Oct 1, 2018

An Interview with Richard Samworth, COPSS Presidents’ Award winner

Richard J. Samworth

 

Richard J. Samworth of the University of Cambridge is the recipient of the 2018 Presidents’ Award. This award is presented annually to a young member of one of the participating societies of COPSS in recognition of outstanding contributions to the profession of statistics. The award citation recognized Samworth “for fundamental contributions to nonparametric inference under shape constraints, nonparametric classification, high-dimensional variable selection and change point estimation; for many substantial contributions to the profession including editorial service, extensive service to statistical societies; and for the training and mentoring of junior researchers”.

Professor Samworth graciously agreed to be interviewed by Wendy Lou, Secretary/Treasurer of COPSS:

What was your first reaction to winning the prestigious COPSS Presidents’ Award?

I was so shocked that, looking back, I’m relieved no bad words slipped out! Obviously, I was delighted: it’s really a great honour for me to join such a distinguished list of statisticians.

Which part of your job do you like the most?

The time I spend doing research with my PhD students and post-docs is what I enjoy most. They make me a better researcher and frequently amaze me with what they are able to accomplish. I love seeing them develop and grow in confidence.

What advice would you give to young people who are entering the profession as PhD students and assistant professors at this time?

First, congratulations! It’s a great time to be entering the profession and it’s wonderful to see the importance of Statistics finally being recognised. For PhD students, the choice of advisor is probably the most important decision. Different people look for different things, but I’d say that ideally, you want a strong researcher who will take an active interest in your research and development. For assistant professors, the main challenge is often to maintain your research momentum and enhance your visibility while also getting up to speed with the other duties of the role. Senior colleagues can often be a great source of advice; personally, I feel I benefited enormously from the travel opportunities that arose at that stage.

Who are your most significant mentors, and how did/do they impact your career?

My PhD supervisor, Alastair Young, helped greatly at the beginning and even now we enjoy going out for an occasional curry. Alastair introduced me to Peter Hall, who I visited twice at the Australian National University in Canberra and once at the University of Melbourne. As everyone knows, Peter was a remarkable person; we wrote two papers together and I learnt a great deal from working with him. More recently, Peter Bühlmann, Ray Carroll, Lutz Dümbgen, Jianqing Fan and Jon Wellner are just some of the many people who have inspired me and supported my career.

Why were you drawn to nonparametric inference? How did you start to work on shape-constrained estimation problems?

Like many statisticians, I often find myself questioning whether our assumptions are realistic, so I was very attracted to the flexibility of nonparametric methods. I first started thinking about shape-constrained estimation problems when Michael Stewart came to visit me in 2005. I became really excited about the prospect of having the best of both the nonparametric and parametric worlds: the modelling flexibility of an infinite-dimensional class, together with the potential to obtain estimation procedures that don’t require the choice of tuning parameters.

Anything else you will like to share about our profession?

Many people at the moment are rightly considering the position of Statistics within the brave new world of data science, and some are fearful that we may even become obsolete. I do think it’s important that we continue to ask what skills we need to acquire and teach in order to remain relevant, but overall I’m pretty optimistic about our future. My personal experience is that our skills are appreciated now more than ever.

Finally, what are your hobbies and interests beyond statistics?

Sport is really my first love. When I was younger I used to play a lot, particularly typically British sports like cricket, rugby, golf and football (soccer!). A rugby injury around 20 years ago put paid to that, though. These days, I still watch quite a bit when I can, and have fun giving various challenges to visitors. These can range from kneeling on a fit ball, to throwing juggling balls off the wall above a door and catching them behind your back as you walk through, to chipping a sponge ball with a golf club so that it clears one room but stops before reaching the end of the adjoining one. I’m sure they all sound completely crazy, but I like to think quite a lot of statisticians will be able to remember some good times attempting them!

 

A little (more) about Richard J. Samworth

Richard was born in Newport Pagnell, UK, and obtained his BA in Mathematics (1999), MMath (2000) and PhD in Statistics (2004) from the University of Cambridge. Following a Research Fellowship at St John’s College, Cambridge, he was appointed as Lecturer in Statistics in the Statistical Laboratory at the University of Cambridge in 2005, before being promoted to Reader (2010) and then Professor of Statistics (2013). In 2017, he became the Professor of Statistical Science, as well as the Director of the Statistical Laboratory. He remains a Fellow of St John’s College, is a Faculty Fellow at the Alan Turing Institute, and holds a Fellowship from the Engineering and Physical Sciences Research Council.

Richard’s main research interests are in developing methodology and theory in nonparametric and high-dimensional statistics. He has made particular contributions to log-concave density estimation, k-nearest neighbour methods for classification and entropy estimation, high-dimensional changepoint estimation and data perturbation methods (e.g. subsampling, random projections) for problems in high-dimensional inference such as variable selection or sparse Principal Component Analysis. He has also worked in various application areas, including cancer genetics, oceanography and archaeology.

Richard has served on the editorial boards of the Annals of Statistics, the Journal of the Royal Statistical Society Series B, the Journal of the American Statistical Association, Biometrika, Statistical Science, Statistica Sinica and the SIAM Journal on Mathematics of Data Science (SIMODS). He will begin a term as co-editor of the Annals of Statistics (with Ming Yuan) from 1 January 2019.

Prior to this latest award, Richard received the Royal Statistical Society’s Research Prize in 2008 and Guy Medal in Bronze in 2012; the Philip Leverhulme Prize in 2014 and the Adams Prize in 2017. He became an IMS Fellow in 2014, an ASA Fellow in 2015, and gave an IMS Medallion lecture at the IMS Annual Meeting in Vilnius in 2018.

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