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Lightning talks 2019
Naila murray, Group lead & senior scientist, NAVER LABS Europe
Naila is a senior scientist and computer vision group lead at NAVER LABS Europe. She obtained a B.Sc. in Electrical Engineering from Princeton University in 2007, and masters and PhD degrees from the Unversitat Autonoma de Barcelona in 2009 and 2012 respectively. Naila’s research interests include fine-grained visual categorization and search, visual attention and image aesthetics analysis. Currently, her research focuses on image search and video action recognition.
Tina Rosario, Head of Data Innovation and Chief Data Officer, SAP FRANCE
Tina is a head of data innovation and works directly with senior business executives to design a data management approach, future state information management capabilities and consult with executives on the execution of their data strategy. As a business strategy professional, Tina has more than 25 years of experience in business process re-engineering, defining business impact and leading transformation programs. During her 18 years at SAP, Tina has held executive positions in business operations, consulting management, and corporate strategy. Tina also serves as President of the European chapter of the Women in Big Data network whose mission is to promote diversity in the field of data management.
ruth urner, Assistant Professor, York University
Ruth Urner is an assistant professor at York University in Toronto, Canada. Previous to that she was a senior research scientist at the Max Planck Institute for intelligent systems in Tübingen, Germany, and a postdoctoral fellow at Carnegie Mellon’s Machine Learning department as well as at Georgia Tech. She received her PhD from the University of Waterloo for a thesis on statistical learning theory. Her research develops mathematical tools and frameworks for analyzing the possibilities and limitations of automated learning, with a focus on semi-supervised, active and transfer learning. She regularly serves as a senior program committee member of the major machine learning conferences, such as NIPS, ICML, AISTATS and COLT.
Cordelia Schmid, Research director Inria / Google
Cordelia is a research director at Inria Grenoble Rhone-Alpes. She studied Computer Science at the University of Karlsruhe and received a PhD from the Institut National Polytechnique de Grenoble (INPG) and did her postdoctoral reserarch in the Robotics Research Group of Oxford University.
Cordelia received numerous awards for her work and was was elected to the German National Academy of Sciences, Leopoldina. Starting 2018 she holds a joint appointment with Google research.
Andreea Hossmann, Principal Product Manager, Swisscom
Andreea Hossmann is a Principal Product Manager for Data, Analytics and AI at Swisscom. She is also a Venture Associate, working with Swisscom Ventures to assess AI startups worldwide. During her 3.5 years at Swisscom, Andreea was a Senior Data Scientist, before assembling and leading a Data Science team to work on AI topics, such as natural language understanding and search. She is an experienced researcher with a background in applied machine learning, network science and computer networking from her PhD education at ETH Zürich.
Michele Sebag, Deputy director Lab. of Computer Science, Université Paris-Sud
With a background in maths, Michele went to industry and started to learn about computer science and artificial intelligence. She got interested in AI, became consulting engineer, and realized that machine learning was something to be. She was offered the opportunity to start research on machine learning for applications in numerical engineering at Ecole Polytechnique, passed my PhD and entered CNRS. Michele founded the TAO (Machine Learning and Optimization) INRIA-CNRS team with Marc Schoenauer at Univ. Paris-Sud. Her current research interests include deep learning and causal learning, with applications in social sciences, and AutoML.
Berenice Pila Diez, Senior Data Scientist, Boehringer Ingelheim
Berenice is a Senior data scientist in the Global Data Science team at Boehringer Ingelheim. She holds a PhD in Astrophysics from Leiden University (The Netherlands), and a degree in Physics from Complutense University of Madrid (Spain). Before joining Boehringer Ingelheim, she worked as a data scientist in London for KPMG and later for Experian Data Labs. Berenice is one of the “20 in Data & Technology” woman awarded in 2017 in the UK.
Sandhya Prabhakaran, Research Fellow, Memorial Sloan Kettering Cancer Center
Sandhya Prabhakaran is a Research Fellow at Memorial Sloan Kettering Cancer Center. She received her Ph.D degree from the Department of Mathematics and Computer Science, University of Basel in 2014 and her Masters degree in Intelligent Systems (Robotics) from University of Edinburgh in 2008. Her research deals with developing and applying statistical models, particularly to problems in Cancer Biology. Prior to academics, she was an Assembler programmer at IBM Bangalore. She practises yoga and meditation and has completed 3 of the World Marathon Majors: Berlin, Chicago and NYC. She also did the Tour du Mont Blanc in 11 days.
