جست‌وجوی استاد و پژوهشگر

• Respiratory Medicine
• Chronic Obstructive Pulmonary Disease
• Dry Powder Inhaler Technology
• +۵ مورد دیگر

Iris van der Ham is an active Dutch researcher whose scholarship bridges respiratory medicine and biomedical engineering. Over the past five years she has co-authored six peer-reviewed articles that collectively investigate the optimisation of dry-powder inhaler use in COPD patients, the clinical and economic consequences of inhalation errors, and the fundamental behaviour of endothelial cells on micro-structured substrates. Her work is embedded in large international consortia, most notably the multi-country PIFotal study. Research Interests Respiratory medicine, with a focus on chronic obstructive pulmonary disease (COPD) Dry-powder inhaler (DPI) technology and technique optimisation Peak inspiratory flow assessment and its clinical implications Health-economic evaluation of COPD management Endothelial cell biology and cell–material interactions Across her recent publications, a clear trend emerges: translating technical aspects of inhaler performance—such as peak inspiratory flow and inhalation errors—into measurable impacts on patient health status, exacerbation risk, and healthcare expenditure. Complementing this translational focus, her 2020 study in Heliyon delves into how topographical cues at the microscale direct endothelial-cell phenotype and contact guidance, underscoring her dual expertise in clinical respiratory research and biomedical engineering. Scientific Impact Although specific awards are not listed, the research has garnered significant scholarly attention: her papers have accrued between 13 and 20 Scopus citations each, been downloaded over 100 times per article in Pure repositories, and have been referenced in clinical guidelines and picked up by news outlets and social media platforms (Twitter, Facebook, Mendeley). Collaborations & Networks Van der Ham collaborates with an extensive international network spanning the Netherlands, Australia, Spain, Poland, Italy, the UK, and beyond. Frequent co-authors include J. W. H. Kocks, S. Bosnic-Anticevich, M. T. Leving, and J. C. de Sousa, among many others, reflecting her embeddedness in multi-disciplinary research initiatives.

• Dynamic Optimisation
• Optimisation under Uncertainty
• Combinatorial Optimisation
• +۷ مورد دیگر

Dr. Joan Alza Santos is an early-career Research Fellow at the School of Computing, Engineering, and Technology within Robert Gordon University (RGU). She is affiliated with the Complex Optimisation Research Group and contributes to RGU's research themes in "Environment, Energy & Sustainability" and "Living in a Digital World." Her work bridges academic research in dynamic optimization with practical applications in sustainable logistics and other real-world domains. Dr. Alza Santos completed her educational journey with: BSc (Hons) in Computer Engineering from Universidad del País Vasco (University of the Basque Country), 2013-2017 Postgraduate Certificate from Robert Gordon University, 2018-2021 PhD in Computing from Robert Gordon University, completed in January 2025 with no corrections required - a rare distinction Her research focuses on addressing fundamental challenges in dynamic optimization. Dr. Alza Santos has made significant contributions to the field through three key innovations: developing a fitness landscape rotation framework for dynamic benchmarking, introducing the concept of "elusivity" to quantify algorithmic adaptability over complete restart, and creating methods for generating realistic synthetic instances from real-world logistic data. Her work aims to bridge the gap between academic research and practical applications, particularly in sustainable logistics where optimization under uncertainty is critical. Dr. Alza Santos's publication record shows a consistent focus on dynamic optimization problems, particularly in combinatorial spaces. Her research trajectory demonstrates progression from theoretical foundations of dynamic permutation problems to increasingly practical applications, culminating in methods for generating realistic benchmarks from real-world data. A notable trend in her work is the development of metrics like "elusivity" that provide quantitative ways to evaluate the true adaptive challenge in dynamic optimization problems, moving beyond simplistic representations of dynamism. Her scientific recognition includes: Membership in the International Graduate Student Research Cohort (2024) Presentation at the Arctic Circle Assembly (2024) PhD defense with no corrections required (2025) - noted as a rare distinction As an early-career researcher, Dr. Alza Santos actively supervises research projects and serves as a Demonstrator for "Applied Data Science" and "Data Visualisation" modules. Her industrial collaborations span multiple sectors including energy, transportation, and environmental sustainability. She has worked on projects evaluating offshore wind farm impacts, developing visualization tools for fleet management, simulating transportation demand, optimizing cargo transportation, creating VR flooding simulations, reviewing childhood obesity data, and developing predictive maintenance platforms for the oil and gas industry. Dr. Alza Santos leads research within the Complex Optimisation Research Group at RGU, where she continues to develop innovative approaches to dynamic optimization problems. Her current work focuses on applying simulation-optimization techniques to address real-world challenges, particularly in sustainable logistics. She is actively seeking new collaboration opportunities with both academic researchers and industry partners to expand the impact of her work on society and the economy.

Sarah Immanuelمشاهده پروفایل

مدرس ارشد

• Biomedical Signal Processing
• Sleep Disorder Diagnostics
• Machine Learning for Healthcare
• +۵ مورد دیگر

Sarah Immanuel is a Senior Lecturer in the Business and Hospitality vertical at Torrens University, specializing in Data Management and Data Analytics. She directs teaching, research, and subject coordination within the Centre for Artificial Intelligence Research and Optimisation (AIRO), leveraging her 23+ years of academic experience across Australian and international institutions. Her educational background includes: Bachelor of Electrical and Electronics Engineering from Bharathiar University Master of Applied Electronics Engineering from Bharathiar University PhD in Biomedical Engineering from The University of Adelaide (dissertation: Polysomnographic signal processing for advanced diagnostics of paediatric sleep disordered breathing) Immanuel's research focuses on biomedical signal processing applications for sleep disorders and clinical diagnostics. She develops machine learning models for disease prediction in sleep disorders, mental health, and cardiovascular conditions, while creating data analytics platforms for healthcare decision-making. Her work integrates Signal and Image Processing with AI to address Digitally Enhanced Living challenges, particularly for elderly populations through ARC Industry Transformation Research Hub projects at Flinders University. Analysis of her 27 research outputs reveals consistent focus on cardiorespiratory dynamics, with recent publications (2023-2024) emphasizing transvenous phrenic nerve stimulation for central sleep apnea, heart rate variability biomarkers for stress/cognitive decline, and machine learning applications for surgical candidate prediction. Her fingerprint shows dominant themes in Central Sleep Apnea (100%), Transvenous Phrenic Nerve Stimulation (100%), and Polysomnography (60%). As an active PhD supervisor, she mentors students in cardiorespiratory signal processing and machine learning for clinical applications. Her research has generated significant community impact through the ARC Hub project on elderly care technologies. Immanuel maintains active research collaborations through Flinders University's Academic status position and contributes to healthcare innovation via the AIRO center's data-driven platforms.