WHO WE ARE
A 2017 ETH Board national Data Science initiative 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 multi-disciplinary team of senior data scientists and experts in domains such as personalized health and medicine, earth and environmental science, social science and digital humanities, as well as economics enables collaboration on both academic and industrial projects. This unique positioning, at the crossroad of academic excellence and fast-paced business environments agility is key in making the complex data science journey simple.
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 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.
After obtaining a joint MSc in Micro and Nanotechnologies from EPFL, Grenoble INP and PoliTo, Amalia worked for several years in the microelectronics industry, combining data science and domain expertise. As a data scientist, she worked on projects such as anomaly detection for quality improvement and machine learning based test optimization, while in her previous work as an application engineer she often employed statistics and data analysis in order to address customers’ challenges. During that time she discovered her passion for data and for working with customers, co-authored two patents and completed a COS in Data Science – Machine Learning from EPFL.
Amalia joined the SDSC’s industry collaborations cell in October 2019
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.
Anna joined the SDSC as a Senior Data Scientist in 2020. She is a statistician by training with a Master’s degree with Honors in Mathematical Statistics from Lomonosov Moscow State University. Anna has graduated with a PhD from ETH Zurich in 2018, where she worked on causal structure learning for protein signaling pathways. During her studies she did an internship at Facebook AI Research in New York working on discovery of hierarchies from data using hyperbolic geometry. Later she joined Facebook AI Research in Paris as a postdoctoral researcher, where she worked on a problem of out-of-distribution prediction of unseen drug combinations. Broadly her research interests are in unsupervised and self-supervised learning, domain adaptation and generalisation.
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.
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.
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.
David joined the SDSC in June 2020 to work with the Knowledge Graph team. He has exeperience in building full-stack web applications and loves using functional programming to do so.
He developed an interest in Knowledge graphs while working for the Human Brain Project, where he took part in the creation of a platform helping with the data curation process.
When he is not coding, David spends his free time producing and recording film music and playing drums.
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.
Eniko joined SDSC as a senior data scientist in September 2017. Previously, she was a postdoctoral researcher at the Courant Institute of Mathematical Sciences, New York University, working on machine learning for dynamical systems and climate science. She obtained her PhD in Computer Science from the University of Geneva, Switzerland (2011), her MSc from Telecom Bretagne, France (2006) and her BSc from the University of Timisoara, Romania (2005). Broadly she is interested in machine learning for nonlinear phenomena and high-dimensional data, and more recently she has been working on using machine learning approaches to advance our understanding of the climate.
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.
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. He has been a visiting professor at Princeton University under a Marie Curie Fellowship and an associate professor at University Carlos III in Madrid. He has also held positions at the Gatsby Unit (London), Max Planck Institute for Biological Cybernetics (Tuebingen), BioWulf Technologies (New York).
Firat completed his undergraduate studies on 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.
Floriane is a Lausanne University graduate. Given her venerable age, digitalization was not a buzz word when she was a student, and she therefore completed a Certificate in Digital Strategy and Communications Management at the University of Toronto in 2015. After moving back to Switzerland, she joined EPFL in 2016 as head of communication for a central service. Prior to this, she held global marketing communications roles at major industrial corporations for close to 15 years. Since April 2017 she is officially a Swiss Data Science Center employee.
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.
Gavin joined the SDSC in Zurich as a Data Science Engineer in 2020. He holds an MSc in Computational Science and Engineering from EPFL, where he completed his Master’s thesis in an SDSC collaboration with the Harvard T.H. Chan School of Public Health on a biostatistics research project. Prior to coming to Switzerland, he completed a BSc in Financial Mathematics and Statistics at the University of Sydney and subsequently worked in various financial institutions. Currently, he is interested in statistical software and data visualisation.
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). At the end of his training, He will get a CFC Mediamaticien (“médiamatique” includes design, photography, marketing and computing skills). For now, he has joined the SDSC as a Graphic Designer Intern for a year.
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.
Izabela holds a PhD degree in Computer Science from University of Rennes 1, France and the National French Institute for Research in Computer Science and Automatics (INRIA), France. Before joining the SDSC, she was a postdoctoral researcher at the Chair of Computational Social Science at ETH Zurich and a lecturer for the “Data Science in Techno-Socio-Economic Systems” course at ETH Zurich. Her main research focus is on big data analytics, tools and platforms, machine learning and data mining, large scale network analysis, in the particular setting of social data mining.
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.
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.
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 Ubran 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 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.
Marcel Blattner joined the industry cell in 2020 as a Principal Data scientist at the Zürich office. After his Ph. D. in physics and a research stay at the Brookhaven National Laboratory, he worked in various industries. His passion is to translate abstract concepts into business-relevant solutions and help the industry benefit from the latest data science developments. Before joining the Swiss Data Science Center he was Chief Data Scientist at TX Group where he led projects in Computer Vision, NLP, and Optimization. To keep up-to-date with the latest research findings, he engages in research of interpretability and artificial neural network transparency.
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.
Maysam is a PhD student in the institute for machine learning at ETHZ since January 2018 and privileged to be under supervision of Dr. Fernando Perez-Cruz and Dr. Andreas Krause at SDSC. He is interested in working on advances in generative machine learning and their applications. Previously Maysam received his MSc in computer science from University of Toledo, Ohio, USA. During his master, as a research assistant, he worked on applying Machine Learning algorithms on physiological data and social network. Also, he received his BSc in computer engineering from Shiraz University, Shiraz, Iran. Maysam enjoys hiking and reading books.
