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Workshop on Detecting Anomalous Structures in Stream Settings, DASS Workshop 2025

Mon 22 Sept

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Lancaster University

Workshop on Detecting Anomalous Structures in Stream Settings, DASS Workshop 2025
Workshop on Detecting Anomalous Structures in Stream Settings, DASS Workshop 2025

Time & Location

22 Sept 2025, 11:00 BST – 25 Sept 2025, 14:00 BST

Lancaster University, Bailrigg, Lancaster LA1 4YW, UK

About the event

General

This workshop, which is taking place in the Postgraduate Statistics Centre (PSC) on will begin Monday, September 22nd 2025, and conclude on Thursday, September 25th 2025, will have the theme 'Detecting Anomalous Structure in Stream Settings'. This will be an event bringing together both early career and established researchers working in the area, together with practitioners, to share their latest work and help foster new collaborations.


Confirmed speakers include: 

  • Professor Yao Xie (ISyE)

  • Professor George Michailidis (UCLA)

  • Professor Olga Klopp (ESSEC)

  • Professor Tengyao Wang (LSE)

  • Professor Veronica Bowman (Paebbl)

and many more!


The full list of speakers can be found on the timetable below, along with on the abstracts and programme booklet attached.

Venue

The Workshop will take place in the Postgraduate Statistics Centre (PSC) at Lancaster University. The exact location of the PSC can be found here.


Accommodation

For a cheaper and convenient accommodation option there are a number of Lancaster campus rooms available for this workshop. To reserve one of these rooms for dates between September 21st and 25th, you can book following the link here. We recommend that you make your reservation as soon as possible, as the number of rooms is limited.


Otherwise, there are many other options available, here are some suggestions:


On campus
In town

Travel

By Bus

From the railway station: during University vacation periods (Monday-Saturday) the 4 and 4X bus services operate hourly from the station. The journey time is around 25 minutes. Taxis are also available at the station.


From the city centre (which is a 5 minute walk from the railway station): Lancaster Bus Station is situated on Damside Street in the city centre and most bus services also stop at Common Garden Street. We recommend using the Common Garden Street stop if coming from the train station. Service 1/1A provides a direct connection to the University every 10 minutes, Services 100, 4, 4X, 40, 41 and 42 also serve the University giving a total of 14 buses per hour from Monday to Saturday until 7pm. A less frequent service then runs daily until around midnight.


By Car

Leave the M6 at Junction 33, and head north along the A6 towards the city centre. You will pass through the village of Galgate, and the main university entrance is about 1.5 miles further on. If using an online route planner or satnav, the main University postcode is LA1 4YW.


Registration

Unfortunately, registration is now closed.


Speaker slides

Tengyao Wang, London School of Economics, Sparse change detection in high-dimensional linear regression.

Ines Wilms, Maastricht University, MLOps monitoring at scale for digital platforms.

Olga Klopp, ESSEC Business School, Change point detection in dynamic networks.

Per August Jarval Moen, University of Oslo, A grid-based methodology for online change point detection and possible extensions to anomaly detection.

Yao Xie, Georgia Institute of Technology, Online change point detection with unknown post-change parameters via online learning.

Guillem Rigaill, INRAE, Online multivariate change point detection: leveraging links with computational geometry.

Housen Li, University of Gottingen, Speed meets accuracy: Change point analysis in high-dimensional linear models.

Farida Enikeeva, University of Poitiers, Anomaly detection in high-dimensional vector autoregression.http://dependence.al

Song Liu, University of Bristol, High-dimensional differential parameter inference in exponential family using time score matching.

Mengchu Li, University of Birmingham, Robust mean change point testing in high-dimensional data with heavy tails.

George Michailids, UCLA, Change point estimation in panel data with temporal and cross-sectional dependence.


Contact

If you have any questions, please direct them to dass@lancaster.ac.uk.

Schedule

29 more items available

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