WHO WE ARE
OUR MISSION
In 2017, a national Data Science initiative from the ETH Board resulted in the creation of a unique joint venture between EPFL and ETH Zurich: the Swiss Data Science Center. The Center’s mission is to accelerate the use of data science and machine learning techniques within academic disciplines of the ETH Domain, the Swiss academic community at large, and the industrial sector.
A team of senior data scientists and experts in domains such as personalized health & medicine, earth & environmental science, social sciences, digital humanities and economics collaborate on academic and industrial projects. This unique positioning, at the crossroad of academic excellence and a fast-paced business environment, is key to simplifying a complex data science journey.
TEAM
Albert’s background is in computational physics, combining materials science and high-performance computing. He studied Applied Physics in Munich and Nottingham. Albert received his Ph.D. at the Max-Planck Institute in Düsseldorf for developing classical models for the -in reality- quantum mechanical interactions of atoms and electrons. To apply his models to real-world materials, he continued his research at EPFL (Lausanne) performing simulations using feedforward neural network. Albert joined the SDSC in March 2022 as a Systems Engineer.
Alessandro received his PhD in High Energy Physics from the University of Torino in 2016. His PhD thesis aimed at demonstrating how general purpose GPU can be leveraged for massively parallel computations in the domain of particle physics. After the PhD Alessandro joined the private sector where he worked as system engineer and Dev/Ops advocate.
In December 2020 Alessandro joined the SDSC team as system engineer to further develop the infrastructure for Renku.
Alessandro holds an M.Sc. in Applied Mathematics from EPFL with a minor in Data Science. After his studies, he joined the SDSC as Data Scientist in April 2022, where he closely works with the academic community to enlarge and support the use of data science. Over the years he worked on a variety of topics, from extreme events modeling to time series representation. His main interest lies in the application of machine learning to the energy sector.
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.
Alexander joined the SDSC’s industry team in May 2022. His background is in nuclear physics and he holds a Ph.D. from the University of Connecticut. Before joining the SDSC, he worked as a Carnegie Mellon University postdoc on the GlueX experiment at the Thomas Jefferson National Laboratory in Virginia where he used data and statistical models to debug and calibrate detectors as well as measure the properties of the phi meson. After academia, he worked in the industry at a small start-up data consultancy, a large printing company, and a financial company where he used neural networks for detecting fraudulent credit card transactions.
An joined the Swiss Data Center in August 2017 as an Executive Assistant. An holds a Bachelor’s degree in English, French and History teaching. She worked in several HR roles (recruitment and development) for Manpower Belgium. After having moved to Switzerland in 2008, An has worked in a Private Wealth Management Division of a well-known American bank.
An relocated to Dubaï with her family for a period of 2 years.
Andrea joined the SDSC in 2021. She received her degree in Information Technology from The University of Valle in 2013. Since then she has worked in the IT and software industry and has specialized in the design and implementation of progressive web applications at scale with a focus on writing clean code, maintainability, and usability. She combines her passion for inclusion and technology by actively participating as a speaker and mentor in talks and Bootcamps of technology communities aimed at bridging the gender gap.
Anna joined SDSC as a Data Scientist focusing on industry collaborations in July 2019. She strives to demonstrate rigor and excellence in data analysis and interpretation, deliver actionable results, and therein to enhance industry products and services. 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 the Financial and Insurance sectors. More specifically, Anna developed a computer vision model for car damage recognition, a high-accuracy credit scoring model for mortgage loans and an insurance KPI dashboard with time-series analysis.
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.
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.
Chandrasekhar studied mathematics at the University of California, Berkeley (B.A. 1997) and art and computer science at the University of California, Santa Barbara (M.A. 2003). He has worked as a software developer and consultant for companies, research institutions, and NGOs in the US, Germany, and Switzerland. Since 2009, he has been at ETH Zürich supporting projects by developing software solutions for data management, analysis, and visualization. He has been with the Swiss Data Science Center since 2017.
