Anastasia Semykina is a Professor of Economics and Deputy Dean (Research and Innovation) at RMIT University's School of Economics, Finance & Marketing. She holds a PhD from Michigan State University (2006) and previously served as Charles and Joan Haworth Professor of Economics at Florida State University. Her expertise spans theoretical and applied econometrics, with a focus on panel data models, missing data estimation, and their application in labor economics, education economics, transition economies, and economic psychology. She teaches advanced econometrics and microeconomics courses at both undergraduate and graduate levels. Research Interests: Theoretical and Applied Econometrics Labor Economics Economics of Education Transition Economies Economics and Psychology Health Economics Her recent publications address topics such as panel data methodologies, healthcare cost-effectiveness analysis, and educational policy evaluation. She is actively involved in supervising PhD and Master's research students in econometrics and applied economics.
Prof. Paul Stupple is a Professor of Medicinal Chemistry at Monash University, Australia, with over 20 years' experience in pharmaceutical industry and academia. He holds leadership roles at Canthera Discovery and manages the Australian Translational Medicinal Chemistry Facility. His expertise lies in small molecule drug discovery, particularly targeting cancer therapies and epigenetic regulators. Affiliations: Monash University, Faculty of Pharmacy and Pharmaceutical Sciences Canthera Discovery (Director, Medicinal Chemistry) Education: BA and DPhil in Chemistry from the University of Oxford (1992–1999). Early career at Pfizer as a medicinal chemistry leader, delivering 6 clinical candidates. Key contributions include: Licensing deals with Merck (2016) and Pfizer (2018) for preclinical projects Leading the Cancer Therapeutics CRC's medicinal chemistry program Research Interests: Small molecule drug discovery focused on histone acetyltransferase inhibitors, cancer therapeutics, and epigenetic modulation. Notable projects include development of KAT6A/B inhibitors for ER+ breast cancer and STING agonists for immunotherapy. Grants/Projects: Principal Investigator for major initiatives like MedChem Australia (2023–2028) and drug target identification platforms. Collaborates widely with institutions like WEHI and University of Sydney. Over 28 peer-reviewed publications spanning 1997–2025. Labs/Teams: Oversees the Australian Translational Medicinal Chemistry Facility, a key resource for drug discovery in Australia.
About Dr. Pegah Varamini Dr. Pegah Varamini is a Senior Lecturer in Pharmacy and Pharmacology at the Sydney Pharmacy School, University of Sydney, and a Casual Lecturer in Music Education at the Sydney Conservatorium of Music. She leads the Breast Cancer Targeting & Drug Delivery (BCTDD) Group, focusing on innovative drug delivery systems for Triple Negative Breast Cancer (TNBC). Her research integrates nanotechnology, targeted therapy, and translational medicine, supported by prestigious grants including the NBCF Fellowship (2016). Research & Education PharmD (Shiraz University of Medical Sciences) PhD in Pharmaceutical Sciences (University of Queensland) Second PhD in Music Education (University of Sydney Conservatorium of Music) Key Research Interests Her work centers on: Peptide-based targeting strategies using 'Trojan Horse' approaches for TNBC Development of nanomedicine for bone metastasis prevention Clinically relevant preclinical models for personalized breast cancer treatment Collaborations with international institutions (e.g., Harvard Medical School, University of Nantes) Teaching & Supervision Dr. Varamini coordinates Drug Design and Development (PCOL3012/3912) and supervises a multidisciplinary team of HDR students and postdoctoral researchers. Notable current students include PhD candidate Hany Ghaly and MPhil candidates Huimin Shao and Farhana Mollah. Awards & Recognition 2021 Equity Prize 2016 Top 25 Young Researchers of Australia and New Zealand 2018 Fresh Scientist of the Year Recipient of multiple grants totaling over AUD 2M Leadership & Outreach She co-chairs the Nanopharma cluster at Sydney Nano Institute and advises the WHO Global Breast Cancer Initiative. Her work has been featured in media outlets such as SBS Farsi News and NBCF publications.
