In an era in which Big Data is booming, so are challenges that can only be surpassed with strong theoretical and practical skills. BIGMATH – INNOVATIVE TRAINING NETWORK (ITN) ON BIG Data challenges for MATHematics is an EU funded project that aims to provide a group of young mathematicians with up-to-date training and knowledge for cutting-edge research on mathematical disciplines. Through a close partnership with the industry, the PhD students are focused on real Big Data-related industrial problems. The research activities to be undertaken by the researchers hired by IST are carried out at the Institute for Systems and Robotics (ISR), the Mathematics Department, and industrial partners 3lateral and SDG consulting.

This is the case of Stevo Rackovic, who will be working on a project related with rich logic optimization, a field in the animation industry. His research will be developed in partnership with 3lateral , a company focused on creating biokinetic models of the human form using computer graphics, with a strong focus on the face. These animations are mostly used in video games, but the company is building a database of such models through 3D and 4D scanning, with registration of this data for the purpose of statistical modelling and machine learning. This is done by scanning people in real time, for which great computational power is necessary. Stevo’s challenge will be to optimize this process to increase the speed and quality of the scanning.

Currently, at ISR, Stevo is taking his theoretical courses and building the basis for the work to be done later in the USA. His goals are to learn a lot more on optimization, and related themes such as linear algebra and stochastics. The mathematics behind the development of the technology towards an optimized distribution is what truly challenges him. “You need to try to model the difference between the positions of a human in consecutive moments. The theory behind that needs to be perfected in order to increase speed without losing quality. This implies a lot of data and a lot of time to process it.”

As a Marie Curie fellow, he has privileged access and contact with top-notch institutions in the field. To anyone wanting to apply, he can’t keep from warning about the process – having good mentors and references is very important – but advises that focus on an opportunity and hard work towards it can lead to great things.