The Digital Futures team are hosting talks by The University of Manchester's new Turing Fellows for 2021-22.
Presenting at this event are Tingting Mu and Markel Vigo.
This will be an online event. To register, please visit the Eventbrite link opposite.
Tingting Mu is senior lecturer in Machine Learning in the department of Computer Science, and her research is focused on developing advanced mathematical modelling and large-scale optimisation techniques to (1) simulate human intelligence and (2) analyse real-world complex data.
Tingting's talk is titled 'Fundamentals and Applications of Representation Learning'.
Representation learning aims at extracting refined information from raw data and knowledge, and encoding it by data representation with low memory usage, which needs to be sufficiently accurate for further use in pattern recognition, prediction and exploration tasks. My core expertise is on the understanding and learning spaces that embed such data representations. In this short talk, I will share my current research landscapes, covering the theory and algorithm development, as well as the practical applications in other disciplines and industry.
Markel Vigo is a lecturer in Health Informatics, and his research looks at how individuals interact with data-intensive, complex and critical interactive systems such as medical dashboards and knowledge artefacts.
Markel's talk is titled 'Methods, Tools and Case Studies for User Interaction Modelling'.
User interaction analysis is key to understanding the interface between humans and interactive computing systems. Despite being an essential activity for digital phenotyping and user modelling purposes, the manipulation, enquiry and mining of interaction data is full of challenges.
Informed by case studies on online learning, knowledge acquisition and user interface evaluation, in this talk I'm going to: (1) introduce a set of tools to support hypothesis-driven and data-driven analysis; and (2) present some innovative data analysis pipelines that involve human decision-making.