Professor Robert McLaughlin is a faculty member in the School of Biomedicine at the University of Adelaide, affiliated with the Faculty of Health and Medical Sciences. He leads the Bioengineering Imaging Group and serves as Managing Director of the start-up Miniprobes. His research focuses on developing optical imaging technologies, including non-invasive tools for blood flow assessment and miniaturized imaging probes. He has secured over $14M in research grants and holds an h-index of 45 with 98 journal papers, 7 patents, and 2 book chapters. Prof. McLaughlin’s career includes roles at the University of Oxford and Siemens Medical Solutions, followed by academic leadership since 2007. His innovations span optical coherence tomography (OCT), fluorescence imaging, and dual-modality systems for clinical applications. Awards include the 2014 WA Innovator of the Year, 2015 Australian Innovation Challenge, and 2016 South Australian Premier’s Research Fellowship. His research emphasizes practical medical solutions, such as imaging needles for deep-tissue diagnostics and optical devices for real-time surgical monitoring. The Bioengineering Imaging Group collaborates with industry and academia to translate technologies into clinical practice.
Dr. Joseph Choi is a Clinical Lecturer and General Surgery Fellow at the University of Sydney's Westmead Clinical School, within the Discipline of Surgery under the Faculty of Medicine and Health. He holds academic qualifications including BSc(Adv), MBBS, MPhil, and FRACS. His clinical and research interests focus on surgical outcomes, colorectal surgery, endometriosis management, and minimally invasive techniques. Dr. Choi's research emphasizes surgical complications, anastomotic leak prediction, and emerging surgical technologies. He has contributed to over 30 peer-reviewed publications since 2011, with recent work addressing robotic surgery feasibility, Strongyloides stercoralis infections, and HER2 therapy outcomes in breast cancer. His academic profile includes collaborations with multidisciplinary teams across oncology, gastroenterology, and gynecology. No formal awards or grants are explicitly listed, though his prolific publication record reflects sustained scholarly activity.
Dr. Jannah Baker is a Research Fellow at the Sydney School of Public Health, University of Sydney. She holds a PhD in Statistics specializing in Bayesian spatiotemporal modelling of chronic diseases, alongside dual postgraduate diplomas in Public Health and Statistics. Her clinical background includes five years as a practicing physician. Her research focuses on cancer prevention (breast, endometrial, melanoma), spatiotemporal disease modeling, health economics, and clinical trial design. She has led projects on sepsis detection systems, diabetes management, and surgical outcomes analysis. Notable contributions include a seminal systematic review on fertility-sparing endometrial cancer treatments referenced in international guidelines. Jannah has attracted $6M+ in collaborative funding and oversees grants such as the 2023 NHMRC-funded ROADMAP trial and a Department of Health-funded study on pediatric sepsis management. Her work spans 50+ peer-reviewed articles across journals like Journal of Medical Internet Research and PLOS One . Professional activities include clinical trials statistics, health economics analysis, and implementation science lectures. She has mentored multiple research teams and maintains an ORCID profile (0000-0002-2208-6584).
Professor Arcot Sowmya is a distinguished academic at the University of New South Wales, serving as Professor in the School of Computer Science and Engineering. With a strong background in both computer science and mathematics, she has established herself as a leading researcher in machine learning and computer vision applications, particularly in medical imaging and diagnostics. Dr. Sowmya earned her PhD in Computer Science from the Indian Institute of Technology, Bombay, along with an MTech in Computer Science, MSc in Mathematics, and BSc in Mathematics from the same institution. Her academic journey has positioned her at the intersection of theoretical computer science and practical medical applications. Her research interests span multiple domains with a primary focus on Machine Learning for Computer Vision . She has made significant contributions to learning object models, feature extraction, segmentation, and recognition techniques. Her work extends into medical image analysis, computer-aided diagnostics, high-resolution remote sensing, and biomedical informatics. More recently, she has applied similar techniques to social sciences domains, developing improved forecasting models for genocide and politicide. Her earlier work also includes contributions to real-time, concurrent, and embedded systems. Analyzing her recent publications reveals a strong trend toward medical applications of computer vision and deep learning. Her work spans from OCT-based glaucoma diagnosis to tumor segmentation, lung disease detection, and breast cancer prognosis. She has successfully bridged computer science with clinical medicine, developing practical tools for disease diagnosis and prediction that incorporate explainable AI approaches. Professor Sowmya's collaborative approach is evident in her extensive publication record across multiple journals and conferences. She has worked with researchers from diverse fields including ophthalmology, oncology, neurology, and public health, demonstrating the interdisciplinary nature of her research. Her laboratory work focuses on developing robust deep learning architectures for medical image analysis, with particular attention to segmentation networks, transformer models, and multimodal data fusion techniques. Her team has developed specialized networks for lung segmentation, tumor detection, and disease classification that address specific challenges in medical imaging.
