Guilherme Augusto Zagatti

I graduated in Economics and worked for a few years in government and industry with policy research. Since graduation and with the increasing digitization of society, larges amount of data in a variety of shape have become available for research driving both industry and academia demand for innovative thinking and cross-disciplinary skills. A PhD in data science became the obvious choice for me. The programme would allow me to improve my skills and develop social science research that leverages big data, thus opening the doors to an academic career.

NUS is consistently ranked as one of the top universities in the world and in Asia. My PhD programme is co-hosted by the Integrative Sciences and Engineering Programme (ISEP) and the Institute for Data Science (IDS) emphasizing cross-disciplinary research by providing a platform that allows me to easily reach different departments at the university. Apart from that, Singapore is pursuing the Smart Nation initiative with many policies focused on leveraging technology to better serve society and the economy. This is exactly the type of research that I am interested about pursuing.

PhD is more fast-paced than undergraduate education. Unlike undergraduate, you are not spoon-fed content. It is important to take ownership of your own work and develop a higher level of initiative and accountability. With that being said, NUS does provide a lot of support in the outset of the PhD programme which prepares the student for independent research during the rest of the programme. In the first year of my programme, I had the chance to meet different professors and work with two of them on small-scale research projects. These experiences helped me understand research and select my supervisor.

Society can be understood as the complex set of social relationships that humans build with one another in society. While we experience and navigate through social relationships on a daily basis, the presence of social relations can be very hard to measure from a researcher’s perspective. One of the most common approaches for capturing social relationships is through costly surveys. However, as society becomes increasingly digitized, it becomes possible to leverage the increasing volume of interaction data to investigate social relationships. In my research, I employ computational social science to develop methods for reconstructing networks from interaction data. My second objective is to investigate the effects that our networked life have on our socio-economic outcomes. For instance, previous work in this field has shown that students connected to well-connected students have better educational outcomes than those less connected. Can we find evidence of similar effects using large-scale data and in other contexts?

My first celebration of Chinese New Year with my lab co-workers was a special moment in my first year. A couple of us organized a hot pot. It was the perfect bonding experience. It is a good idea to balance study with social life while doing a PhD.

One of the highlights of my programme is the cross-disciplinary aspect which brings fresh ideas and new perspectives to the table. While I might not be able to follow graduate-level chemistry or biology, it is still valuable to learn how my fellow students conduct research. The challenges they face helps me to relate to my own experience.

On a practical level, I enjoy being allocated a work desk in the lab which helps me to integrate with other PhD students and researchers. Spontaneous encounters and the ability to bounce ideas is an important aspect of research.

The main challenge during the PhD is to work independently. While my lab provides a lot of opportunity to interact with other PhD students and researchers, at the end of the day you must work on your own towards your final thesis. To complete the programme within allocated time requires a lot of focus and discipline.