Ople | Kaggle Grandmaster
Gilberto TitericzOple | Kaggle Grandmaster
Gilberto is the leading data scientist at Ople, where he develops artificial intelligence products that automate the data science process. Prior to Ople, he worked at Airbnb, Petrobras and Siemens. He is well known for his extensive track record in winning machine learning competitions. Gilberto had held the #1 position at Kaggle for more than two years and holds a master's degree in electrical Engineering from UTFPR Curitiba, Brazil.
Alipio JorgeINESC TEC
Alípio Jorge is an associate professor of the Faculty of Science of the University of Porto, where he leads the Department of Computer Science. He is the coordinator of LIAAD, Laboratory of Artificial Intelligence and Decision Support of INESC TEC. He holds a Ph.D. and a degree in Computer Science from U. Porto and a Master's Degree in Foundations of Advanced Information Technology from Imperial College London and has been an active researcher in Machine Learning and Data Mining with a focus on Information Extraction and Recommender Systems. He leads research projects and technology transfer in data mining and artificial intelligence and regularly organizes conferences in the area, such as the ECML-PKDD machine learning conference in 2005 and 2015, and was vice-president of APPIA - Portuguese Association of Artificial Intelligence from 2000 to 2008. He is the director of the Masters in Data Science at FCUP and launched the Master in Data Analysis and Decision Support Systems from FEP. He is currently the coordinator of the team defining the Portuguese AI strategy.
Szilard studied Physics in the 90s and obtained a PhD by using statistical methods to analyze the risk of financial portfolios. He worked in finance, then more than a decade ago moved to become the Chief Scientist of a tech company in Santa Monica, California doing everything data (analysis, modeling, data visualization, machine learning, data infrastructure etc). He is the founder/organizer of several meetups in the Los Angeles area (R, data science etc) and the data science community website datascience.la. He is the author of a well-known machine learning benchmark on github (1000+ stars), a frequent speaker at conferences (keynote/invited at KDD, R-finance, Crunch, eRum and contributed at useR!, PAW, EARL, H2O World, Data Science Pop-up, Dataworks Summit etc.), and he has developed and taught graduate data science and machine learning courses as a visiting professor at two universities (UCLA in California and CEU in Europe).
Miguel CabreraNew Yorker
Miguel works as Senior Data Scientist for New Yorker, a German clothing retailer. He leads a multidisciplinary team implementing end-to-end solutions within the company.
Previously he worked at TrustYou processing millions of hotel reviews from across the web. Miguel obtained a M.Sc. degree in Computer Science from TU in Munich with an honors Masters in Technology Management. In Munich he founded and ran the Munich DataGeeks, the second largest ML/Data Science group in Germany. In Berlin he was part of the organization team of PyData Berlin 2017 and he had volunteered in many editions of Europython.
Coming to the Data Science field from a Software Engineer background he is a strong believer in applying Software Engineering practices to the Data Science craft.
When not using his computer Miguel enjoys playing Latin American folk music and practicing Brazilian Jiu-Jitsu.
Hugo Penedonesex-Google DeepMind
Hugo has been doing Machine Learning research and applications since 2005, in different fields including time series analysis, computer vision, online ranking, bioinformatics and reinforcement learning. This path led him to diverse workplaces such as the European Space Agency, EPFL, Microsoft and Google DeepMind. He loves to find neat solutions for real world problems.
Mariana is a Data Engineer at QuantumBlack, a Mckinsey company. She joined QuantumBlack in April 2018 and has worked in the pharmaceutical and banking industries ever since. Her role is to work closely with data scientists to build enterprise level end-to-end big data solutions from ingestion to feature engineering.
Prior to joining QuantumBlack, Mariana worked a Data Analyst for Keboola in London. She graduated in 2017 from the University of Porto (FEUP) with a Master’s degree in Mechanical Engineering.
Rui BarrosRádio Renascença
Rui Barros is a data journalist at Rádio Renascença since 2016. There, he works with code and databases to build interactive features and get new data-driven stories. He is also responsible for Renascença's Open Data Portal, the first open data initiative from a Portuguese media outlet.
Rui graduated in 2016 from University of Minho with a Bachelor's degree in Communication Science. Currently, he is writing a Master's Thesis about the forces shaping innovation on his newsroom.
University of Coimbra
Catarina MaçãsUniversity of Coimbra
Catarina Maçãs has an Undergraduate and Master degrees in Design and Multimedia from University of Coimbra. Currently, she is enrolled in the Doctoral Program of Information Science and Technology of the University of Coimbra and is a teaching assistant at the Department of Informatics Engineering of the University of Coimbra. She is also a researcher at the Computational Design and Visualization Lab (CDV), which is part of the Centre for Informatics and Systems of University of Coimbra (CISUC). Her research focuses on Information Visualisation, more specifically in the visualisation of temporal events for the understanding of patterns and trends.
Nemanja Radojkovic, electrical engineer-turned-Data Scientist, PhD dropout, working as a Senior Data Scientist at dataroots, a feisty boutique consultancy based in Leuven, Belgium.
