AIML 3-minute thesis competition (Practice Round, Batch 1)

Date: 19th November 2021
Time: 14:00-16:00
Location: Hybrid Meeting (G.07)
Talks

Title: Euler the Mathemagician
Speaker: Imogen Morris
Abstract:
Euler was infamous for using ‘impossible’ numbers that are smaller than any other number, yet bigger than zero, and using his almost magical intuition to arrive at the right answer, like a magician pulling a rabbit out of a hat. Using a proof-assistant, and a modern theory of infinitely-small numbers, I aim to show the real magic was in Euler’s reasoning.

Title: The silent epidemic: Role of networks in tobacco control
Speaker: Adarsh Prabhakaran
Abstract:
Smoking behaviour can spread in a population through social ties. We are trying to model the spread of smoking and develop strategies to control the spread using an Agent-based model on a network.

Title: Explaining machine answers to human questions
Speaker: Jorge Gaete-Villegas
Abstract:
The field of artificial intelligence has accomplished much in recent years and every day its applications are more embedded into our daily life. But can we really trust these systems and their predictions? Are we willing to put in the hands of a machine things like the healthcare of our loved ones? In this talk I explain our quest to provide a bridge between AI and decision makers via explanations.

Title: Uncertain events and Business Process Management
Speaker: Jiawei Zheng
Abstract:
Deviations are ubiquitous in our world, such as machine malfunction in the context of manufacturing and falling over in daily life. How to detect these deviations and provide effective interventions such as robot support when people fall to avoid further adverse effects is the main objective of my research.

Title: Human Action Recognition
Speaker: Zonglin Ji
Abstract:
Recognising human actions from a video has been considered a challenging task as it requires identifications of both spatial and temporal features to consider. In this project, I have built a classification model using deep learning that can distinguish and classify 100 plus different actions in daily life from a human skeleton-based dataset.

Title: Prove that your car won’t crash
Speaker: Ramon Mir Fernández
Abstract:
In this talk, we explain how you can convince your computer (and yourself) that an autonomous system will behave safely.