Associate Professor Ernest Ekpo is affiliated with the University of Sydney's Sydney School of Health Sciences, within the Discipline of Medical Imaging Sciences. He holds academic roles as a Scholarly Teaching Fellow and Co-Director of the Medical Image Optimisation and Perception Group (MIOPeG). He is also an Associate Editor of the Journal of Medical Imaging and Radiation Sciences and a member of the Sydney Southeast Asia Centre and Cancer Research Network. Education: Earned BSc (Hons) in Radiography/Sonography from the University of Calabar, Nigeria, and a PhD from the University of Sydney. His research focuses on breast density, cancer biomarkers, medical image perception, radiation dose optimization, and radiology education. He explores applications in low-resource settings and emerging technologies like AI for diagnostic accuracy. Research interests include breast cancer treatment outcomes, image-based phenotypes, and improving imaging pathways for acute abdominal pain. Key themes are Cancer and Medical Imaging, with an emphasis on Women's Health and Chronic Disease. His work combines clinical practice, public health strategies, and technological advancements to enhance diagnostic efficacy and reduce unnecessary procedures. Articles from 2021–2024 highlight his contributions in mammography optimization, radiographer training, and AI-driven diagnostic tools. Recent grants include a 2024 project on CT examination education and a 2023 initiative to streamline breast cancer screening pathways. His awards recognize peer review excellence, early-career teaching, and research leadership. He supervises multiple students investigating breast density biomarkers, imaging modalities for dense breasts, and radiation dose management. His educational efforts aim to improve radiographers' capabilities in identifying urgent findings across CT and X-ray modalities, leveraging blended learning approaches.
Dr. Jiang Qian is a Lecturer at the University of Sydney. He holds a PhD in Marketing from the University of Houston, a Master’s in Finance from Johns Hopkins University, and an undergraduate double major in Information Systems and Finance from the Southwestern University of Finance and Economics. His research focuses on leveraging quantitative models and machine learning techniques to extract insights from large-scale data in marketing and healthcare contexts, particularly in social media, online search, and healthcare markets. Current research supervision includes Jennifer Ye’s project on Audio Data Analytics: A New Dimension in Customer Service Excellence . Dr. Qian’s recent work spans AI applications in breast cancer detection, medical imaging analysis, and reinforcement learning for autonomous systems. His studies address challenges like AI model calibration, training data quality, and radiologist-AI collaboration in clinical settings. Notable contributions include analyzing video cover image impacts on advertisement engagement and exploring multiresolution techniques for medical imaging segmentation. His interdisciplinary approach bridges marketing analytics and healthcare technology, emphasizing practical clinical translation of AI systems.