Christian joined SDSC in 2019 to design data-driven solutions to support academic research projects. His research interests comprise inference of probabilistic models, with a focus on nonparametric models, and stochastic processes. He holds a PhD in Computational Neuroscience from the Technical University Berlin, Germany, a MSc from the Bernstein Center for Computational Neuroscience Berlin, and a BSc in Cognitive Science from the University of Osnabrück, Germany. During the course of his studies, he additionally conducted research at Khalifa University (UAE), Strathclyde University (UK), and the RIKEN Brain Science Institute and the Kyoto University in Japan. Before joining SDSC, he was an intern at Amazon CoreAI in Berlin.
Christian joined the SDSC in July 2021 as a data scientist in the industry cell. Before that he worked at the Media Technology Center at ETH Zurich to develop new ML technology for their industry partners. He completed his Master’s degree in Mathematics at ETH Zurich (2017) with focus on algorithmics and machine learning. After his studies he worked as a online marketing data analyst in the news publishing business. His expertise lies in statistics, NLP and software engineering.
Christine received her PhD in Applied Mathematics in 2003 (Paris Dauphine University). She joined the Swiss Data Science Center in 2019 from the Harvard T.H. Chan School of Public Health where she was a Senior Research Scientist and an instructor in the Master of Science in Health Data Science. Her research interests are statistical software, reproducible workflows, and environmental policy and health policy. Recent published works include the New England Journal of Medicine, the Journal of the American Medical Association, and the Annals of Applied Statistics.
Cindy is a seasoned Executive Assistant at Senior Management level with over 15 years in the field. She gained experience in demanding sectors such as Private Banking and Industry. Before joining EPFL in 2008, she had the opportunity to work for the CFO and his team of Directors at the European headquarters of a US-based multinational company. She also spent a couple of years as HR and Communications coordinator in the same enterprise.
She has been working at EPFL for almost 10 years, previously as the assistant of a Professor’s Laboratory doing research in polymer chemistry.
Since April 2018, she is one of the SDSC Executive Assistants.
Clément joined the SDSC as a Data Scientist focused on industry projects in January 2019. He obtained a BSc in Physics (2016) from EPFL in Switzerland and a MSc in Computational Science and Engineering (2018) also from EPFL. During his studies, he mainly worked on applying Data Science and Machine Learning tools to optimize industrial processes.
Corinne joined the SDSC as a senior data scientist in December 2020. She graduated with a PhD in Statistics from the University of Washington in 2020. Her doctoral research focused on representation learning for partitioning problems. Prior to her PhD, she obtained bachelor’s degrees in Math, Statistics, and Economics, along with a master’s degree in Economics, from Penn State University. Her research interests include deep learning and kernel-based methods, with applications in fields ranging from computer vision to oceanography.
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.
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.
Ekaterina received her PhD in Computer Science from Moscow Institute for Physics and Technology, Russia. Afterwards, she worked as a researcher at the Institute for Information Transmission Problems in Moscow and later as a postdoctoral researcher in the Stochastic Group at the Faculty of Mathematics at University Duisburg-Essen, Germany. She has experience with various applied projects on signal processing, predictive modelling, macroeconomic modelling and forecasting, and social network analysis. She joined the SDSC in November 2019. Her interests include machine learning, non-parametric statistical estimation, structural adaptive inference, and Bayesian modelling.
Elena joined the SDSC industry cell in December 2019. She graduated from MIPT (BSc, Moscow) and Ecole Polytechnique (MSc, Paris). Before joining SDSC she was working as a data scientist in the field of construction, manufacturing and gas & oil industries risks. Elena was developing ML modes identifying dependencies between “weak signals” such as observations, audits results, HR data and workspace incidents in order to prevent incidents in future and do workplace a safer place. She was a volunteer in an association organizing international students data science game and enjoys participating in data science challenges with friends.
Eliza has joined the academic team as a senior scientist. She previously worked as a postdoctoral researcher at the Massachusetts Institute of Technology (2012-2013), Empa (2013-2017) and the University of Innsbruck (2017-2020). Eliza received her PhD in Atmospheric Science from the Max Planck Institute for Chemistry in 2012, and her Bachelor degree with Honours in Antarctic Science from the University of Tasmania in 2008. Her previous research has centered around the use of novel isotopic measurements and modelling approaches in atmospheric and biogeosciences, in particular the nitrogen cycle. Her research at SDSC will focus on data analytics and machine learning approaches in environmental and natural sciences.
