from various disciplines mainly from Switzerland and neighboring European countries. During the 2-day-event researchers, clinicians, and scientists from academia, industry and the public sector will explore present and future directions in the field of personalized health technologies, translational research, and development.
Details
Programme
Meet the Swiss Data Science Center!
SDSC colleagues and topics will be present as follows duringthe conference program:
Monday, 26th August, 2024 | TIME: 09:00 – 17:30 (fullday workshop at HG E 33.5)
WORKSHOP: Empowering FAIR data and reproducible research across the ETH Domain
Presenters: Franziska Singer and David Meyer, ETH Zurich with Rok Roškar from SDSC
Tuesday, 27th August - Wednesday, 28th August, 2024 |TIME: 9:00 – 18:00 (ETH Main Hall, during exhibition times)
EXHIBITION STAND Nr. 4
Contact: Nora Toussaint, Head of Biomedical Data Science at SDSC
Tuesday, 27th August, 2024 | TIME: 16:15 – 18:00 (HG F30)
POSTER SESSION
- Poster title: "Multi-Omics Digital Objects (MODO): One object to map them all"
Presenter: Cyril Matthey-Doret, Sr. Data Science Engineer Open-Research at SDSC
- Poster title: “AI meets Bedside: Development of a Clinical Decision Support System for Prevention of Hospital-acquired Pressure Injuries”
Presenters: Paloma Cito, Jr. Full-Stack Engineer at Clinical Data Science Group of CHUV; StefanMilosavljevic, Biomedical Data Engineer Open-Research at SDSC
- Poster title: “Integrating Single-Cell DNA-seq and RNA-seq for DrugResponse Prediction in Cancer”
Presenters: Daniel Trejo Banos, Sr. Data Scientist Academia and Quentin Duchemin, Sr. Data Scientist Academia at SDSC
Wednesday, 28th August, 2024 | TIME: 11:15 – 11:45 (ETHZ Audimax HG F 30)
PRESENTATION: One Scan - All Answers. Dual Positron Lifetime Emission Tomography for personalized treatments in oncology.
Presenter: Lars Gerchow, ETH Zurich, co-authors include Benjamin Bejar Haro and Lin Zhang from SDSC
Other events
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Johan Berdat joined the SDSC in May 2019 as a Senior Machine Learning Engineer in the Innovation team, based in Lausanne.
After completing his M.Sc. in Computer Science at EPFL, he worked for a few years as a consultant in the industry. Specialized in natural language processing (NLP) and computer vision, he loves challenges in document analysis and knowledge extraction.
Clément Lefeebvre joined the SDSC in January 2019 as a Data Scientist with an emphasis on industry-oriented projects in the Innovation team, based in Lausanne.
He holds a Bachelor of Science degree in Physics, acquired in 2016 from the École Polytechnique Fédérale de Lausanne (EPFL) in Switzerland. Following this, he earned a Master of Science in Computational Science and Engineering in 2018, also from EPFL. Throughout his academic journey, Clément concentrated on leveraging Data Science and Machine Learning techniques to enhance efficiency in industrial processes. Subsequently, he developed a specialized interest in Generative AI, with a particular focus on Natural Language Processing (NLP), especially in the application of Large Language Models for innovation.
Klemen Voncina joined the SDSC in April 2026 as a Machine Learning Engineer in the Innovation team, based in Lausanne.
Klemen holds an MSc in Artificial Intelligence from the University of Groningen. Prior to this, Klemen worked for several years in both consulting roles and startups. He brings a strong engineering-focused perspective, combined with a solid background in machine learning. He particularly enjoys tackling practical challenges, especially those related to infrastructure and application deployment. Outside of work, Klemen enjoys a range of outdoor activities such as climbing and mountaineering, as well as more home-based hobbies like board games, reading, and tea.
Kyle (Hogir) van de Langemheen joined the SDSC in September 2025 as a Machine Learning Engineer in the Innovation team, based in Lausanne.
Kyle holds an MSc in Artificial Intelligence from the University of Groningen. He brings several years of experience applying AI across research and industry.
Outside of his professional interests, Kyle enjoys hiking, reading, cooking, and coffee.
Thibaut holds a B.Sc in Computer Science from HEIG-VD. Before joining the SDSC, he worked in startups where he developped a diverse skill set combining cloud infrastructure, database and application development. Thibaut is very enthusiatic about new technologies and best coding practices and he is looking forward to supporting the team and its projects.
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Johan Berdat joined the SDSC in May 2019 as a Senior Machine Learning Engineer in the Innovation team, based in Lausanne.
After completing his M.Sc. in Computer Science at EPFL, he worked for a few years as a consultant in the industry. Specialized in natural language processing (NLP) and computer vision, he loves challenges in document analysis and knowledge extraction.
Clément Lefeebvre joined the SDSC in January 2019 as a Data Scientist with an emphasis on industry-oriented projects in the Innovation team, based in Lausanne.
