Sathya Bursic

Sathya Bursic

PhD in Computer Science
machine learning; reinforcement learning; deep learning; bayesian modelling;

About

20
Publications
11,686
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
173
Citations
Introduction
A computer science postdoc focusing on machine learning with a particular zeal for probabilistic modelling and Bayesian statistics. I'm passionate about research in affective computing, computer vision and NLP, as well as their potential applications. A computer science postdoc focusing on machine learning with a particular zeal for probabilistic modelling and Bayesian statistics. I'm passionate about research in affective computing, computer vision and NLP.

Publications

Publications (20)
Conference Paper
Full-text available
Active vision is critical for navigating complex, unstructured environments like agricultural fields, where oc-clusions, diverse scales, and unknown elements can obscure task-relevant information. This paper investigates the use of deep learning architectures to estimate information gain and expected loss in continuous, multidimensional observation...
Conference Paper
Full-text available
Human language interactions involve complex processes beyond pure information exchange, for example, actions aimed at influencing beliefs and behaviors within a communicative context. In this paper, we propose to investigate the dialogue understanding capabilities of large language models (LLMs), particularly in multi-party settings, where challeng...
Chapter
Full-text available
Artificial intelligence’s (AI) progress holds great promise in tackling pressing societal concerns such as health and climate. Large Language Models (LLM) and the derived chatbots, like ChatGPT, have highly improved the natural language processing capabilities of AI systems allowing them to process an unprecedented amount of unstructured data. Howe...
Preprint
Full-text available
Artificial intelligence's progress holds great promise in assisting society in addressing pressing societal issues. In particular Large Language Models (LLM) and the derived chatbots, like ChatGPT, have highly improved the natural language processing capabilities of AI systems allowing them to process an unprecedented amount of unstructured data. T...
Preprint
Full-text available
Educational chatbots come with a promise of interactive and personalized learning experiences, yet their development has been limited by the restricted free interaction capabilities of available platforms and the difficulty of encoding knowledge in a suitable format. Recent advances in language learning models with zero-shot learning capabilities,...
Chapter
We present a digital media literacy activity composed of (i) an educational talk and (ii) a game-based activity. The aim is to support teachers in developing learning activities to increase awareness of social media threats among students. Through this activity students directly experience phenomena like echo chambers and filter bubbles that can be...
Article
Full-text available
A core endeavour in current affective computing and social signal processing research is the construction of datasets embedding suitable ground truths to foster machine learning methods. This practice brings up hitherto overlooked intricacies. In this paper, we consider causal factors potentially arising when human raters evaluate the affect fluctu...
Article
Full-text available
Natural language processing and other areas of artificial intelligence have seen staggering progress in recent years, yet much of this is reported with reference to somewhat limited benchmark datasets. We see the deployment of these techniques in realistic use cases as the next step in this development. In particular, much progress is still needed...
Article
COVID-19 is a highly contagious disease that was first identified in 2019, and has since taken more than six million lives world wide till date, while also causing considerable economic, social, cultural and political turmoil. As a way to limit its spread, the World Health Organization and medical experts have advised properly wearing face masks, s...
Article
Full-text available
A principled approach to the analysis of eye movements for behavioural biometrics is laid down. The approach grounds in foraging theory, which provides a sound basis to capture the uniqueness of individual eye movement behaviour. We propose a composite Ornstein-Uhlenbeck process for quantifying the exploration/exploitation signature characterising...
Article
Full-text available
Social media have become an integral part of our lives, expanding our interlinking capabilities to new levels. There is plenty to be said about their positive effects. On the other hand, however, some serious negative implications of social media have been repeatedly highlighted in recent years, pointing at various threats to society and its more v...
Chapter
Full-text available
We present a simple, yet general method to detect fake videos displaying human subjects, generated via Deep Learning techniques. The method relies on gauging the complexity of heart rate dynamics as derived from the facial video streams through remote photoplethysmography (rPPG). Features analyzed have a clear semantics as to such physiological beh...
Chapter
Full-text available
In this work we address the problem of gender recognition from facial images acquired in the wild. This problem is particularly difficult due to the presence of variations in pose, ethnicity, age and image quality. Moreover, we consider the special case in which only a small sample size is available for the training phase. We rely on a feature repr...
Chapter
Full-text available
Computer systems have grown in complexity to the point where manual inspection of system behaviour for purposes of malfunction detection have become unfeasible. As these systems output voluminous logs of their activity, machine led analysis of them is a growing need with already several existing solutions. These largely depend on having hand-crafte...
Article
Full-text available
When automatic facial expression recognition is applied to video sequences of speaking subjects, the recognition accuracy has been noted to be lower than with video sequences of still subjects. This effect known as the speaking effect arises during spontaneous conversations, and along with the affective expressions the speech articulation process i...
Preprint
Full-text available
Computer systems have grown in complexity to the point where manual inspection of system behaviour for purposes of malfunction detection have become unfeasible. As these systems output voluminous logs of their activity, machine led analysis of them is a growing need with already several existing solutions. These largely depend on having hand-crafte...
Preprint
Full-text available
In this work we address the problem of gender recognition from facial images acquired in the wild. This problem is particularly difficult due to the presence of variations in pose, ethnicity, age and image quality. Moreover, we consider the special case in which only a small sample size is available for the training phase. We rely on a feature repr...

Network

Cited By