Eric received his PhD degree in Electrical Engineering from Columbia University, New York, in June 1999. Eric Bouillet has been working at IBM T.J. Watson Research Center, Hawthorne, NY since June 2004, and at the IBM Smarter City Technical Centre, Dublin from October 2010 to August 2016. While at IBM he has been working on scalable data stream analytics applied to a number of fields, including finances, law-enforcement, telecommunications, environmental monitoring, intelligent transport systems, and aircraft reliability control systems. Before joining IBM Research, Eric Bouillet was at Tellium, Oceanport, NJ where he was part of the research team who invented and designed the first commercial optical mesh restoration network (deployed nationwide and documented in their book Path Routing in Mesh Optical Networks), and at Lucent Technologies’ Mathematical Science Center in the department of Mathematics of Networks and System Research department where he worked on the design optimization and sizing of circuit and packet switched networks.
Federico holds a M.Sc. in Engineering and a Ph.D. in Sustainable Development and Innovation Engineering. After a three-year Postdoc in Environmental Data Mining at the University of Lausanne, in 2021 he joined the Swiss Data Science Centre, where he now works as Senior Data Scientist supporting the acceleration of the digital transformation within industries, NGOs and public bodies. Over the years he worked on the development of methodological tools to mine and model big spatiotemporal datasets. He has deep competencies in applied statistics, machine learning, geocomputation, spatial statistics, remote sensing.
Fernando received a PhD. in Electrical Engineering from the Technical University of Madrid. He has been a member of the technical staff at Bell Labs and a Machine Learning Research Scientist at Amazon. Fernando has been a visiting professor at Princeton University under a Marie Curie Fellowship and an associate professor at University Carlos III in Madrid. He held positions at the Gatsby Unit (London), Max Planck Institute for Biological Cybernetics (Tuebingen), and BioWulf Technologies (New York). Since 2022, Fernando is the Deputy Executive Director of the SDSC.
Firat completed his undergraduate studies in Electronics Engineering at Sabanci University. He later received his MSc. in Electrical and Electronics Engineering from EPFL. He conducted his doctoral studies on medical image segmentation in Computer Vision Lab at ETH Zurich. In between, he visited INRIA (Sophia Antipolis, France) and ABB Corporate Research Center (Baden, Switzerland). His research interests revolve around computer vision and machine learning, with a focus on the medical domain. He has been with SDSC since 2019.
Fotis has joined SDSC as Sr. Systems Engineer.
Before SDSC’s Engineering team, Fotis has been delivering HPC platforms and large scale services across several countries, with varying technical complexity.
Even with multiple projects, ranging from global ISPs TCP/IP delay measurements, several clusters for CERN’s Large Hadron Collider physics experiment, developing in EasyBuild while automating HPC software builds and contracted for professional documentation thereof, up to delivering in 2015 and running the system that has led globally for processing most human DNA for clinical use ever, 100K Genome Project, Fotis always found the time and enthusiam for training hundreds of scientists and systems administrators to fulfill their mission.
Finally, Fotis is an active promoter of Open Source Software and open standards and has been spearheading several impactful HPC/OSS hackathons.
Francois received his PhD in December 2018 from Stellenbosch University (SU) in South Africa where he focused on improving inference algorithms for probabilistic graphical models. Before joining the SDSC, Francois worked as a senior lecturer at the Department of Statistics and Actuarial Science at SU. His research interests include probabilistic graphical models, time series forecasting, causal inference and discovery, extreme value theory, and machine learning in general.
After earning a MSc in Theoretical Physics at University of Padua, Giulio graduated in Quantitative Finance from Bocconi University. Before joining the SDSC industry cell in June 2021, he spent a few years working in the financial sector, where he mainly dealt with the application of machine learning to financial risk management.
When not coding, Giulio spends his free time playing bass guitar, hiking and cooking.
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.
In 2018, Hervé joined a school called CPNV (Professional Center of Northern Vaud) to get a CFC Médiamaticien (“médiamatique” includes graphic design, photography, marketing, economic and computing skills). During his training, in 2020, he joined SDSC as an intern. He has now finished his training as a médiamaticien and has been recruited as a graphic designer.
