Dr Haider has a track record of scientific research and innovations focused on multimodal information processing, ambient assisted living technologies, digital biomarkers for mental health monitoring, machine learning methods, feature selection and extraction methods, social signal processing, video intelligence and affective computing. He has experience in managing research, having led work packages in research projects and endorsed by TechNation UK as an internationally recognized leader in digital technologies. His PhD thesis title is "Improving Social Intelligence of Machines in the Context of Public Speaking Situations" and is fully funded by EU FP7 (European Commission 7th framework programme) and TCD studentship awards. He has presented his work in the top venues of speech and multimodal information processing. Most of his research is funded by European Commission, and he had worked on two EU projects, namely SAAM and METALOGUE. He has also worked on industrial research projects focused on video intelligence in collaboration with Huawei. He was on an industrial secondment funded by UKRI-BBSRC recently and investigated the potential of biological biomarkers for the automatic diagnosis and progression of Dementia. Currently, he is working as Research Associate in Machine Learning at the School of Engineering.