By David Murphy
Ajay Jasra is a professor of applied mathematics and computational sciences who recently joined the KAUST CEMSE Division in July 2019. Jasra joined KAUST after holding tenured faculty positions at The National University of Singapore and Imperial College London where, in 2005, he completed his Ph.D. in statistics. Prior to joining the Division, he also held postdoctoral positions, mainly in statistics, at The University of Oxford and The University of Cambridge as well as the Institute of Statistical Mathematics in Tokyo, Japan.
The main drives of Jasra’s research can be summarized as the design, analysis, and application of stochastic algorithms for data analysis. In particular, in relation to the application of Monte Carlo algorithms for problems in Bayesian Statistics, uncertainty quantification, and computational finance. He has also worked on many applications, including computational biology, target tracking, finance, economics, and control engineering. His research also has real-world applications, such as stock market index predictions.
“For this type of prediction, one constructs a statistical or stochastic model which hopes to capture the real-life phenomenon. In practice, these models can be quite intricate, and they often lead to solutions that are not analytically tractable. That is to say, that one cannot return the ‘answer,’ e.g. a prediction of a stock index, using a simple mathematical formula which can be computed given the data. Often, one has to resort to numerical approximation schemes using probabilistic techniques, and this is where our work is done.
“In some cases, our work is to design new, efficient and scalable algorithms, which are mathematically understood, for real problems in finance or biology and health. In other cases, it is to provide [a] mathematical understanding of existing, so as to comprehend the utility of this given algorithm. In other cases, one would like to apply existing algorithms to real case studies, so as to understand a given data-generating mechanism.”
His reasons for joining KAUST are numerous, chief among them, the potential to pursue ‘blue skies’ research; research with a need to drive applications that are of significant interest to Saudi Arabia as a whole.
“This [KAUST] is a unique challenge, where one can do very good research, but at the same time, one must be mindful of the practical applications. The second [reason for joining] is the generous research funding and the associated environment that KAUST provides. I had visited the campus five times previously up until my appointment, and the dynamic environment I found on campus was one that I had not experienced for some years.
“This is a place where people really do care about what you are doing, and one can interact with world-class researchers who are often available. This makes the experience of coming to work more enjoyable (than it had been for a long time).
In a decade-long research career—which has been marked with 60 publications in the field of computational statistics and applied probability (receiving over 2,500 citations)—Professor Jasra has remained true his overarching aim as a researcher; chiefly, to attempt to work on research problems which he believes are interesting and of practical use.
“My research goals are very much similar to that of my entire career; to do the best possible research I can, which can hopefully be used in practice. There are specific projects I work on, for instance, the stochastic analysis of practical algorithms. However, I am a strong believer that if one wants to solve meaningful problems, then one must be prepared to sometimes take detours, to gain knowledge and experience.
“In my opinion, when it comes to your professional (and even personal) life; the main thing in life is to work hard and smartly, and good things can happen. Pick your battles and goals and work hard to achieve them.”