Imen holds a Master of Management & Financial Analysis from Lorraine University in France and a Master of Accounting from Sfax University in Tunisia. Before joining the SDSC, Imen worked as a financial controller for two Software companies in France as well as for an Oil & Gas company in Monaco. She is responsible for the SDSC budget process, the financial reporting and the cost accounting, as well as the audit process.
Isinsu joined the SDSC in May 2022. She obtained a Bachelor’s degree in Computer Science from Middle East Technical University, Turkey, and later received a Master’s degree in Computer Science from EPFL. She conducted her doctoral studies in the Computer Vision Lab at EPFL with a focus on human body pose estimation and motion prediction using deep learning-based methods. Her research interests include self- and semi-supervised learning for image-based analysis of the human body and motion, with applications ranging from athletic training to healthcare.
Ivan-Daniel joined the SDSC Innovation team in September 2022, where he works as a Data Scientist. He obtained an MSc in Robotics (2022) from EPFL and holds a BSc in Microengineering (2019), also from EPFL. His main fields of interest are Machine Learning, Computer Vision, and animal locomotion modeling.
Jimena joined SDSC as Frontend designer in November 2022. She is an all-round creative graphic designer with in-depth knowledge of typography, branding, user interface & user experience.
Her job at Renku include close collaboration with the product manager, developers and engineers to gather requirements from users before designing ideas that can be communicated using storyboards, process flows, sitemaps, personas, sketches, wireframes, mockups, prototypes and user test.
She combines design, creativity and new technologies with focus on solving problems for the end-user and creating user-friendly interfaces according to GUIs.
Johan joined the SDSC industry cell in May 2019. 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 and computer vision, he loves challenges in document analysis and knowledge extraction.
Laura joined the SDSC in 2022 as a Senior Data Science Engineer in the ORD Engagement & Services team. She holds a Master’s Degree in Computer Science from Rensselaer Polytechnic Institute (USA). She has worked as a Data Scientist and Software Engineer in the healthcare IT field in both industry and academia. She is interested in open source tooling for data science, and how good software tools make data science more reproducible, collaborative, and user-friendly. When not coding, she can be found hiking, biking, and exploring the SBB train network.
Lili obtained the MSc in Statistics from ETH in 2018. She wrote her Master thesis at the Swiss Data Science Center applying topic modelling to political data. She rejoined the center in May 2020 after a year as a statistical consultant at the Seminar for Statistics at ETH. With her MSc in Chemical Engineering, she worked as a process engineer in the glass industry for several years. She is interested in interdisciplinary projects where data science can help uncover new insights.
Lorenzo Cavazzi graduated in Computer Systems Engineering at Polytechnic University of Milan in 2012 with a thesis on a new type of JavaScript MVC-like framework. He then joined Repower AG, at first as a system engineer helping to expand and maintain the new Microsoft based infrastructure, then as a software engineer in the trading department. His two biggest projects were a data management system to properly manage data acquisition, and the new web portal to provide services to corporate and external user in the energy industry through a set of web applications.
Lucas joined the SDSC’s industry cell as a Data Scientist in November 2020, having previously worked in data related roles at the New York State Attorney and at Ericsson.
He holds a BSc in Economics from Bocconi University, a MSc in Urban Science and Informatics from New York University as well as a MSc in Machine Learning from KTH Royal Institute of Technology.
Over the course of his academic and professional career he has worked on a variety of topics, from computer vision tasks for automated driving to financial fraud detection to generating data driven insights to inform urban policy decisions.
Luis Barba Flores joined the SDSC in 2022 as Senior Data Scientist. He received a joined PhD in Computers Science in 2016 from the Université Libre de Bruxelles and Carleton University. He served as a postdoctoral researcher at ETH Zurich from 2016 to 2019, and then moved to EPFL Lausanne to work in the Machine Learning and Optimization Group until 2022. His research interests include distributed optimization algorithms, first-order optimization methods and their applications to Deep Learning models.
