Thursday 14 October 2021
9.45am - 5.00pm
The Department of Statistics is one of the world's leading centers of quantitative methods in the social sciences and has long been home to some of the world's most famous and innovative statisticians
This Open Day is designed for aspiring PhD Statistics students who are keen to formulate authentic, cutting-edge research in Data Science, Probability in Finance and Insurance, Social Statistics, and Time Series and Statistical Learning. Academics from the Department will offer useful insights through their research talks, followed by one to one sessions and social activities during the day.
You can book sessions to suit your interests. You will also have a chance to book one-to-one sessions with your preferred academic mentors to help identify your specific needs, interests and requirements for your application.
Welcome and PhD Programme overview (9.45am - 10.15am)
Please note these talks will run parallel to each other. Each talk will run for 15 mins. These talks will provide a high-level overview of the programme and current research.
Track 1: Data Science - chaired by Milan Vojnovic
Track 2: Probability and Finance - chaired by Kostas Kardaras
- Yufei Zhang - Model-based and model-free methods for stochastic control problems
- Erik Baurdoux - Stochastic processes and optimal stopping
- Andreas Søjmark - Interacting particle systems and weak convergence in probability and finance
- Umut Cetin – Markovian tools for learning in equilibrium for financial markets
- Kostas Kardaras - Portfolio theory and aribitrage
- Daniela Escobar - Risk management with applications in insurance and finance
Track 3: Social Statistics - chaired by Yunxiao Chen
Track 4: Statistical Learning and Time Series - chaired by Qiwei Yao
- Piotr Fryzlewicz, Non-stationary time series: change, uncertainty, causality and machine learning
- Yining Chen, Beyond parametric models: an introduction to shape-constrained estimation
- Tengyao Wang, Sparse structure identification in high-dimensional data
- Clifford Lam, High dimensional data analysis in financial econometrics: tensor time series, high frequency data analysis and spatial econometrics
- Xinghao Qiao, Functional data analysis: high-dimensional time series, classification and inference
- Qiwei Yao, Complex time series analysis: high-dimensional time series, spatio-temporal modelling, and dynamic networks
Conference style research talks, inclusive of presentations and overview of teaching and research activities. Attendees are welcome to join any seminars. Seminars are concurrent to your one-to-one meetings.
Data Science (1.00pm - 2.00pm)
- Milan Vojnovic - Overview of the group
- Chengchun Shi - Does the Markov Decision process fit the data: testing for the Markov property in sequential decision making
- Zoltan Szabo - Distribution regression and beyond
Probability and Finance (2.00pm - 3.00pm)
- Yufei Zhang - From stochastic control to machine learning and back
- Andreas Søjmark - Systemic risk: from exogeneous correlation to endogenous contagion
Social Statistics (3.00pm - 4.00pm)
- Yunxiao Chen - Overview of the group
- Yunxiao Chen - Statistical methods for detecting cheating in educational tests
- Camilo Cardenas-Hurtado - A flexible class of latent variable models
Time Series and Statistical Learning (4.00pm - 5.00pm)
- Clifford Lam - Rank determination for tensor factor models using correlation analysis
- Piotr Fryzlewicz - Narrowest significance pursuit: inference for multiple change-points in linear models
One-to-one meetings will be held between the Department faculty and prospective students. Meetings will have a duration of 25 minutes.
A list of our faculty members can be found here.
More information on signing up to these meetings will be provided to registered participants nearer the time.