Data Science – Demystified!

Hao NaiBy Hao Ni (@Hello19860630). Hao currently works as a senior postdoctoral fellow at Oxford-Man Institute of Quantitative Finance. Her research interest is to model the evolution of complex systems that are impacted by noise using the theory of rough path and its applications. In today’s world, we are increasingly exposed to novel terms such as ‘big data’, ‘artificial intelligence’, and ‘computer board game grandmasters’. During her presentation at the Oxford Soapbox Science event, Hao will touch on these themes by introducing her research on modelling the effects of data streams, and give some demonstrative examples to show the performance of her algorithm.


In mathematics, there are only absolute trues and falses, everything is clear-cut, and there is no ambiguity. The “good” mathematical objects stem out of the abstraction of realities. To me, these are the mystical wonders of the mathematical world.

Appealed by its natural beauty and elegance, I have enjoyed learning and working with mathematics from a very young age. I have been very fortunate to be able to pursue my interests in this area; having completed my undergraduate studies in mathematics in China and Germany, I went on to work with Professor Terry Lyons at Oxford, first as a doctorate student, then as a postdoctoral researcher. Starting this fall, I will be based at University College London, working in my capacity as a senior lecturer in financial mathematics and fellow of the Alan Turing Institute for data science.

I have worked on various research themes such as stochastic analysis, machine learning and financial mathematics during my time at Oxford.

Although I have a strong passion for theoretical mathematics, I also enjoy working in the applied field. Having completed a masters degree in Computational and Mathematical finance at Oxford, I interned briefly in the financial industry. My PhD work was mostly theoretical and focused on the rough paths theory, a branch of stochastic analysis; in the final year of my doctorate, I worked on linking this theortical work with regression and develop a general methodology to model the effects of data streams. I have continued my work in this area to this day and as a result, gained some research experience in machine learning and statistics. I believe the development of machine learning or artificial intelligence has traditionally focused more on the engineering side, which has led to huge successes in various domains, such as image recognition and robotics. But it is yet unclear why those methods were so successful. I believe mathematics can offer an answer to this question, and provide a solid theoritical foundation to data science as a whole.

Since last September, I have worked on change-point detection in financial time series, and collaborated with a number of commercial partners such as the Man Group, and colleagues from the departments of mathematics and engineering at Oxford. I have enjoyed communicating with people from different research backgrounds, which broadens my knowledge and brings new perspectives into scope. I have been as a member of Oxford-Man Institute for Quantitative Finance for over six years; and I deeply appreciate the excellent opportunities this interdisciplinary institute offered in meeting with people from different backgrounds.

Outside of work, I enjoy traveling, fine art, and food tasting. I am grateful that I am generously supported in life by my parents and loving friends, who have given me lots of courage and care. In my professional life, I have had great mentors, colleagues and collaborators. To me, the stochastic analysis group at Oxford is like a family.

Starting from a young age, I have felt obliged to make a positive impact on our society by helping others. This is my main reason for wishing to share my research experience and thoughts at Soapbox. It has never occurred to me that there would be any conflict between being a scientist and a woman at the same time; instead it defines who I am and makes me feel special and proud. From my own personal experience, the most important thing in research is to have an open mind to new ideas, and be curious as a child. Scientific research is not always straightforward, which can often bring stress to people; there is no guarantee that hardworking researchers can ultimately achieve their research goals. But if one is determined to do research, one should enjoy the process as a whole rather than focusing only on achieving the end goals.

Lastly I would hope a life that is defined by Bertrand Russell’s famously stated Three Passions, which I would like to quote to end this mini-blog: “Three passions, simple but overwhelmingly strong, have governed my life: the longing for love, the search for knowledge, and unbearable pity for the suffering of mankind.


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