Saddam Abbasi, Pakistan: Statistics PhD student
"I like the cultural diversity here"
Saddam Abbasi’s research aims to improve process monitoring techniques by focusing on the most important statistical process control tool – control charts. Control-chart procedures detect unusual variations in process parameters. Although they first emerged in manufacturing, control charts have since been applied in fields as diverse as nuclear engineering, health care and education.
Find out about Saddam's study and his Auckland lifestyle
Ke (Kim) Nan, China: Statistics PhD student
“A good reputation here and overseas”
The potential of New Zealand’s wind energy to power the nation drives Ke (Kim) Nan’s doctoral research. By studying the statistics generated by the New Zealand wind industry, and looking at economics, the environmental impact, and the country’s current power generation, he hopes to help build a better understanding about how wind-generated power could become a viable option for the future, both environmentally and economically.
Read more about Kim and his study
Lisa Chen, China: Statistics PhD student
"I can't get a better supervisor or more interesting research topic"
Lisa is working on algorithms to find the best decisions users can make in various queueing situations – but particularly when travelling. She focuses on individual selfish routing choice in a class of queueing model and studies its effect upon overall system performance.
You can see it this way, she says: “If everybody decides to take a private car to work by assuming that their travel time will be shorter than via public transport, the actual travel time, in terms of an overall average, is usually longer than expected because the motorways are consequently overloaded – and that’s how we have daily traffic jams in Auckland. In this case, individual (selfish) choice has a negative impact on the overall system performance.”
Find out more about Lisa and her study
Xinxing (Joyce) Li, China: Statistics PhD student
“Researchers and research topics were very important in my decision”
Xinxing’s research is driven by computational problems arising in the use of the univariate generalised hyperbolic distribution (GHyp) in statistical applications. In most cases, their solution requires advances in theory and methodology. Her research necessitates developing software in R, the free statistical computing and graphics tool developed at The University of Auckland in the 1990s and now used worldwide.
Find out why researchers and research topics were important to Joyce
Jared Tobin, Canada: Statistics PhD student
“Auckland is the best fit for me”
Jared Tobin is researching machine learning, an area of research at the crossroads of statistics and computer science that uses probability and computational savvy to solve hard prediction problems. In particular, his work focuses on better incorporating information about uncertainty into problems that use large amounts of data.
Machine learning techniques can be applied to fields as diverse as finance, ecology, computer vision, climatology, logistics, and speech recognition, Jared says. “Whether it's Facebook auto-recognising your friends' faces in pictures, or your phone auto-completing your texts, you can bet there is a machine learning algorithm somewhere doing all the work!”
Find out why Auckland was Jared's best fit
Jing Liu, China: Statistics PhD student
“I chose The University of Auckland simply because it is the best in New Zealand”
Jing Liu was 16 when he came to New Zealand to study at Hamilton Boy's High School. In the 11 years since, he has completed his undergraduate study at The University of Auckland and moved on to a doctorate.
Jing, seen here at Auckland Zoo with a tuatara, a native and endangered New Zealand reptile, started his PhD study by looking at genetic data as a way to capture the population size of endangered species; the real or effective size in terms of genetic variation can be significantly smaller than the counted population. But his focus has changed: “Later, I found out the idea has a greater impact on association studies for disease, so I have focused on that since.”
Find out more about Jing's study and lifestyle
Xu Xu (Demi) Wang, China: Statistics PhD student
“Choosing The University of Auckland means I also chose an amazing lifestyle”
Xu Xu (Demi) Wang’s research looks at multivariate nonparametric mixture models, which provide solutions to challenging real-world issues in cluster analysis, density estimation, discriminant analysis and random effects models.
Find out more about Xu Xu and living in Auckland
Tong Zhu, China: Statistics PhD student
“The reason I chose Auckland was my supervisor”
Tong’s research focuses on stochastic processes. For his thesis, entitled Optimal Control, Paradoxes and Phase Transitions in Stochastic Networks, he is exploring ideas and techniques from Markov random fields, statistical mechanics, dynamical systems, interacting particle systems, graph theory and applied probability.
Find out more about Tong and his life and study in Auckland
Chanatda Somchit, Thailand: Statistics PhD student
"This is a safe and secure destination for international students"
Chanatda, pictured here with supervisor Thomas Yee, is working on initial values for nonlinear regression and implementing new link functions for generalised linear models (GLMs). Nonlinear regressions are common in areas such as agriculture, biometry and chemistry, and GLMs are widely used in applied statistics. “The ones I am working on apply to binary responses – as in there are only two possible values, such as alive and dead – so the application areas are limitless.”
Read more about Chanatda and her life and study in Auckland
Shabnam Fani, Iran: Statistics PhD student
"A top-100 ranking was the most important factor for me"
Shabnam Fani’s research involves studying various problems that fall under the general heading of nonparametric survival analysis under shape restrictions. She is investigating various types of shape restrictions on a survival or hazard function, finding out how the corresponding survival or hazard models can be computed efficiently, analysing the properties of the fitted models, and examining their applications and performance using real-world problems.
Find out more about Shabnam's decision to study in the University of Auckland