Luis is originally from Spain, where he completed his bachelor studies on Electrical engineering, and my 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 equalisation. 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 data scientist, encompassing topics such as microscopy image analysis, neuroimaging, single cell gene expression analysis, etc. He joined the SDSC in April 2018.
Martin joined the SDSC in October 2019 to work on the Swiss Data Custodian project as a computer scientist. He obtained a BSc and a MSc in Communication Systems from EPFL. His great interest for Cyber security led him to specialize in Information Security and Privacy during his master. At the end of his studies, he did an internship where he coupled machine learning and security to develop a tool to automatically analyze log files and detect behavioural anomalies. After that, he came back to EPFL for his master thesis, where he investigated Website Fingerprinting, an attack aiming at breaking the privacy of Tor and other encrypted and anonymous networks.
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.
Michele received a Ph.D. in Environmental Sciences from the University of Lausanne (Switzerland) in 2013. He was then a visiting postdoc in the CALVIN group, Institute of Perception, Action and Behaviour of the School of Informatics at the University of Edinburgh, Scotland (2014-2016). He then joined the Multimodal Remote Sensing and the Geocomputation groups at the Geography department of the University of Zurich, Switzerland (2016-2017).
His main research activities were at the interface of computer vision, machine and deep learning for the extraction of information from aerial photos, satellite optical images and geospatial data in general.
Mohammad has received his Master’s Degree in Computer Science from University of Tehran, Iran in 2005. He has been working as a researcher and software developer in academia and industry in Iran and Switzerland. He has multidisciplinary experience in computer systems design on a variety of platforms ranging from embedded systems to commercial servers. He is passionate about software design, programming languages, and agile software development.
Mylène likes to make the connection between people and projects. After her studies in Tourism Development & Management, she worked for several destinations and sites, developing the touristic and cultural offer. Then, she worked in the luxury hospitality field, planning and coordinating customized retreats for a high hand international clientele. Always keen to discover new fields, she joined the HEC Lausanne center for continuing education as program coordinator, always looking for the best way to make both students and professors live a perfect experience. Mylène has now joined the SDSC as Event and Industry Relations Coordinator.
After finishing his Master in electrical engineering at the Ecole Fédérale de Lausanne (EPFL), Nathanaël worked as a researcher in the Acoustic Research Institute (ARI) in Vienna. In 2013, he returned to EPFL for a PhD, where he specialized himself in different fields of data science: signal processing, machine learning, graph theory and optimization. Furthermore, he created two open source libraries for optimization (UNLocBoX) and graph signal processing (GSPBOX). Since 2017, Nathanaël Perraudin is a Research Data Scientist at the Swiss Data Science Center in the ETH Zurich. He focuses on different aspects of deep learning in the area of generative models (VAE and GAN), recursive architectures and convolutional neural network for irregular domains. Outside office hours, he is passionate by tango dancing, tandem bike touring, skiing and rock climbing.
- Personal website: https://perraudin.info/
- Google Scholar: https://scholar.google.com/citations?user=Rlz7I8gAAAAJ
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.
Olivier Verscheure holds a PhD in computer science from the EPFL (1999).
He was Lab Program Director and Senior Research Manager at IBM Research Ireland from 2010 to 2016, and prior to this Research Manager and Senior Member of the Research Staff at the IBM T.J. Watson Research Center (1999 – 2010). He took over the Executive Director position of the SDSC in 2016.
He is also an expert in the Strategy Working Group on Data, Computing and Digital Research Infrastructures in the State Secretariat for Education, Research and Innovation (SERI) since 2019, member of the Executive Committee of Personalized Health and Related Technologies (PHRT), an ETH Domain Strategic Focus Area (since 2017) and co-academic Director, Certificate of Advanced Studies (CAS), Data Science and Management, HEC Lausanne and EPFL (since 2018).
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.
https://quentin-duchemin.alwaysdata.net/
Ralf graduated from the FHNW in Brugg, Switzerland with a BA in Computer Science. He previously worked for over 20 years in the IT industry as a software engineer, working on diverse topics such as NLP, computer vision, distributed machine learning, traffic data analysis, infrastructure maintenance and web development, as well as having worked as CTO for a startup focusing on NLP technologies. His research interests are in NLP with a focus on Sentiment Analysis and working with Swiss German. As part of this he has helped organize the Swiss Text conference two years in a row. Since August 2018 he has been at Swiss Data Science Center working on Renku, the SDSC’s platform for data science reproducibility and collaboration.
