Scope of the Spring School
We live in a Big Data world where information is accumulating at an
and often the real problem has shifted from collecting enough data to
with its impetuous growth and abundance.
In fact, we often face poor scale-up behavior from algorithms that have
been designed based
on models of computation that are no longer realistic for big data.
The spring school aims for an introduction to the design of
efficient algorithms for Big Data problems by lectures from internationally
leading experts from computer science and mathematics,
addressing in particularily young researchers in India and Germany.
The spring school is jointly organised by
the priority program "Algorithms for Big Data" of the German Reserach
Foundation (DFG) and
Indian Institute of Technology, Bombay.
- Jan 10:
| Venue for the school is F.C. Kohli Auditorium, KRESIT, IIT Bombay.
Open Venue in Google Maps
- Oct 4:
| Program schedule announced.
Motivation and Objectives
The Indo-German Spring School on
Algorithms for Big Data
wants to train young researchers, in particular PhD students and
postdocs, in algorithmic solution techniques for big data problems. To
this end, we bring leading researchers together that work on big data
aspects in different scientific subfields - albeit under the common
umbrella of efficient algorithms and data structures for large-scale
problems. Besides the training, such a forum would allow the exchange of
ideas for solving future challenges in the big data context. Moreover,
and at least equally important, the lectures presented by international
experts introduce students to unfamiliar areas related to each student’s
own expertise. The newly acquired knowledge is likely to improve the
students’ skills and take their scientific achievements to a higher
We will also invite selected industrial
researchers from India as speakers. Furthermore, interested
practitioners are welcome to attend and share their experience in
discussion rounds. This opening to industry is meant to improve the
exchange between theory and practice in both directions. Academic
researchers learn about application requirements in practice and, in
turn, top-notch academic results may enter industrial solutions sooner.
This way the workshop would also serve as a platform for seeding new
collaborations, both between academia and industry but also within
academia across the two countries and beyond.