Hi, I am Sicui Zhang. I have been studied as a PhD student in Zhejiang University for two years. In the past, my work focused on the clinical decision support system (CDSS) ‘Tracebook’ and machine learning work in the Biomedical Engineering department of ZJU. From now on, I will work here as an exchange PhD of the Brain Bridge Project for another two years.
It is the first time that I have been to The Netherlands. Although the beginning is always difficult, I will try to integrate our group as soon as possible. I really like the life and the people here. And I believe there will be some surprise waiting for me in the future!
Hi, I am Kalliopi Zervanou and I am a computational linguist. In an almost previous life, I got my Bachelor in French Literature & Linguistics from Aristoteles University of Thessaloniki and sometime after working as a conference interpreter I returned to academia for an MSc in Machine Translation from the UMIST Language Engineering Dept., and a PhD in Information Extraction from the School of Computer Science of the University of Manchester. My research focuses in information management of mainly unstructured text data (free-text): I have a long experience in information extraction research, including language technology applications in information retrieval, digital libraries and semantic web, for a variety of domains (financial, biomedical, humanities, police). Since 2009, I have been actively involved in digital humanities in a series of projects and as a leading member of the computational linguistics digital humanities community, both as programme chair of the LaTeCH workshop series, as well as founding member of the respective ACL Special Interest Group, SIGHUM, which I also serve as elected secretary for three consecutive terms, since 2013. My most recent research focused on historical data modelling issues and event extraction from texts.
I received my Bachelor’s degree from Ferdowsi University of Mashhad in 2012 and then, my Master’s degree from University of Tehran in 2015. After that I worked for 2 years as a data scientists in Tehran.
Now, I am a PhD student at TU/e in Information Systems (IS) group. My research focus is on the programmatic advertising decision system project which involves collaboration with high tech industry. My research interests also include data mining, data analysis, machine learning and social networks analysis.
I obtained my Bachelor’s degree in Computational and Applied Mathematics in 2010 from the University of Campinas (Unicamp), with a specialisation in Operational Research. After my bachelor studies, I worked in Data Analytics roles for 4.5 years at two major companies in the banking sector, based in São Paulo, Brazil.
I then moved to Dublin, Ireland to pursue a Master’s degree in Business Analytics at the University College Dublin (UCD). After completing the programme in 2016, I extended my stay in Ireland working as Data Scientist.
At TU/e I will work within the Information Systems (IS) and the Operations, Planning, Accounting and Control (OPAC) groups as PhD student on the Real-time data-driven maintenance logistics project (WP1), which aims to leverage dynamic maintenance logistics policies supported by real-time data. The topic is focused on the integration of machine learning and optimisation models for more efficient and real-time decision making. I am excited to start working on the topic and looking forward to the next years of learning and collaboration.
You are cordially invited to the Data Science Seminar that will take place on Friday, 28th October 2016 (TU/e AUD2).
Participation is free of charge, but please register by sending an email to email@example.com before 26th October 2016.
Speaker: Joao Paulo Carvalho, INESC ID’s Spoken Language Systems Laboratory
Title: Fuzzy Fingerprints: Identification and classification in Big data using top-k values
Information about the event is as follows:
Abstract: Fuzzy Fingerprints are a recently introduced technique inspired by the fact that many types of data studied in the physical and social sciences can be approximated with a Zipfian distribution. I.e., the frequency of an item is inversely proportional to its rank in the frequency table. Fuzzy Fingerprints efficiently use the implicit information contained in top-k most frequent data values to perform identification in large datasets. The term “fingerprint” is used in the sense that fingerprints are unique, and are usually left unintentionally, allowing us to identify their “owners”. The fingerprint concept can be extended from single users to categories, topics or classes, allowing us to perform tasks such as classification and recommendation.
In this talk I will approach the ideas behind Fuzzy Fingerprints and show case studies and applications involving: identification of anonymous users based on their phone and web usage habits; text author identification based on their writing habits; classification and identification in social data (e.g. detecting tweets related to a given trending topic); classification based on medical text data; movie recommendation; etc.
