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
AMLD 2024 | Clinical AI: from Research and Development to the Bed Side
SDSC-Connect | AI for Precision Medicine
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.
ENID | Enabling Innovation with Data Science at UNIL-EPFL
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.
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.
Olivier joined the SDSC as a data scientist focused on industry collaborations in February 2023. He obtained a MSc in Physics (2017) from EPFL with a minor in Mathematics, and a PhD in Astrophysics (2021) from Aix-Marseille University. Before joining the SDSC, he worked in a small start-up, as a data scientist, on a variety of topics, including data wrangling, natural language processing and time series forecasting.
Clément became part of the SDSC team in January 2019, assuming the role of a Data Scientist with an emphasis on industry-oriented projects. 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.
SDSC-Connect 2023
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.
Roberto holds an M.Sc. and a Ph.D. in Particle Physics from the University of Torino, Italy. He has worked for several years in fundamental research as a senior fellow and data scientist at the CERN Experimental Physics division and on a research project supported by the Belgian National Fund for Scientific Research (FNRS). In 2018 he moved to EPFL to work on data mining and Machine Learning techniques for the built environment and renewable energies. He has started and led multiple collaborations with academic and industry partners in the energy domain. Roberto joined the SDSC in September 2021 as a Principal Data Scientist with the mission of accompanying industries, NGOs and international organizations through their data science journey.
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