Raphaël worked for 6 years as an engineer in biomedical research labs. Performing a lot of image analysis for microscopy experiments, its curiosity led him to learn about Data Science. Therefore, he joined a consulting company and worked on several projects, notably one within Air France Company, on a predictive maintenance project and a shorter one on an NLP PoC. Since the beginning of 2021, Raphaël is working in the SDSC industry team.
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.
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
Sabrina joined the SDSC in September 2019 as a computer scientist. Her mission is about developing and deploying privacy-preserving solutions. She received her PhD in Information Systems from the University of Geneva with a focus on designing fair and responsible data sharing ecosystems. Her interests include ethical data processing, cloud computing, service design, privacy-preserving systems.
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.
Sean obtained his PhD in Telecommunications Engineering from Dublin City University in 2001. Since then he has worked in large industry and startup contexts but has spent most of his time working in academic research labs with a strong applied focus spanning both Ireland and Switzerland. Sean has experience with all aspects of the research project lifecycle, ranging from project inception to proposal stage to project execution and reporting. Having a keen interest in technology trends and evolution, he strives to maintain a hands on approach with practical experience with key technologies in the rapidly changing cloud and analytics technology landscape.
Sean works on the Renku Infrastrucuture team, leveraging his experience with modern cloud technologies, helping to make Renku easy to deploy and manage.
Shirin Goshtasbpour completed her M.Sc. in Communication Systems at Sharif University of Technology in Tehran. Currently, she is a Ph.D. student at ETH Zurich and she is working as an early stage researcher on the Windmill project, a European Union’s Horizon2020 programme focusing on Integrating Wireless Communication Engineering and Machine Learning. Her main interests are deep generative models and their evaluation and generalization.
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.
Simon joined the SDSC as a senior data scientist in April 2022. He conducted his doctoral studies on statistical modeling of genetic data at ETH Zürich and obtained his MSc and BSc degrees at Technical University Munich in computer science. Before joining the SDSC, Simon worked as a freelance statistical consultant, and as an ML scientist at an AI startup in Lugano where he built experience in various topics ranging from generative modeling over Bayesian optimization to time series forecasting. Simon’s research interests and expertise lie broadly in probabilistic machine and deep learning, causal inference, generative modeling, and their application in the natural sciences. Simon is an avid open-source software contributor and particularly enthusiastic about probabilistic programming languages, such as Stan.
See Simon’s private page and GitHub
Snežana joined the SDSC industry team in June 2021 on a mission to advance adoption of modern data driven solutions in the domain of public health care. She has a background in experimental particle physics with a Diploma from the ETH Zurich and a PhD from the University of Geneva. Snežana pursued fundamental research in the field of high energy physics at CERN for nine years, harnessing the power of machine learning and statistical methods to uncover the traces of new physics in petabytes of proton-proton collision data and to develop innovative particle identification algorithms. Since 2018, Snežana served as a Data Science consultant, supporting partners from industries such as manufacturing, insurances, compliance services and online platforms in creating business value from internal and external data.
Sofiane is the Program Manager at the Swiss Data Science Center. He is also a senior member of the research staff. Sofiane received his Ph.D. degree in computer science from the Swiss Federal Institute of Technology, Lausanne (EPFL), in May 2006
He has previously occupied positions at the border between management and science and led many projects applied to domains as varied as medicine, finance, environmental sciences, and scientific computing. His expertise and research interests include: stream processing, large scale data management, scientific and data visualization, and cloud computing.
Stephan is a marketing and communications all-rounder with over 20 years of experience in the luxury consumer industry across a range of global markets including Berlin, London, Singapore, Bangkok, Zurich, and Osaka.
Stephan graduated in 2018 with an Executive Masters in Corporate and Marketing Communication from IE School of Human Sciences and Technology in Madrid. He holds a Certification in Marketing Strategy from Cornell University and a Bachelor in Hospitality Management from the Alexandre Dumas Hotel & Tourism Management School in Strasbourg, France.
