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BigDat 2019

Cambridge, United Kingdom

January 7-11, 2019


Co-organized by:


Cambridge Big Data Initiative, University of Cambridge


Institute for Research Development, Training and Advice (IRDTA)

Brussels / London





BigDat 2019 will be a research training event with a global scope aiming at 
updating participants on the most recent advances in the critical and fast 
developing area of big data, which covers a large spectrum of current exciting 
research and industrial innovation with an extraordinary potential for a huge 
impact on scientific discoveries, medicine, engineering, business models, and 
society itself. Renowned academics and industry pioneers will lecture and share 
their views with the audience.


Most big data subareas will be displayed, namely foundations, infrastructure, 
management, search and mining, security and privacy, and applications (to 
biological and health sciences, to business, finance and transportation, to 
online social networks, etc.). Major challenges of analytics, management and 
storage of big data will be identified through 2 keynote lectures, 24 four-hour 
courses, and 1 round table, which will tackle the most active and promising 
topics. The organizers are convinced that outstanding speakers will attract the 
brightest and most motivated students. Interaction will be a main component of 
the event.


An open session will give participants the opportunity to present their own 
work in progress in 5 minutes. Moreover, there will be two special sessions 
with industrial and recruitment profiles.



Master's students, PhD students, postdocs, and industry practitioners will be 
typical profiles of participants. However, there are no formal pre-requisites 
for attendance in terms of academic degrees. Since there will be a variety of 
levels, specific knowledge background may be assumed for some of the courses. 
Overall, BigDat 2019 is addressed to students, researchers and practitioners 
who want to keep themselves updated about recent developments and future 
trends. All will surely find it fruitful to listen and discuss with major 
researchers, industry leaders and innovators.



3 courses will run in parallel during the whole event. Participants will be 
able to freely choose the courses they wish to attend as well as to move from 
one to another.



BigDat 2019 will take place in Cambridge, a city home of a world-renowned 
university. The venue will be:






PROFESSORS AND COURSES: (to be completed)


Thomas Bäck (Leiden University), [introductory/intermediate], Data Driven 
Modeling and Optimization for Industrial Applications


Richard Bonneau (New York University), [introductory] Large Scale Machine 
Learning Methods for Integrating Protein Sequence and Structure to Predict Gene 


Altan Cakir (Istanbul Technical University), [introductory/intermediate] 
Processing Big Data with Apache Spark: From Science to Industrial Applications


Nitesh Chawla (University of Notre Dame), tba


Nello Cristianini (University of Bristol), [introductory] The Interface between 
Big Data and Society


Geoffrey C. Fox (Indiana University, Bloomington), [intermediate] High 
Performance Big Data Computing


David Gerbing (Portland State University), [introductory] Data Visualization 
with R


Geoff McLachlan (University of Queensland), [intermediate/advanced] Applying 
Finite Mixture Models to Big Data


Folker Meyer (Argonne National Laboratory), [intermediate] Skyport2: A Multi 
Cloud Framework for Executing Scientific Workflows


Wladek Minor (University of Virginia), tba


Sankar K. Pal (Indian Statistical Institute), [introductory/advanced] Machine 
Intelligence and Soft Granular Mining: Features, Applications and Challenges


Lior Rokach (Ben-Gurion University of the Negev), [introductory/advanced] 
Ensemble Learning


Michael Rosenblum (University of Potsdam), [introductory/intermediate] 
Synchronization Approach to Time Series Analysis


Hanan Samet (University of Maryland), [introductory/intermediate] Sorting in 
Space: Multidimensional, Spatial, and Metric Data Structures for Applications 
in Spatial and Spatio-textual Databases, Geographic Information Systems (GIS), 
and Location-based Services


Rory Smith (Monash University), [intermediate/advanced] Statistical Inference: 
Optimal Methods for Learning from Signals in Noise


Jaideep Srivastava (University of Minnesota), tba


Mayte Suárez-Fariñas (Icahn School of Medicine at Mount Sinai), [intermediate] 
A Practical Guide to the Analysis of Longitudinal Data Using R


Jeffrey Ullman (Stanford University), [introductory] Big-data Algorithms That 
Aren't Machine Learning


Andrey Ustyuzhanin (National Research University Higher School of Economics), 
[intermediate/advanced] Surrogate Modelling for Fun and Profit


Wil van der Aalst (RWTH Aachen University), [introductory/intermediate] Process 
Mining: Data Science in Action


Zhongfei Zhang (Binghamton University), [introductory/advanced] Relational and 
Multimedia Data Learning



An open session will collect 5-minute voluntary presentations of work in 
progress by participants. They should submit a half-page abstract containing 
title, authors, and summary of the research to by December 30, 



A session will be devoted to 10-minute demonstrations of practical applications 
of big data in industry. Companies interested in contributing are welcome to 
submit a 1-page abstract containing the program of the demonstration and the 
logistics needed. At least one of the people participating in the demonstration 
must register for the event. Expressions of interest have to be submitted to by December 30, 2018.



Firms searching for personnel well skilled in big data will have a space 
reserved for one-to-one contacts. It is recommended to produce a 1-page .pdf 
leaflet with a brief description of the company and the profiles looked for, to 
be circulated among the participants prior to the event. At least one of the 
people in charge of the search must register for the event. Expressions of 
interest have to be submitted to by December 30, 2018.

ORGANIZING COMMITTEE: (to be completed)


Sara Morales (Brussels)

Manuel J. Parra-Royón (Granada)

David Silva (London, co-chair)



It has to be done at


The selection of up to 8 courses requested in the registration template is only 
tentative and non-binding. For the sake of organization, it will be helpful to 
have an approximation of the respective demand for each course. During the 
event, participants will be free to attend the courses they wish.


Since the capacity of the venue is limited, registration requests will be 
processed on a first come first served basis. The registration period will be 
closed and the on-line registration facility disabled when the capacity of the 
venue is exhausted. It is highly recommended to register prior to the event.



Fees comprise access to all courses and lunches. There are several early 
registration deadlines. Fees depend on the registration deadline.



Suggestions for accommodation will be available in due time.



A certificate of successful participation in the event will be delivered 
indicating the number of hours of lectures.




Cambridge Big Data Initiative, University of Cambridge


Institute for Research Development, Training and Advice (IRDTA) – 
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