This event is technically co-sponsored by the Benelux Chapter of IEEE
Computational Intelligence Society.
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I am a visiting scholar in the Information Systems group at Eindhoven University of Technology and an associate professor of School of Computer and Information Technology, Northeast Petroleum University, Heilongjiang Province, China.
I graduated from Beihang University in 2009 with Doctor of Science Degree. I have been working in Northeast Petroleum University for 6 years. I have done more than 11 projects of Business Process Modeling, Data Integration and Quality Management.
My current research and work focuses on (1) Business Process Intelligence (2)Business Process Management (3)Big Data.
My name is Jason and I will be joining the Information Systems group in September. I grew up in Curaçao and when I was 18 years old I left Curaçao to go study in Rotterdam. In 2012 I obtained my Bachelor’s diploma in Economics and in the following years I also obtained Master’s degrees in Economics (2014) and Econometrics and Management Science (2015). For the last two years I worked at CPB Netherlands Bureau for Economic Policy Analysis as an academic researcher.
The PhD project which I will be working on will aim to develop a decision-support tool for revenue optimization for online companies who provide content or physical goods by combining state-of-the-art techniques from the world of big data and from the world of optimization. Furthermore, the project will involve both the OPAC and IS groups. I am looking forward to getting to know and collaborating with the rest of both groups!
My hometown is Henan Province, China. The Shaolin Temple in my hometown is famous around the world because of the Chinese Kung fu.
My Bachelor’s Degree was received from Zhengzhou University, China after four years (2010-2014) study majored in Biomedical Engineering. Then I was admitted into Zhejiang University as a Direct Ph.D. student in September, 2014. From March 2015 to December 2015, my work mainly focused on the standardization and mapping of Chinese clinical terminology and related Medical Terminology Services, which aimed to promote the medical information exchange and sharing. The technologies used included text similarity algorithm and Chinese words segmentation. In the end, I developed a web-based middleware software including terminology mapping and management services, which will be evaluated in a real hospital.
From the end of December of 2015, I was selected to take part in the Brain Bridge Project” Risk assessment to improve patient outcomes for cardiovascular diseases”. The goal of this project is to predict the risk of cardiovascular patients of different conditions using data mining technique so that practitioners can adopt suitable therapies.
I received my Ph.D. degree in Computer Science from University of Manchester in UK. Before joining TU Eindhoven, I worked as an assistant professor in the Department of Econometrics at Erasmus University Rotterdam. Earlier, I worked in the Algorithmics group at TU Delft, in the Computational Intelligence group at TU Clausthal (Germany), and in the Institute for Advanced Computer Studies at University of Maryland, College Park, USA.
I consider myself an “Artificial Intelligence” researcher. During my Ph.D and post-doc period, I developed algorithms and mechanisms to solve multi-agent problems, i.e., task allocation, planning and scheduling problems that involve cooperative or self-interested players. Over the past a few years, I have been also investigating how data can help to improve decision making and optimization. For example, I designed machine learning methods to learn bidders’ behaviour models, and used the learned models to optimize auction design.
At TUE, I will continue my research on data driven decision making, algorithm design, (computational) game theory, and multi-agent systems. In addition, I am looking forward to learning new knowledge, tackling new application domains, and establishing new cooperations!
In March 2015 I got my Master’s degree in Biomedical Engeneering at the Eindhoven University of Technology (TU/e) in the field of Regenerative Medicine and Tissue Engineering. I also studied at Leiden University where I obtained my Master’s degree in Medicine in 2008. With this background I am able to bridge the gap between technology and patient. It inspires me to combine multiple disciplines and work with experts from different professional backgrounds.
Currently, I work as PhD student at the department of Clinical Chemistry and Laboratory Medicine at the Catharina Hospital in Eindhoven. My PhD project is part of the Data Science Flagship, a collaboration between TU/e and Philips Research (IMPULS 2.0). The aim of the project is to improve the outcome of cardiac resynchronization therapy (CRT) using hospital data and/or personal health devices by discriminating beforehand between responders and non-responders of CRT.