Jiu-Jitsu enthusiast, abusing data until it confesses everything. Loves talking long walks through Random Forests. Favorite fruit: LIME
DK Ventures | deepkapha.ai
Tarry SinghDK Ventures | deepkapha.ai
Eliano MarquesEmirates Group
Eliano Marques is the VP of Data Science at Emirates Group. As part of the role, Eliano aims to build a world-class team of AI experts to build and deploy Data Products with Machine/Deep Learning on its core on top of the most critical use-cases across the Group leveraging the best and most innovative technologies. In the past, has successfully led teams and projects to develop and implement analytics platforms, predictive models, and analytics operating models and has supported many businesses making better decisions through the use of data. Recently, Eliano has been focused in developing analytics solutions for customers around deep learning, predictive asset maintenance, customer path analytics, and customer experience analytics across different industries. Eliano holds a degree in economics, an MSc in applied econometrics and forecasting, and several certifications in machine learning.Emirates Group
Office for National Statistics
Sophie WarnesOffice for National Statistics
Sophie is a Data Journalist based in Cardiff, and has previously worked for The Mirror, ITV News and The Guardian. She writes a weekly data journalism and data visualisation newsletter called Fair Warning.
Nuno Carneiro has 4 years of experience as a data scientist, in industries such as e-commerce, financial services and customer service. He has been responsible for the deployment of machine learning models at many financial institutions in Europe and the US while working at James, where he led the Customer Success Team. Nuno is currently responsible for AI at Cleverly, a startup working with natural language understanding to develop an assistant for customer service teams.
Nuno has a Masters in Industrial Engineering and Management from the Faculty of Engineering of the University of Porto (FEUP), and has published work in journals such as Decision Support Systems. He is a member of the Global Shapers Community of the World Economic Forum.
Sam HopkinsDareData Engineering
Sam is a generalist Software Engineer, Data Scientist, Data Engineer, and IT educator. He started his technical career working closely with a Carnegie Mellon professor who has since gone on to become a Director of AI and Machine Learning at Apple. He has worked as a data scientist and software engineer with some of the most successful names in the Portuguese startup scene such as Unbabel, OutSystems, James, GetSocial, and Daltix. During this time he developed solutions that are currently in use by brands such as Pinterest, SkyScanner, Oculus, UnderArmour and King. While CTO at James and experiencing difficulty in hiring data scientists, he co founded the Lisbon Data Science Academy which is still running strong. Through his various companies and organizations, Sam has been directly involved with the training of almost 100 data scientists in the last 2 years.
University of Coimbra
Evgheni PolisciucUniversity of Coimbra
Evgheni Polisciuc is a data visualisation specialist and a cross-media designer. Currently he is a PhD student at the Doctoral Program for Information Science and Technology of University of Coimbra. Concluded a Bachelor and Master degrees in Design and Multimedia at the same university. In March of 2013 he was invited to SMART (Singapore-MIT Alliance for Research and Technology) as a visiting MSc student.
He is interested in information visualisation and aesthetics, visual complexity and perception and dynamic and adaptive visualisation systems. Particularly, interested in the application of design strategies and visualisation techniques to study of geo-temporal information.
Pedro is a research engineer with a focus on data processing systems @ Feedzai. Since finishing his degree in 2016 he has worked in different areas from frontend development at Farfetch to distributed systems and machine learning at Feedzai. Pedro is particurlary focused on the performance both in the software and UX & pushing the boundaries of whatever he touches.
An easy nerd snipping target, presented with big real-world problems he will lend a hand even if just to challenge himself.
Sara Guerreiro de Sousa
SF Digital Labs | Data Science for Social Good
Sara Guerreiro de SousaSF Digital Labs | Data Science for Social Good
Sara is a Data Scientist solving real-world problems that enable better decision-making processes and have potential for high social impact in education, health, energy, criminal justice, social services, etc.
Sara’s passion for data and her desire to use it for good made her move to London to join the Social Finance's pioneering project of Digital Labs. During the past 4 years she has been working with non-profits, foundations and public-sector partners on data science projects to tackle problems that really matter by surfacing insights that partners understand, trust and know how to use.
More recently, Sara was working as a Data Science Project Manager for the Data Science for Social Good programme at Imperial College in London and she has been actively supporting the creation of an open community of data scientists, data lovers and data enthusiasts that want to explore ways of using data in an ethical and impactful way.
Prior to this, Sara worked as Assistant Professor at of two master courses at NOVA School of Business and Economics and worked in projects across education, development, immigration and intercultural dialogue.
Sara holds a BSc in Applied Mathematics and Computation from the Technical University of Lisbon (IST, Portugal), a MSc in Finance (NOVA School of Business and Economics, Portugal) and a Data Science certification from General Assembly London.
In her free time, she loves exercising, reading and taking care of her small plant ecosystem.
Jorge Martinez Rey
JTA: The Data Scientists
Jorge Martinez ReyJTA: The Data Scientists
Jorge Martinez-Rey is a Data Visualization Engineer. He has a background in Physics, with an MSc. in Applied Physical Oceanography at the British Antarctic Survey in Cambridge, UK, and a PhD. in Ocean Biogeochemical Modeling at the LSCE in Paris, France.
His work focuses on bridging the gap between data from complex software architectures such as Earth System Models and its visual representation. This includes dataviz projects of wind, icebergs, carbon, oxygen, hurricanes, ocean acidification or model benchmarking, combining data analysis in Python, data visualization in D3.js and bits of graphic design.