In today's world data is ubiquitous. Increasingly large and complex datasets are gathered across many domains. Data analysis - making sense of all this data …
This dissertation shows how mobile phone data can be used in order to study the consequences of short term population movement. All three chapters use …
Modeling the complex interactions that arise when query workloads share computing resources and data is challenging albeit critical for a number of tasks such as …
In the age of big data, uncertainty in data constantly grows with its volume, variety and velocity. Data is noisy, biased and error-prone. Compounding the …
The analysis of the statistical properties of data is a core goal in computer science. The challenges encountered in this task have evolved through time …
Background: Prognostic prediction has empirically proven to be a highly effective paradigm that is radically reshaping public health, clinical medicine, and healthcare as a domain. …
This dissertation tackles demand estimation in a big-data context from multiple perspectives. Chapter 1 (“Model Selection and Estimation with the Constrained Adaptive Elastic Net”) proposes …
Over the last decade, Python emerged as the language of choice for data processing and model building. Yet, the developer productivity of Python comes at …
This thesis takes aim at two directions. The first direction involves setting the foundations for a new type of data-driven scientific computing, essentially creating a …
Causal mediation analysis is widely applied in the social, economic and biological sciences to assess the causal mechanism between three variables: a treatment, an intermediate …
The widespread popularity of visual data exploration tools has empowered domain experts in a broad range of fields to make data-driven decisions. However, a key …