Eleni Pratsini, Managing Director, Accenture AG
Eleni is the AI lead in Accenture Technology Europe, bringing innovation to clients. She joined Accenture from IBM Research where she held leadership positions in Europe and the USA. In her most recent roles, she was Director of Cognitive IoT Solutions, Lab Director of IBM Research – Dublin, and Director of Optimization Research. Her interests lie at the intersection of AI, Analytics and Optimization and the development of industrial solutions. Prior to moving to industry, Eleni had a successful career in academia, first in the US as associate professor at Miami University, and then in Europe at the ETHZ.
Maria Rodriguez Martinez, Technical Lead of Systems Biology at IBM Research ZUrich
Maria is the Technical Leader of the group of Systems Biology at IBM Research - Zürich. A physicist by training, she joined IBM Research in 2013, and became an associated member of the Department of Biology at ETH in 2014. Her current research focuses on the development of computational and statistical approaches to unravel cancer molecular mechanisms using high-throughput multi-omics datasets and single-cell molecular data. She is the technical coordinator of two H2020 consortia: PrECISE and iPC, focused on developing personalized medicine approaches for prostate and paediatric cancer patients respectively.
Anita Schmid, Data Scientist, Migros
Anita is a Data Scientist at Migros, Switzerland largest retailer, where she works on various projects advancing the retail customers' experience using data. She thrives on making business impact with data products using Machine Learning. She holds a Masters in Physics and a PhD in Neuroscience from ETH Zurich. She lived and worked in New York City for 10 years before returning to Switzerland. She is co-founder of the Zurich chapter of the Women in Machine Learning and Data Science Meetup group. She also teaches Machine Learning at Propulsion Academy, a bootcamp for aspiring Data Scientists in Zurich.
Franziska Dammeier, Senior Data Scientist, Ava AG
Franziska Dammeier is a Senior Data Scientist at Ava AG and responsible for all algorithm development in the Trying To Conceive product line. Previously she worked as a research associate in renewable energies at ZHAW. She holds a Bachelor’s degree from Caltech, and Master’s and PhD degrees from ETH Zurich.
Reka Solymosi, Lecturer in Quantitative Methods, University of Manchester
Reka is a lecturer in quantitative methods focused on making use of new forms of data to gain insight into people's behaviour and subjective experiences, particularly focusing on crime, transport, and spatial research. Reka is also interested in promoting data literacy.
SARAH EBLING, Senior researcher, University of Applied Sciences of Special Needs Education
Sarah is a senior researcher and lecturer at the University of Applied Sciences of Special Needs Education (HfH) Zurich and University of Zurich. With a background in computational linguistics, her focus in research and teaching is on the contribution of language technology to accessibility for persons with disabilities. Her previous research includes sign language technology, specifically, machine translation into sign language and sign language synthesis, the generation of signing avatars. More recently, she has been involved in an interdisciplinary project centering around automatic sign language recognition.
Helen Yannakoudakis, Senior Research Associate, University of Cambridge
Helen is a Senior Research Associate and an Affiliated Lecturer at the Department of Computer Science and Technology of the University of Cambridge. Helen is working on machine learning for natural language processing, with a focus on real-world applications and noisy domains, such as social media and learner language. She has developed machine learning models for automatically assessing someone's language competence that are now deployed under the Cambridge brand. Helen is also a Fellow of Murray Edwards College (Cambridge), and a Research and Development specialist at iLexIR, working on viable commercial applications in AI and natural language processing. Previously, she was a Postdoctoral Research Fellow at Cambridge English Language Assessment, and a Newton Trust Teaching Fellow at Girton College, Cambridge. Helen holds a PhD in Natural Language and Information Processing from the University of Cambridge, and an MPhil in Computer Speech, Text and Internet Technology.
Lito Kriara, Digital Biomarker Data Scientist, Roche, Basel
Lito is a Mobile Systems Researcher and Data Scientist. She received her PhD from the University of Edinburgh and continued her research at Disney Research and ETH Zurich. Currently she is working with Roche on digital biomarkers from remote patient monitoring in clinical trials. Her research interests include mobile data enabled healthcare, user understanding, and affective computing.
lise regnier, Lead Inventive Science and Architect, Warner Bros. Entertainment
After studying Music and Mathematics Lise pursued her studies doing a PhD at the IRCAM on the topic of Singing Voice Identification. After few post-docs in the field of Music Information Retrieval Lise joined the Warner Bros Company. As the lead Data Scientist and Architect of the French territory she is conducting researches on marketing automation and video sales and box office prediction.
