جست‌وجوی استاد و پژوهشگر

• Applied Mathematics
• Mathematical Biology
• Mathematics Education
• +۳ مورد دیگر

Hayden Tronnolone is a Teaching Professor in the College of Science and Engineering at Flinders University. He coordinates the Bachelor of Mathematical Sciences program and serves as Deputy Teaching Program Director for Computing and Mathematical Sciences. He is also a member of the STEM Academy Steering Group and the Flinders Learning and Teaching Academy Steering Committee. Bachelor of Mathematical Sciences (Applied and Pure) Bachelor of Mathematical Sciences (Honours) PhD in Applied Mathematics (2016) His research spans applied mathematics and mathematical biology, including fluid dynamics in helical channels, modeling yeast growth with discrete lattice methods, and shape quantification from experimental images. He focuses on mathematics education, particularly strategies to reduce math anxiety and promote conceptual understanding through collaborative, creative teaching approaches. Hayden has received numerous awards for teaching excellence and academic achievement, including the Dean's Award for Excellence in Teaching (2022) and the University Medal (2010). He actively engages in professional service as the South Australian Representative on the AustMS Standing Committee on Mathematics Education and has organized major conferences like ANZIAM and AustMS. Dean (Education) Award for Excellence in Teaching (2022) Student-Led Teaching Award (2021) Dean's Commendation for Doctoral Thesis Excellence (2016) T. M. Cherry Prize (2015) University Medal (2010)

Robertson Burgessمشاهده پروفایل

مدرس

• Science education
• Mathematics education
• STEM teacher preparation
• +۵ مورد دیگر

Dr Robertson Burgess is a Lecturer in the School of Education at the University of Newcastle, Australia, specialising in secondary science and mathematics teacher education. Leveraging his PhD in Physics and prior experience as a high-school science and mathematics teacher in both England and Australia, he now leads research and teaching initiatives that integrate emerging technologies into STEM education. Education Doctor of Philosophy (Physics), University of Newcastle Bachelor of Science (Honours), University of Newcastle Master of Teaching (Secondary), University of Newcastle Research Interests Dr Burgess investigates how cutting-edge technologies—particularly artificial intelligence, virtual reality, and games-based learning—can be harnessed ethically and effectively in secondary classrooms. His work addresses two intertwined strands: (1) understanding the impact of these technologies on student learning and teacher practice, and (2) supporting early-career science teachers, many of whom teach outside their specialisation. By analysing large-scale teacher interactions in online communities using generative AI, he identifies pressing challenges and feeds these insights back into initial teacher education programs. Grants & Funding Across 2023–2024 he has secured or co-secured eight grants totalling $164,491 . Key projects include: Developing a Pacific Waste Curriculum Toolkit for Pacific Island Nations – SPREP (2023) Google Educator PD Grant Workshop – Google Asia Pacific (2024) CNC Plasma Cutter, Mobile Immersive Learning Lab, ICE Software iCave, Eye-Tracking Wearable, Video Editing Workstation – multiple CAPEX awards (2024) CHSF Pilot Research Scheme – College of Human and Social Futures (2024) Research Supervision He currently co-supervises or principal-supervises five PhD candidates , all within the College of Human and Social Futures. Projects span immersive digital tools in architecture education, teacher decision-making for VR integration, instructional balance for low-SES science students, HSC course-prediction modelling, and the cognitive effects of lighting on colour perception. Labs & Teams Dr Burgess is an active member of interdisciplinary teams within the School of Education and the College of Human and Social Futures, contributing to the university’s Mobile Immersive Learning Lab and collaborating with colleagues on the integration of AI-driven analytics into teacher professional development programs.