Dr Nicola Fearn is a Lecturer in the Discipline of Occupational Therapy at the Sydney School of Health Sciences, Faculty of Medicine and Health, The University of Sydney. Since joining in 2024, she has integrated 19 years of clinical experience in Australian and UK acute hospital, rehabilitation, and community settings with her research on cancer rehabilitation and lymphedema management. She maintains active clinical practice as an accredited lymphoedema therapist. Her educational background includes: Occupational Therapy qualification (2005) PhD in breast lymphoedema assessment, incidence, and risk factors following breast cancer treatment (2022) Dr Fearn's research program addresses critical gaps in cancer survivorship through four interconnected pillars: cancer rehabilitation focusing on long-term quality of life; lymphoedema management (particularly breast-related); neurological upper limb rehabilitation for stroke and brain injury; and implementation science to translate evidence into clinical practice. Her work consistently emphasizes patient-centered approaches and interdisciplinary collaboration. Analysis of her 11 publications since 2022 reveals dominant themes in constraint-induced movement therapy for stroke rehabilitation (60% of output) and breast lymphoedema quantification/management (30%), with strong methodological diversity spanning systematic reviews, qualitative studies, feasibility trials, and telehealth adaptations. Key trends include integration of behavior change frameworks (Theoretical Domains Framework, COM-B model) and growing emphasis on health equity for diverse populations. Dr Fearn actively supervises HDR students interested in cancer survivorship and evidence implementation, and has secured the 2024 FMH Start-up Scheme grant. Current projects include SURPASS (patient-centered survivorship care), DIVERSE (supportive care for diverse backgrounds), ReCITE (remote constraint-induced therapy), and telehealth validation studies for rehabilitation assessments. As a member of the Australasian Lymphology Association, she collaborates with St Vincent's Health Network teams across oncology, neurology, and rehabilitation services to develop clinically relevant interventions that address both physical and psychosocial aspects of survivorship and neurological recovery.
Dr. Heather Murray is a Cancer Institute NSW Early Career Research Fellow at the University of Newcastle, affiliated with the School of Biomedical Sciences and Pharmacy. She holds dual roles as a Lecturer and Postdoctoral Researcher, focusing on proteomics and phosphoproteomics to uncover therapeutic targets in acute myeloid leukemia (AML). Her work combines genomic, proteomic, and clinical approaches to address treatment resistance and precision medicine in blood cancers. Education: PhD in Medical Biochemistry (University of Newcastle, 2020), MPhil, BSc (Hons) in Biomedical Sciences, and BSc in Biological Sciences, all from the University of Newcastle. Research Interests: Proteomic characterization of leukemia subtypes, DNA repair mechanisms, and drug resistance pathways. Her lab uses phosphoproteomics to identify synergistic drug combinations targeting oncogenic pathways like FLT3 and KIT mutations. Key Collaborations: Works with clinicians like Associate Professor Anoop Enjeti and researchers at Hunter Medical Research Institute. Partnerships include institutions like the University of Southern Denmark and QIMR Berghofer. Grants & Funding: Secured over $2M in funding, including a 2022 Cancer Institute NSW Fellowship, BarbeCURE grants, and philanthropic support from organizations like the McDonald Jones Charitable Foundation. Supervision: Mentors 6 current PhD students on topics like venetoclax resistance, breast cancer biomarkers, and ex vivo AML models. Supervision history includes 6 completed Honours projects. Labs/Teams: Leads the Molecular Oncology group under Associate Professor Nikki Verrills. Member of the HMRI Precision Medicine Program and University of Newcastle ECR committees.
Associate Professor Susanna Park is an academic in Neuroscience at the School of Medical Sciences, University of Sydney. She leads a research group investigating neuropathy and neuromuscular diseases, with a focus on chemotherapy-induced peripheral neurotoxicity. Her work emphasizes clinical assessment tools and axonal degeneration mechanisms. Park holds affiliations with the Brain and Mind Centre and the Faculty of Medicine and Health. Education: PhD from University of New South Wales (UNSW) Notable Fellowships: RG Menzies/NHMRC Overseas Biomedical Fellowship (2011–2014) Research Interests: Clinical neurophysiology, blood-based biomarkers, and motor neuron disorders. Her studies address nerve excitability, chemotherapy-induced neuropathy, and inflammatory neuropathies. Park’s translational work includes developing clinical tools for neuropathy assessment in cancer patients. Publications focus on chemotherapy-induced neuropathy mechanisms, axonal degeneration, and biomarker discovery. Recent work explores electroacupuncture for neuropathy management and plasma lipidomics in risk assessment. Awards: 2022 SUPRA Supervisor of the Year finalist, 2018 RD Wright Fellowship Labs/Teams: Brain and Mind Centre, collaborating with international consortia like the Toxic Neuropathy Consortium.