Natasha Antropova, Research Engineer, Google DeepMind
Natasha is currently a Research Engineer at Google DeepMind. Her current research focuses on developing machine learning methods for breast cancer diagnosis based on screening mammograms. Prior to joining DeepMind, she was doing a PhD in medical physics at The University of Chicago under the supervision of Dr. Maryellen Giger. During her dissertation, she developed machine learning methods for breast cancer diagnosis and prognosis based on dynamic MRIs and mammograms.
Tanvi Singh, Managing Director, Head of Analytics & Data Science at Credit Suisse’s Compliance organization, Credit Suisse
Tanvi is a Managing Director at Credit Suisse and has created and been leading one of the largest Analytics & Data Science teams in the space of Banking and Financial Regulatory Compliance in Switzerland. She has two decades of experience in diverse industries and domains, including extensive expertise in AI, Data Science, Machine Learning, Statistics and Digital Analytics. She has been implementing a wide range of use cases and creating and monetizing value from Big Data in the Banking and Finance industry, particularly in the area of Anti-Money Laundering and Transaction Surveillance, Employee Surveillance, KRI and KPI Management, and Private Banking.
Christina Heinze-Deml, Postdoctoral Researcher, ETH Zurich
Christina Heinze-Deml is a postdoc and lecturer at the Seminar for Statistics at ETH Zurich. During her PhD she was advised by Nicolai Meinshausen and Jonas Peters and she also spent some time at Facebook AI Research and DeepMind. Among other things, Christina has worked on privacy-preserving distributed machine learning and causality. Within the field of causality, she has been interested in causal structure learning when data sets from different environments are available and recently, she has used a causal framework to make classifiers more robust to certain adversarial domain shifts. More generally, Christina is particularly interested in exploring the connections between causal inference, robust machine learning and fairness.
Deniz Gunaydin, Senior Data Scientist, Swiss Re
Deniz is a senior data scientist in Swiss Re. Deniz has data science experience having worked in companies such as IBM, Nokia, and Credit Suisse, as well as, a research background in Computer Vision. After working on data analytics and machine learning projects almost a decade, Deniz is keen on following through what data reveals to ignite a change. She is passionate about building data-driven digital products, and driving innovation and hackathon projects as a strong believer in intrapreneurship. Deniz holds a master's degree in Computer Science and a minor in Management of Technology and Entrepreneurship from EPFL, Lausanne. Recently her focus has been on recommender systems, propensity models, pricing optimization and user behavior analytics.
Alexandra Fritzen, Product Manager at Oracle Labs
Alexandra is a product manager at Oracle Labs, focusing on Graph analytics and graph query languages. Her research includes graph analytics and visualization for various domains such as financial crime and health care.
Kornelia Papp, NLP Data Scientist, Swiss Re, Zurich
Kornelia is a data scientist at Swiss Re’s Digital Smart Analytics team taming unstructured data. She holds a Ph.D. in Cognitive Semantics and has over 10 years’ experience in building and managing analytic capabilities in various industries. She is the founder of the NLP Zurich group, an AI-driven language technology focused event series in Switzerland. Kornelia currently focuses on document understanding solutions using rule-based programming, machine learning, and augmented intelligence techniques. She previously developed AI applications in the area of speech technology, machine translation, fraud detection, and natural language generation. As an operational efficiency addict, Kornelia regularly speaks at both scientific and business events to help move AI and product intelligence automation forward.
NATASCHA SPINDLEr, Senior Data Scientist, AXA, Zurich
Natascha is a senior data scientist at AXA Switzerland. Within the data science team, she is responsible for a wide range of projects, pushing the digital transformation in the firm. Topics include campaign management, machine learning models for predicting AXA’s market share after product optimizations, and general customer behavior analytics. Natascha has as well long-year working experience in the manufacturing segment, particularly as senior liquid handling scientist and project leader in the medical-technology company Tecan. She graduated with PhD in Physics from RWTH Aachen and Forschungszentrum Jülich on computer vision in environmental science. Natascha lives with her two kids and husband in Kanton Zurich.
SOFIA KYRIAKOPOULOU, Director, Head Smart Analytics Group Asset Management, Swiss Re, Zurich
Sofia is heading Smart Analytics in Group Asset Management at Swiss Re. Her expertise lies in digital strategy, data science and financial engineering. She has experience leading the delivery of analytics, machine learning/AI solutions that help financial services organizations automate decision processes and obtain insights from data. Prior joining Swiss Re, she has worked for at Vontobel Asset Management, UBS and Credit Suisse. She holds an MBA (University of St. Gallen / Imperial College London) and has an engineering background (MSc Computer Science EPFL, MEng & BEng Electrical and Computer Engineering NTUA).