Programme
Programme
Day 1
09:00 — 09:30
Registration and welcome coffee
09:30 — 09:45
Opening remarks
09:45 — 10:45
The intersection of generative AI and statistics: Opportunities and challenges
10:45 — 11:15
Coffee break
11:15 — 11:45
Session 1: Foundations of statistics
Advancing statistical frontiers: Integrative analysis and deep learning in high-dimensional data science
11:45 — 12:15
Bayesian knockoff filter for FDR control
12:15 — 12:45
Toward robust and scalable Bayesian deep learning
12:45 — 14:00
Lunch break
14:00 — 14:30
Session 2: Emerging trends in AI and statistics
Exploring Bayesian structural equation modelling: Innovations and applications in medical and behavioral sciences
14:30 — 15:00
Unraveling complexity: Nonlinear time series and market volatility in financial data analysis
15:00 — 15:30
Unveiling genetic complexity: Fine mapping with h2-D2 Bayesian approach in multi-ancestry settings
15:30 — 16:00
Coffee break
16:00 — 17:00
Panel discussion
Bridging the gap: Integrating statistical and AI methods
17:00 — 17:15
Closing remarks for day one
Day 2
09:30 — 10:30
Bayesian inference and computational innovations: Advancing statistical machine learning in Biology
10:30 — 11:15
Coffee break
11:15 — 11:45
Session 3: Foundations of AI
11:45 — 12:15
Collaboration and evolution of foundation and specialised models
12:15 — 12:45
Integrating statistical modelling and computation: Innovations in bioinformatics, text mining, and social network analysis
12:45 — 14:00
Lunch break
14:00 — 14:30
Session 4: Case studies in industry
14:30 — 15:00
Machine learning and Bayesian approaches: Transforming empirical asset pricing in finance
15:00 — 15:30
From academia to industry: Bridging statistical innovation in healthcare and actuarial science
15:30 — 16:00
Coffee break
16:00 — 17:00
Panel discussion
Charting the path forward: Collaborative innovations and future directions
17:00 — 17:15
Closing remarks for day 2
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