Fabio Zanini is an Associate Professor at the University of New South Wales (UNSW) , leading a research group focused on computational biology , single-cell approaches , and transcriptomic analysis across diseases like severe dengue , neonatal lung disease , cancer , and marine biology . He previously conducted postdoctoral research at Stanford University (2016-2019) and earned a PhD in Bioinformatics from the Max Planck Institute for Developmental Biology and the University of Tuebingen (2015). Current Affiliation: Group leader, UNSW Previous Training: Postdoc (Stanford), PhD (Max Planck/University of Tuebingen) His research spans single-cell RNA sequencing , computational virology , developmental cell biology , and bioinformatics tool development , with recent work on: Severe dengue progression (viral-host interactions, immune signatures) Lung development (endothelial cell diversity, hyperoxia-induced injury) Cancer genomics (mutant HSC clones, AZA therapy response) Marine biology (plankton transcriptomics, evolutionary analysis) Bioinformatics (HTSeq 2.0, northstar algorithm) Recent scientific awards include grants from the Chan Zuckerberg Initiative ($270,000), NIH R01 (multiple), ARC Discovery Grant , and NHMRC Ideas Grant . Notable contributions include: Northstar - Cell classification algorithm SpectralSeq - Hyperspectral-transcriptomic integration Tabula Muris - Mouse aging atlas He has supervised research into hematopoietic stem cell regulation , lung vascular development , and autophagy in viral infections , with collaborations across Stanford , University of Sydney , and Harvard .
Chee-Ming Ting is an Associate Professor in the School of Information Technology at Monash University Malaysia. His expertise lies in machine learning, data science, and biomedical engineering, with a focus on signal processing, computational neuroimaging, and computer-aided detection. Previously, he held positions at King Abdullah University of Science and Technology (Research Scientist) and Universiti Teknologi Malaysia (Senior Lecturer). He has authored over 26 journal papers and 43 conference papers, and has secured research grants totaling RM2.5 million as PI/Co-PI. Education: PhD in Mathematics - Statistics, Master of Engineering in Electrical Engineering, and Bachelor of Engineering (Hons.) in Electrical & Electronics Engineering. Research interests include biomedical signal/image analysis, deep learning, spatio-temporal modeling, and neuroimaging applications for disease prediction and patient monitoring. He has supervised 9 graduate students (4 PhD, 5 Masters) and currently oversees 10 PhD candidates. Awards include the IEEE Signal Processing Society Malaysia's Research Excellence Award (2019, 2022) and several national/international innovation awards. His work contributes to UN Sustainable Development Goals related to health and technological advancement. Key projects include frameworks for neurological disease prediction using brain networks and generative adversarial networks for medical imaging enhancement.
Dr. Ghazal Bargshady is a Lecturer at the University of Canberra , with expertise in Affective Computing , Artificial Intelligence , and Healthcare Technology . Her roles include teaching units such as Computer Vision, Data Analytics, and Soft Computing, as well as supervising PhD and Master by Research students in AI-driven projects for healthcare and road safety. Education: She earned her PhD in Artificial Intelligence and Computer Vision from the University of Southern Queensland in 2020. Research Interests: Dr. Bargshady specializes in Computer Vision Deep Learning Biosignal Processing Facial Expression Analysis Human Factors in AI Wearable Sensors Multimodal Data Fusion Brain–Computer Interfaces Her work addresses real-world challenges in pain assessment, depression recognition, and driver safety using cutting-edge AI models. Article Trends: Her recent publications focus on Transformer architectures , fNIRS signal analysis , multimodal pain detection , and depression severity estimation via facial video data. These studies highlight her contributions to AI in healthcare , transportation safety , and biomedical signal processing . Teaching Activities: Dr. Bargshady has lectured units including Programming for Data Science , Computer Vision , and Soft Computing , emphasizing practical AI applications.
