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All times shown in AEST (UTC+10). JSON.

Ballroom 1 Data & AI Ballroom 2 Scientific Python Ballroom 3 Education

12:20 PM–12:50 PM

Who_Dunnit.xlsx – Teaching Python through Data Investigation
Renee Noble

10:00 AM–10:30 AM

The Duck and the DataFrame: A Data Engineer’s Journey with DuckDB
Ankur Jain

10:00 AM–10:30 AM

Going with the flow? Apache Airflow for operational-quality scientific workflows
Patrick Sunter, Michael Pegios, and Daehyok Shin

11:40 AM–12:10 PM

On the Fly and On the Flight: Scientific Data Analysis Beyond the Beamline
Melanie Hampel

12:20 PM–12:50 PM

From Matlab to Lambda: Transforming Structural Engineering Research Tools
Brooks Smith

12:20 PM–12:50 PM

Hierarchical Clustering: Finding the awkward reunions
Neha

11:00 AM–11:30 AM

Modernizing Legacy: Wrapping a 25+ Year Computational Fluid Dynamics Codebase
Tishampati Dhar and Duy Nguyen

1:50 PM–2:20 PM

Taking Back the Streets: NaviLens and the Fight for Open Navigation
Stephen Tierney

9:00 AM–9:20 AM

Scientific Python Track Opening
Genevieve Buckley, Kai Striega, Charles Turner, and Jo Basevi

11:00 AM–11:30 AM

A case study on building our first LLM feature – how to balance speed + quality
Vivek Katial

3:10 PM–3:40 PM

What’s in a Name? – Fuzzy Matching Techniques for Proper Nouns
Renee Noble

4:10 PM–5:20 PM

Student Showcase
Amanda J Hogan, Nicky Ringland, and Alison Wong

2:30 PM–3:00 PM

Object-Oriented Oncology: Making Sense of Complex Patient Journeys
Georgie Kennedy and Ghazaleh Niknam

4:50 PM–5:20 PM

High altitude balloon imagery decoding in the browser with C, JS, and Python
Michaela Wheeler

2:30 PM–3:00 PM

Beyond Vibes: Building Evals for Generative AI
Dilpreet Singh

9:20 AM–9:50 AM

Life Beyond Pandas: Workflows with DuckDB, Daft, Polars, and Datafusion
Mimoune DJOUALLAH

3:10 PM–3:40 PM

Takeaways from teaching Python in college
Vladimir Roudakov

11:40 AM–12:10 PM

Capturing Flags with Microbits
Edwin Griffin

3:10 PM–3:40 PM

Building an electricity market model from scratch
Dr Jack Simpson

10:00 AM–10:30 AM

The Lab - Lessons from an Autism-Inclusive Learning Space
Maddie Mackey

9:20 AM–9:50 AM

Big Brains, Small Targets: Whole-Brain Image Analysis with Python
Ishrat Zaman

4:10 PM–4:40 PM

PyEarthTools: Machine learning for Earth system science
Tennessee Leeuwenburg

9:20 AM–9:50 AM

Why Teach the "Why"?
Jack Reichelt

11:40 AM–12:10 PM

Needle in the Haystack: Applied ML for Inspections of Power Infrastructure
Boaz Ash

1:50 PM–2:20 PM

Time Series Analysis in Python: Easy Tools for Scientific Insight
Muhammad Sakib Khan Inan and Rubaiath E Ulfath

9:00 AM–9:20 AM

Data & AI Track Opening
Nic Crouch and Jack Skinner

5:20 PM–5:40 PM

Education Track Closing
Amanda J Hogan, Nicky Ringland, and Alison Wong

2:30 PM–3:00 PM

Data Structures: A learning journey
Izy Hogan

9:00 AM–9:20 AM

Education Track Opening
Amanda J Hogan, Nicky Ringland, and Alison Wong

4:10 PM–4:40 PM

Scaling Security Anomaly Detection in Enterprise Knowledge Base with Dask
Isabelle De Backer

11:00 AM–11:30 AM

Catching them all: teaching fundamental OOP concepts with Pokemon
Sujatha

1:50 PM–2:20 PM

The Streamlit Experiment: building web dashboards with Yr 10-12
Geoff Matheson

4:50 PM–5:20 PM

AI for Good: Using Responsible AI to Drive Social Impact and Inclusion
Dr.Swapnilsony Singh

5:20 PM–5:40 PM

Scientific Python Track Closing
Genevieve Buckley, Kai Striega, Charles Turner, and Jo Basevi

5:20 PM–5:40 PM

Data & AI Track Closing
Nic Crouch and Jack Skinner
Welcome reception
9:00 AM 9:30 AM 10:00 AM 10:30 AM 11:00 AM 11:30 AM 12:00 PM 12:30 PM 1:00 PM 1:30 PM 2:00 PM 2:30 PM 3:00 PM 3:30 PM 4:00 PM 4:30 PM 5:00 PM 5:30 PM 6:00 PM