Abstract Submission

Submission opened on Wednesday 11th December 2024

Submission has been EXTENDED and now closes at Midnight (23:59 GMT) Friday 14th March 2025

Notification of abstract acceptance will be by Friday 28th March 2025

Early-bird registration closes on Friday 18th April 2025 (23:59 BST)

POSTER ONLY EXTENSION

We have re-opened abstract submission for posters only. We will be reviewing them at regular intervals and will close the submission form on the registration deadline of Friday 23rd May 2025 (23:59 BST)

1. Present Your Work: Share your findings with an engaged and supportive audience.

2. Expand Your Network: Meet peers, mentors, and leaders in the field.

3. Boost Your Profile: Gain visibility and recognition for your contributions.

4. Presentation Prizes: Be in with the chance to win tickets to the Royal Statistical Society conference 2026 for best oral presentation and best poster. Prizes to be confirmed for flash talks.

5. Visit Liverpool!

1. Undergraduate and postgraduate students and early career professionals in statistics or related fields.

2. Researchers applying statistical methods in diverse areas, such as healthcare, data science, social sciences, finance, and beyond.

3. Anyone passionate about advancing statistical science.

Below are some abstract topic ideas. This is not an exhaustive list and is only given as a helping hand for those new to conferences and to illustrate the wide variety of topics we accept at YSM.

Medical Statistics

• Machine Learning in Personalised Medicine - Applications of predictive models in patient diagnosis and treatment

• Survival Analysis Techniques - Advancements in modelling time-to-event data

• Clinical Trials Design - Innovative approaches to adaptive trial designs or interim analyses

• Real-World Evidence Analysis - Statistical challenges in analysing large healthcare datasets

• Longitudinal Data Analysis in Healthcare - Handling missing data and correlation structures over time

Bayesian Statistics

• Bayesian Hierarchical Models in Action - Applications in multi-level and multi-source data

• Bayesian Neural Networks - Combining Bayesian inference with deep learning

• Model Comparison and Selection - Exploring Bayes factors and cross-validation techniques

• Uncertainty Quantification in Decision-Making - Case studies in medical or environmental policy

• Bayesian Methods for Sparse Data - Overcoming data limitations in challenging applications

• Nonparametric and Advanced Theory

Spatial Statistics

• Modelling Disease Outbreaks - Spatial modelling for tracking and predicting disease spread

• Geospatial Big Data Applications - Statistical methods for analysing satellite or GPS-based data

• Urban Planning and Spatial Data - Using spatial statistics to optimise city infrastructure

• Environmental Risk Assessment - Mapping pollution hotspots using spatial regression

• Bayesian Approaches to Spatial Data - Hierarchical modelling of geospatial phenomena

Environmental Statistics

• Climate Change Modelling - Statistical methods for projecting temperature or sea level trends

• Ecological Data Analysis - Advancements in species distribution modelling

• Statistical Approaches to Renewable Energy Optimisation - Modelling wind or solar energy output

• Monitoring and Mitigating Air Pollution - Statistical tools for real-time data

• Extreme Value Analysis in Environmental Data - Modelling rare and impactful events

Economic Statistics

• Time Series Analysis in Economic Forecasting - New methods for modelling inflation, GDP, or unemployment rates

• Big Data in Economics - Analysing transactional or online behaviour datasets

• Causal Inference in Policy Evaluation - Statistical tools for understanding economic policy impacts

• Behavioural Economics and Statistical Modelling - Quantifying decision-making biases

• Game Theory and Statistical Applications - Solving real-world economic challenges with statistical techniques

Forensic Statistics

• Probabilistic Methods in DNA Evidence - Interpreting statistical evidence in forensic cases

• Statistical Evaluation of Fingerprint Evidence - Quantifying the reliability of pattern recognition

• Bayesian Inference in Legal Decision-Making - Statistical frameworks for courtroom evidence

• Data Integrity and Fraud Detection - Using statistical models to detect anomalies

• Machine Learning in Forensic Analysis - Applications in image recognition or digital forensics

Education Statistics

• Statistical methods for analysing educational outcomes and learning processes

• Applications in assessment, curriculum evaluation, and studnet performance prediction

