UQ-UZH Public Lecture: A Toolbox for Human-AI Collaboration in Lifespan Health Analysis

Join us at UQ Brisbane City for a Public Lecture, held as part of the UQ-UZH Symposium, co-hosted by The University of Queensland (UQ) and the University of Zurich (UZH).

A Toolbox for Human-AI Collaboration in Lifespan Health Analysis

Physiological time series data holds considerable promise for advancing the understanding of health and aging. However, transitioning from raw signals to analytically ready data remains a complex and often ad-hoc process. In this presentation, PhD candidate Gabriela Morgenshtern introduces STAG (Statistical Timeseries Analysis Guide), a visual analytics system developed at the University of Zurich to facilitate transparent and reproducible preprocessing of sensor data for exploration and model training.

STAG enables clinical researchers to build, document, and share preprocessing workflows using a modular, low-code interface that records each transformation along with its underlying rationale. The system produces exportable Python scripts, structured insight templates, and graphical workflow documentation to promote collaboration and cross-study comparability.

Ms Morgenshtern will demonstrate STAG and reflect on how visual analytics can improve collaboration between humans and AI in sensor and broader time series analysis. The session will also explore how longevity research can benefit from more rigorous and reusable preprocessing practices.

Event details

Date: Tuesday 7 October 2025
Time: 5:15pm arrival (5:30pm start) — 6:30pm, followed by networking and refreshments
Venue: Room 0M08, Level 0M, 308 Queen Street, Brisbane City

Registrations are now closed. 

About the presenters

Gabriela Morgenshtern

Gabriela Morgenshtern is a DSI Excellence Fellow and PhD researcher at the University of Zurich, where she focuses on human–AI collaboration and the analysis of wearable sensor data in healthcare. Her work develops interactive systems that integrate human expertise into machine learning pipelines, with applications in clinical monitoring and model validation. She previously studied bioinformatics and computer science at the University of Toronto, where she was a DeepMind Scholar, and conducted research at the Vector Institute in collaboration with The Hospital for Sick Children. Her broader interest lies in designing intuitive user experiences that support effective validation and integration of machine learning into clinical workflows. 

Professor Gianluca Demartini

Professor Gianluca Demartini is a Professor in Data Science and an ARC Future Fellow at the University of Queensland, Australia. His main research interests include Information Retrieval, Semantic Web, and Human Computation. His research is currently funded by the Australian Research Council, the Swiss National Science Foundation, Meta, Google, and the Wikimedia Foundation. He received Best Paper Awards at the ACM SIGIR International Conference on the Theory of Information Retrieval (ICTIR) in 2023, AAAI Conference on Human Computation and Crowdsourcing (HCOMP) in 2018, at the European Conference on Information Retrieval (ECIR) in 2016 and 2020, and the Best Demo award at the International Semantic Web Conference (ISWC) in 2011. He has published more than 200 peer-reviewed scientific publications, is an ACM Senior Member, ACM Distinguished Speaker, and a TEDx speaker.

This is a UQ sustainable event