Abstract:
Artificial Intelligence (AI) is transforming the healthcare landscape, enabling innovative solutions to complex challenges. In this seminar, we explore two key applications of AI in healthcare: EEG/MEG-based brain-computer interfacing (BCI) and computer vision for skin cancer detection. The first part of the talk will focus on adaptive learning techniques in BCIs, which address the non-stationarity of EEG and MEG signals. By leveraging AI-driven adaptive models, we can enhance brain signal interpretation, improving communication systems and neurorehabilitation technologies for individuals with disabilities. The second part will discuss the use of computer vision techniques, combined with metadata fusion (including C4C risk factors) for early skin cancer detection, and compare our results against the 7PCL and William Score. This approach integrates image analysis with patient data to create more accurate and reliable diagnostic tools, addressing current limitations in skin cancer screening. This seminar highlights how AI can drive significant advancements in patient care, fostering innovations that support more accurate diagnoses and effective treatments in both neurological and oncological domains.

Bio:
Dr Haider Raza (SMIEE, FHEA) is an Indian-born British Computer Scientist currently a Senior Lecturer (Associate Professor) in Artificial Intelligence at the University of Essex, UK and a founder of Sensiwise AI Limited. Driven by a passion for advancing knowledge, he pursued a PhD in Computer Science at the University of Ulster, U.K., focusing on "Adaptive learning for modelling non-stationarity in EEG-based brain-computer interfacing”. Dr Raza has held notable positions in academia and research. Starting as a post-doctoral researcher at the University of Ulster, U.K., he later transitioned to Swansea University Medical School, U.K., as a postdoc research Officer specializing in Data Science. In 2017, he joined the University of Essex as a PostDoc Research Fellow and swiftly progressed to become a Lecturer in AI in 2020, attaining the position of Senior Lecturer in 2022. Dr Raza's research centers on healthcare advancement, particularly in developing diagnostic algorithms and treatment planning. His expertise spans machine learning (ML), computer vision, and eXplainable AI (xAI), focusing on enhancing decision-making processes, addressing non-stationary learning challenges, and propelling brain-computer interfacing (BCI) applications in healthcare, business, and environmental domains. His contributions to academia and research are noteworthy, securing significant research funding exceeding £3.3 million in the last 5 years. Dr Raza's research output is extensive, with publications in eminent international journals and conferences, solidifying his presence in the academic realm. Additionally, he takes on editorial roles in esteemed journals, showcasing his dedication to advancing scientific understanding and knowledge dissemination. Dr Haider Raza's impactful academic journey and pioneering research underscore his potential to elevate the field of Artificial Intelligence, promising a technologically advanced and socially beneficial future.