Genomic and Bioinformatics Statistics

• Statistical methods for analysing DNA, RNA, and protein sequence data

• Applications in gene expression studies and precision medicine

Actuarial and Financial Statistics

• Risk modelling for insurance, pensions, and financial plannign

• Applications in life expectancy prediction and financial risk management

Legal and Criminal Justice Statistics

• Quantitative analysis of crime trends and legal policies

• Applications in recidivism prediction and police resource allocation

Computation and Simulation-Based Statistics

• Techniquea like Monte Carlo simulations and bootstrapping

• Applications in high-performance comuting and algorithm testing

Social Statistics

• Techniques for studying social behaviour, demographics, and policy impacts

• Applications in sociology, anthropology, and public policy

Sports Statistics

• Performance analytics for athletes and teams

• Applications in game strategy, injury prevention, and fan engagement

Agricultural Statistics

• Analysis of crop yields, livestock production, and agricultural economics

• Applications in sustainable farming and food security

General Statistics

• Applications of Statistical Software - Novel techniques or case studies using popular statistical tools

• Statistics in Decision-Making - Case studies from real-world projects

• Data Ethics and Privacy - Handling sensitive data in various fields

• Innovative Teaching Methods in Statistics - Sharing experiences in teaching and learning statistics

• Personalised Application of Statistical Models - Showcasing creativity in applying statistics to unique domains

Emerging Statistics

• Ethical Challenges in Stastical Modelling - Bias, fairness, and responsible use of data

• Statistical Methods for Artifical Intelligence - Bridging traditional statistics and AI

• Reproducibility in Data Science - Best practices for ensuring robust and reproducible analyses

• Interactive Data Visualisation - Tools and methods for presenting complex datasets

• Open-Source Tools in Statistical Research - Case studies using R, Python, or other open-source platforms

We welcome abtracts for the following presentation formats, offering a variety of opportunities for attendees to share their work and engage with the conference community:

1. Oral Presentation (10 - 15 minutes)
   Oral presentations provide an opportunity for attendees to deliver a detailed overview of their research or project to an engaged audience. Each presentation will be followed by a brief Q&A session, allowing presenters to discuss their work in greater depth and receive valuable feedback from peers and experts. This format is ideal for those with significant findings or complex topics to share.

2. Poster Presentation
   The poster presentation format allows attendees to visually showcase their research through a professional, engaging poster displayed in a dedicated session. Presenters will have the chance to discuss their work with attendees in a more informal setting, facilitating in-depth conversations and networking. This format is perfect for presenting preliminary findings, work-in-progress, or exploratory studies.

3. Lightning Talk (3 minutes)
   Lightning talks are fast-paced, concise presentations designed to provide a snapshot of your research or project. Each presenter will have three minutes to capture the audience's attention and convey the key aspects of their work. This format is an excellent choice for those who are new to presenting or wish to share focused insights, with the potential to spark interest for further discussions during the conference.

Detailed guidance for the format of each presentation type will be provided with the abstract notification email.

Please read these guidelines carefully before submitting an abstract

• There is a 2,500-character limit (including spaces), roughly 300-350 words, for the submitted abstract.

• The title should be clear and accurately reflect the content of the abstract.

• Abstracts should include headers of Background, Methods, Results, and Conclusions.

• Abstracts should contain text only - you will not be allowed to upload figures or tables on the submission form.

• If not all results are available at the time of abstract submission, an outline of the analysis protocol and some speculation of the results will also be considered.

• The presenting author is expected to have registered by the early-bird deadline. If they do not do so, they risk losing their presentation slot. The early-bird deadline will be after abstract outcomes are notified.

• The presenting authors are expected to attend the conference and present their abstracts. If they are not planning on attending both days, this can be indicated on the abstract submission form.

• The corresponding author is required to ensure that all co-authors are aware of the abstract content before submission and pass on the Organising Committee's decision.

• All abstracts must be in English with accurate grammar and spelling of a quality suitable for publication.

• All submitted abstracts will be reviewed anonymously by the Organising Committee and consider originality, clarity, and relevance to the conference. 

• Notification regarding status (i.e. acceptance & format) will be sent to the corresponding author once the review process is complete.