Dr Krishna Kumar

Research Associate, Department of Engineering
College Research Associate, King's College

Contact information

Research interests

Krishna's work involves developing massively parallel micro-/macro-scale numerical methods. Krishna works on large-scale big data frameworks for city-scale simulations and infrastructure monitoring. Multi-scale city simulation The world’s population continues to urbanise. Here in the UK, more than 80% of the population lives in the cities. Cities increasingly need to be able to do more with less, to provide for the well-being of their citizens in a truly sustainable way. Existing infrastructure is challenged by the need to increase load and usage – be that number of passengers carried, numbers of vehicles or volume of water used – and the requirement to maintain the existing infrastructure while operating at current capacity. These two demanding challenges create issues on ageing infrastructure, which we see in our everyday life. The strategy adopted in this study is a “bottom-up” for discrete spatio-temporal dynamical processes that is agent-based (human behavior) and cellular automata (physical infrastructure). I'm working on developing a multi-scale tool (from street-level to city-level) to predict the response of strongly coupled infrastructure networks for city-scale infrastructure operators, local governments and citizens using real-time, simulation and sensor data.

Publications

About us

The Cambridge Centre for Data-Driven Discovery (C2D3) brings together researchers and expertise from across the academic departments and industry to drive research into the analysis, understanding and use of data science.

The Centre is funded by a series of collaborations with partners in business and industry which have an interest in using data science for the benefit of their customers and their organisations. Our founding partner is Aviva, the UK’s leading insurance company. We work with industrial partners to build a portfolio of collaborative research projects, provide professional development opportunities for their own staff and access to the full breadth and depth of the University’s talent pool in the area of data science.

With unprecedented access to increasing volumes of data, our research ranges from the underlying fundamentals in mathematics and computer science, to data science applications across all six University Schools of Arts and Humanities, Biological Sciences, Clinical Medicine, Humanities and Social Sciences, Physical Sciences, and Technology.

In parallel, our research addresses important issues around law, ethics and economics, in order to apply data science to solve challenging problems for society.

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