He holds a Bachelor of Science degree in Physics, acquired in 2016 from the École Polytechnique Fédérale de Lausanne (EPFL) in Switzerland. Following this, he earned a Master of Science in Computational Science and Engineering in 2018, also from EPFL. Throughout his academic journey, Clément concentrated on leveraging Data Science and Machine Learning techniques to enhance efficiency in industrial processes. Subsequently, he developed a specialized interest in Generative AI, with a particular focus on Natural Language Processing (NLP), especially in the application of Large Language Models for innovation.
Klemen Voncina joined the SDSC in April 2026 as a Machine Learning Engineer in the Innovation team, based in Lausanne.
Klemen holds an MSc in Artificial Intelligence from the University of Groningen. Prior to this, Klemen worked for several years in both consulting roles and startups. He brings a strong engineering-focused perspective, combined with a solid background in machine learning. He particularly enjoys tackling practical challenges, especially those related to infrastructure and application deployment. Outside of work, Klemen enjoys a range of outdoor activities such as climbing and mountaineering, as well as more home-based hobbies like board games, reading, and tea.
Kyle (Hogir) van de Langemheen joined the SDSC in September 2025 as a Machine Learning Engineer in the Innovation team, based in Lausanne.
Kyle holds an MSc in Artificial Intelligence from the University of Groningen. He brings several years of experience applying AI across research and industry.
Outside of his professional interests, Kyle enjoys hiking, reading, cooking, and coffee.
Thibaut holds a B.Sc in Computer Science from HEIG-VD. Before joining the SDSC, he worked in startups where he developped a diverse skill set combining cloud infrastructure, database and application development. Thibaut is very enthusiatic about new technologies and best coding practices and he is looking forward to supporting the team and its projects.
AI for Decision Makers - Executive Course at EPFL
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.
Alessandro joined the SDSC in March 2019 as a data scientist focused on industry collaborations. His mission is to support corporates in leveraging the power of their data by adopting analytical approaches and data-centric solutions. His background is in biomedical engineering, with a PhD in neuroscience from the University of Tübingen. Before joining the center, he worked as a postdoc at the Max Planck Institute for Biological Cybernetics, at the EPFL Laboratory of Cognitive Neuroscience in Geneva, and as data scientist for a private ecommerce company.
Clément Lefeebvre joined the SDSC in January 2019 as a Data Scientist with an emphasis on industry-oriented projects in the Innovation team, based in Lausanne.
He holds a Bachelor of Science degree in Physics, acquired in 2016 from the École Polytechnique Fédérale de Lausanne (EPFL) in Switzerland. Following this, he earned a Master of Science in Computational Science and Engineering in 2018, also from EPFL. Throughout his academic journey, Clément concentrated on leveraging Data Science and Machine Learning techniques to enhance efficiency in industrial processes. Subsequently, he developed a specialized interest in Generative AI, with a particular focus on Natural Language Processing (NLP), especially in the application of Large Language Models for innovation.
Thibaut holds a B.Sc in Computer Science from HEIG-VD. Before joining the SDSC, he worked in startups where he developped a diverse skill set combining cloud infrastructure, database and application development. Thibaut is very enthusiatic about new technologies and best coding practices and he is looking forward to supporting the team and its projects.
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Saurabh Bhargava, joined the SDSC as a Principal Data Scientist in the Industry Cell at the Zürich office in 2022. Saurabh previously worked in the retail sector and the advertising industry in Germany. He lead and built various data products for customers using state of the art machine learning methods and industrializing them thereby adding value for the customers. He completed his PhD from ETH Zürich in June 2017 specializing in machine learning applications on Audio data. He obtained his Master’s and Bachelor’s degrees from EPFL and Indian Institute of Technology (IIT), Roorkee, India in 2011 and 2009 respectively. His interests and expertise are in combining state of the art data science and data engineering tools for building scalable data products.
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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.
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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.
Paulina Körner joined the SDSC in September 2025 as a Data Scientist in the Innovation team in Zurich.
Paulina holds an MSc in Environmental Science from ETH Zürich and completed an MPhil in Machine Learning and Machine Intelligence at the University of Cambridge. She has worked as a data science intern in Alpine Remote Sensing and as a research assistant at ETH Zürich, where she focused on automating chemical risk evaluations. She also gained consulting experience at South Pole, supporting clients in designing decarbonization roadmaps. Paulina is particularly interested in interpretable machine learning and in applying AI to address real-world challenges in environmental science, industry, and the public sector.
Oliver Poole joined the SDSC in December 2025 as Data Scientist for the Innovation team, based in Zurich.
Prior, Oliver completed his bachelor's and master's degrees in mechanical engineering from ETH Zurich, with research on custom 3D-printed metallic springs for (non-)linear stiffness customization and reinforcement learning applications in control systems. He developed anomaly detection systems for X-ray images of mechanical parts, milk foam quality assessment using computer vision and sensor data, and data-driven flow control strategies and extraction consistency for coffee machines. His work bridges physical engineering intuition with machine learning, focusing on robust models that connect sensor data directly to measurable outcomes in industrial systems.
Marisol has a degree in Law and more than 15 years of experience working as a notary officer in Madrid. After relocating to Switzerland with her family, she obtained a certification to teach Spanish as a foreign language, dedicating four years to teaching Spanish online to students of all ages and backgrounds. Marisol has returned to her professional roots as an administrative assistant, joining the SDSC team in June 2023.
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