Fluent in French, German and English, Stephan is passionate about accelerating the adoption and use of new technologies, communication strategies, partnerships and collaborations, driving the links between brands and the public, and the people who create them.
Since 2022, Stephan is the Head of Communications at the Swiss Data Science Center.
Steven Stalder joined the SDSC in 2022 as a Data Scientist in the academia team. He received both his BSc and MSc in computer science from ETH Zürich, with a main focus on machine learning and high-performance computing. His first contact with the SDSC was during his master’s thesis, where he worked on explainable neural network models for image classification. Outside of work, Steven loves playing football, reading an interesting book, or watching a good movie.
Tasko got his Bachelor degree in Chemical Engineering at the University of Toronto. He worked at an oil refinery in Canada and then joined Ramboll in California as an environmental consultant with a focus on air quality modeling. During his five-year tenure at Ramboll Tasko worked on a variety of projects applying physical and statistical models to study ambient air quality. His latest work at Ramboll was the development of a cloud-based real-time air quality modeling platform called Shair, where Tasko was involved in modeling emissions, deploying models to the cloud, and web and cloud infrastructure design and implementation. At SDSC Tasko splits his time between software development for the Renku platform and academic projects such as data-driven snow avalanche forecasting.
Tomasz has obtained a MSc in Machine Learning from University College London, and then a PhD in Physics and Astronomy from the same university. Then he moved to ETH Zurich Cosmology group, where he worked on data science problems in measurement of cosmological parameters using large telescope surveys. He was a PI of “Deep Learning for Observational Cosmology”, an SDSC project in the first call for proposals. He worked extensively on introducing deep learning and generative machine learning methods in cosmology.
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.
Victor has joined the SDSC in 2020 to design solutions for data-driven optimization problems. His research interests lie at the crossroad of machine learning and decision-making. This contains several topics such as stochastic optimization, reinforcement learning, combinatorial optimization, and probabilistic graphical models. Victor received a PhD in operations research and machine learning from Ecole des Ponts Paristech in 2020. Before that, he completed a master degree in Operation Research and Machine learning at Ecole des Ponts Paristech and a bachelor degree in Applied Mathematics and Computer Sciences.
Wesley joined the SDSC in 2022 as a Systems/Software Engineer in the Renku team. He specialises in deploying infrastructure-as-code in cloud environments, enabling developer productivity with CI/CD pipelines, and building custom monitoring solutions. His professional interests include containerisation, programming, and automation. He is currently obtaining his BSc in Computing and IT part-time from the Open University.
William obtained a PhD in Statistics in 2015 jointly from the University of Geneva and the University of Sydney. He then worked as a post-doctoral research fellow at Dalhousie University as part of a Canadian Statistical Sciences Institute collaborative research team. He was an Assistant Professor of Statistics at Stevens Institute of Technology in Hoboken, New Jersey, before joining the SDSC in September 2020. His research interests include robust statistics, non-parametric methods, and spatio-temporal modeling. His recent cross-disciplinary collaborations involve applications in marine biology, volcanology, and fisheries science.
Xiaoran Chen joined SDSC as a senior data scientist in July 2022. Prior to this, she received her PhD at ETH Zurich in 2021. Her research was focused on unsupervised learning and anomaly detection on magnetic resonance imaging (MRI) scans. She also holds a master’s degree in bioinformatics and bachelor’s degree in biological science. Her research interest includes self-supervised learning, representation learning and general applications using machine learning methods.
Yousra studied Mathematics and Computational Statistics. She did a PhD in Statistical Learning followed by a post-doc both at EPFL, where she developed empirical Bayes methods for automatic L2 regularization problems in smooth regression for big data. Before joining SDSC, she worked at SIB/UNIL, where she developed a statistical optimization solution to the parent-of-origin identification problem in human genetics. Her technical expertise includes supervised learning, numerical optimization for machine learning, statistical modeling and methodology, high-performance and distributed computing for big data, Bayesian computation and time series analysis. She worked on applied problems in quantitative finance and environmental sciences.