Dr Zulaikha currently serves as Senior Lecturer and Clinical Medical Physicist at the Clinical Oncology Department, UMMC. She previously worked as Medical Physicist in Hospital University of Science Malaysia (HUSM) for 3-years before joining UMMC in 2010. She received her PhD in Clinical Oncology Physics in 2021 from the Faculty of Medicine, University Malaya. As clinical physicist and a lecturer in a teaching hospital, she is responsible on producing high quality radiotherapy treatment planning for oncology patients; perform dose measurement and quality assurance check on radiotherapy modalities while being involved with various clinical improvement technique, research and academic teaching related to Medical Physics and Oncology services. Her main expertise and research covers all applications related to brachytherapy, stereotactic body radiotherapy, in vivo dosimetry, hybrid treatment planning and radiobiology of hypo-fractionated treatment, while being the author and co-author for number of publications related to her field of expertise.

Cardiovascular pharmacology focusing on the study of signal transduction pathways that mediate vasoconstriction and vasorelaxation. Techniques: Tissue/organ bath experiments, calcium assays, western blotting, toxicity assay using Caenorhabditis Elegans and metabolomics. 

Hema Subramaniam is a Senior Lecturer in the Department of Software Engineering, Faculty of Computer Science and Information Technology at Universiti Malaya. She earned her PhD in Software Engineering from Universiti Putra Malaysia (UPM) in 2016, following a Master of Computer Science (Software Engineering) from Universiti Selangor in 2010 and a BSc in Information Technology from the same institution in 2006. Her research focuses on software architecture and quality measurement, with an emphasis on reusability and real-time systems. Recently, she has expanded her work into mental health analytics, exploring anxiety prediction via slang analysis on social media platforms. She investigates how system architecture can support real-time processing and sentiment analysis using natural language processing (NLP) models tailored to regional slang, contributing to mood detection systems for early anxiety prediction. Additionally, she has worked on embedded software solutions for learning disabilities (LD) supported by a grant. Hema has published both software engineering and mental health analytics, with ongoing projects in slang-based mood detection, and social media-driven anxiety prediction. Currently, she supervises a group of Master’s students working on system architectures for scalable, real-time mood and anxiety detection applications under her guidance.