Michele received the 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.
Natalie joined the SDSC in April 2019 as a data scientist in the industry cell. She completed her Bachelor’s degree in Operations Research at Princeton University with a focus on statistics, probability and optimization, and became interested in using these tools for biological applications. She continued her Master’s studies in Computational Biology and Bioinformatics at the ETH in Zurich, focusing on machine learning and statistical modeling in biomedical settings. After her thesis, she did an internship with the machine learning and data analytics group at Disney Research in Zurich, working on solving problems in various domains using deep learning.
Natasa is a computer scientist by training, with a Bachelor degree in Computer Science and Engineering and Master degree in Embedded Systems from Ss. Cyril and Methodius University in Skopje, North Macedonia. She finished her doctoral studies in Information Systems at UNIL- HEC Lausanne, under the supervision of Valérie Chavez-Demoilun. During her studies she did an internship at NATO and Facebook AI Research. Her research interest focuses on causal inference, generative models, uncertainty and interpretability.
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.
Nina has joined the SDSC in 2019 as administrative organizer. Her strengths lie clearly in communicating, structuring and organising. With more than 20 years of experience in sales, marketing and project management, she has specialized as a flexible generalist. After completing her commercial apprenticeship decades ago she has soon found interest in building up back offices in the field of start-up and small business. She is very excited to becontinuing this journey with the SDSC at the interface of the academic community and the industrial sector.
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 joined SDSC in 2021 as a data scientist in the industry team.
His expertise lie at the intersection of big data, software engineering and machine learning, with a strong interest for applications in domains like energy, telecoms, manufacturing.
Quentin graduated EPFL in 2020 with a M.Sc. in computer science and a specialisation in data analytics. He carried out his master thesis on algorithms for pattern recognition in event streams, and also contributed in smart grid projects during his studies.
On his free time, Quentin is a keen volleyball player, snowboarder, and occasional cross country biker.
Radhakrishna has a PhD in Computer Science from EPFL Switzerland, an MSc in Computer Science from NUS Singapore, and a BEng degree in Electrical Engineering from JEC India. During his 16 years of working experience, he has worked in the industry and academia, and has founded three start-ups. He has published over 20 refereed papers, which have received over 9000 citations. He is a co-inventor in 4 patents. He has served as a reviewer for several conferences and journals of repute and as area chair for ECCV 2016. His main interests are Computer Vision, Image Processing, and Machine Learning.
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 graduated in 2014 with an engineering degree from l’Ecole des Mines de Paris and holds since 2018 a Ph.D. in Statistics from l’Ecole Polytechnique Fédérale de Lausanne. Before joining the Swiss Data Science Center as senior data scientist, Raphaël was post-doctoral researcher at the Institute of Mathematics at EPFL working on quantitative risk modelling for natural hazards using extreme value theory. His research interests lie at the boundary of statistics and environmental sciences with a special focus on the analysis of spatio-temporal data.
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.
Sandro is a Data Science passionate. He has 10 years of experience applying Data Science in industries such as Finance, Telco, Chemicals, Online Travel and Retail. He is currently Chief Industry Advisor at the Swiss Data Science Center. Sandro holds a PhD in Computer Science from EPFL and founded the Swiss Association for Analytics to promote Data Science in Switzerland.
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.
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 M.Sc. in Computer Science from EPFL and a Ph.D. in Computer Science from the University of York, UK. She has been a senior research fellow at Politecnico di Milano and later at the University of Trento, Italy, where 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 to create and expand. Silvia has joined the Swiss Data Science Center in 2019 as a Principal Data Scientist for industry collaborations with the aim of helping the industry benefit from the latest innovation in data science.
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.
Tao Sun joined SDSC as a Computer Scientist in March 2020. Tao holds a MSc in Electrical & Electronic Engineering from EPFL, where he specialized in data analytics and developed a keen interest in machine learning. Before coming to Switzerland, he completed his undergraduate studies in Zhejiang University (Hangzhou, China) with a major in Electronic Information Engineering and a minor in Public Administration.
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.
Travis started out in test automation at a search engine company called Splunk. He then worked on consumer cloud storage products at Amazon and Microsoft. His interest in the Scala programming language as well as the alps brought him to Switzerland. He joined the SDSC in 2020 as part of the KG Team.
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.
Viktor Gal joined the RENKU team as a senior software engineer in 2021. He finished his post-graduate studies at the University of Ghent (Belgium) as a Marie-Curie fellow, where his research was in medical image similarity using machine learning. He worked about 5 years in industry [telecomm, banking, e-commerce] as a data scientist. In 2017, he has moved to Zurich to start his PostDoc at ETHZ with Gunnar Rätsch, where he got involved with Renku about 2 years ago. On a windy day you can always find him on the lake trying to foil with his boat.
Virginia Friedrich received her Computer Systems Engineering degree from the Universidad Nacional del Sur in Argentina. She took her first steps as a Software Developer in Hexacta, one of the 100 best outsourcing companies in the world (IAOP). In 2015 Virginia came to Zürich to do an IAESTE internship and shortly after began working for SkyCell AG as a Frontend Developer, where she also gained some experience doing Project Management and Requirements Engineering tasks.
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.