Sreenivasulu Chadalavadaمشاهده پروفایل

مدرس ارشد

• Hydrogeology
• Groundwater modeling
• Contaminant transport
• +۵ مورد دیگر

Dr. Sreenivasulu Chadalavada is a Conjoint Senior Lecturer at the Global Centre for Environmental Remediation (GCER) within the College of Engineering, Science and Environment at the University of Newcastle, where he has been employed since 2016. He serves as Program Coordinator for two major research programs funded by the Department of Defence and BHP at CRC CARE, which is headquartered at the University of Newcastle. His work focuses on demonstrating cost-effective remediation solutions for contaminated sites across Australia. Dr. Chadalavada completed his Ph.D. research at the Centre for Environmental Risk Assessment and Remediation (CERAR) at the University of South Australia. His doctoral research focused on simulation-optimization modeling approaches to identify unknown groundwater pollution sources, which led to the development of a novel software tool in hydrogeological modeling. Prior to joining the University of Newcastle, he worked as an Adjunct Research Fellow/Senior Hydrogeologist at the University of South Australia and as a Research Associate at the Indian Institute of Technology Kanpur. Dr. Chadalavada's research career over the past decade has centered on cutting-edge groundwater modeling and hydrogeology, with a focus on efficient characterization of potentially contaminated sites. His expertise spans mathematical modeling of groundwater flow and contaminant transport in contaminated aquifers, vapour intrusion modeling, and simulation-optimization methods. He has developed specialized knowledge in applying genetic algorithms to environmental remediation problems and has extended his research to include climate change impacts on groundwater systems. His current and future research focuses on developing mathematical models to simulate various hydrogeological processes and vapour migration pathways. Analysis of Dr. Chadalavada's recent publications reveals a strong interdisciplinary approach combining environmental engineering, hydrogeology, and computational methods. His work spans traditional hydrogeological modeling, climate change impacts on water resources, and increasingly incorporates artificial intelligence and machine learning techniques for environmental prediction and monitoring. There is a clear progression toward more sophisticated computational approaches in his recent work, with applications ranging from water quality index prediction to construction damage detection following natural disasters. Dr. Chadalavada has secured significant research funding through CRC CARE, including a $758,318 project on electrokinetic remediation of hydrocarbon-contaminated soils, a $533,848 project on natural attenuation of vapors, and a $481,835 project on co-disposal of contaminated soils with mine waste. His research has resulted in numerous high-impact publications in environmental science and engineering journals. As an academic supervisor, Dr. Chadalavada has co-supervised multiple PhD students working on diverse environmental remediation topics including vapour intrusion modeling, climate change impacts on groundwater, and electrokinetic remediation techniques. His teaching responsibilities include courses in Hydrogeology and environmental remediation. Dr. Chadalavada works within the Global Centre for Environmental Remediation, a specialized research center focused on developing practical solutions for contaminated site management. His role as Program Coordinator for the Department of Defence and BHP research programs places him at the forefront of translating research into practical applications for major industrial and government stakeholders.

Irosh Fernandoمشاهده پروفایل

مدرس ارشد

• Psychiatry
• Digital Health
• Health Informatics
• +۳ مورد دیگر

Dr. Irosh Fernando is a Conjoint Senior Lecturer at the School of Medicine and Public Health , University of Newcastle , with a dual background in psychiatry and computer science. He holds medical degrees (MBBS, 2000; MD Psychiatry, 2006) from the University of Colombo, a MPhil in Computer Science (Open University Sri-Lanka, 2006), and a PhD in Computer Science (University of Newcastle, 2017), complemented by a Master of Biostatistics (University of Sydney). PhD Research: Diagnostic Algorithms Subspecialty: Medical Expert Systems Research Interests focus on revitalizing medical expert systems through: Development of orthogonal vector projection for diagnostic reasoning Clinical decision support system design Mathematical modeling of depression dynamics Pattern-based formulation methodologies Integration of biostatistics in psychiatric assessment Telepsychiatry and mobile health applications Scientific Contributions include creating the Mental State Examination Scale (MSES) and Pattern-Based Formulation (PBF) framework. His work combines control theory with clinical data to model illness trajectories and treatment responses. Grant Leadership shows sustained funding from Hunter New England Local Health District and Priority Research Centre for Brain and Mental Health Research for projects like: 2020-2023 : Online mental health assessment trials 2018-2022 : Mobile application for psychiatric triaging 2022-2023 : Chest pain diagnostics via algorithms

• Nuclear Structure
• Experimental Nuclear Physics
• Nuclear Spectroscopy
• +۳ مورد دیگر

Dr AJ Mitchell is a Research Fellow in the Department of Nuclear Physics & Accelerator Applications within the Research School of Physics at the Australian National University. He joined ANU in 2015 and also serves as a Tuckwell Fellow, working closely with undergraduate scholars. Additionally, he is actively expanding outreach and engagement of the Research School of Physics across the Asia-Pacific region. His educational qualifications are: PhD in Experimental Nuclear Physics, University of Manchester, UK (2012) MSci (Honours) in Applied Mathematics and Physics, Queen's University Belfast, UK (2009) Dr Mitchell's primary research interests lie in experimental nuclear physics, with a focus on nuclear structure. His work includes investigating high-j single-particle energies in nuclei, nuclear spectroscopy using nucleon-transfer reactions, and studying the radioactive decay properties of exotic nuclei. He is particularly interested in the search for isomer depletion levels and the development of novel infrastructure for nuclear physics experiments. His significant scientific awards include: ACT Tall Poppy Science Award (2019) Senior Fellow, Higher Education Academy (2019) Fellow, Higher Education Academy (2017) In teaching, Dr Mitchell convenes PHYS8204 Fundamentals of Nuclear Radiation and co-convenes PHYS1001 Foundations of Physics. He is passionate about science communication and leads outreach initiatives such as hosting laboratory tours for high-school groups and running the ACT branch of the ConocoPhillips Science Experience. Internationally, he is involved in teacher training in Timor Leste and a capacity-building program with the University of Yangon in Myanmar.

Piotr Koniuszمشاهده پروفایل

دانشیار مدعو

• Computer Vision
• Machine Learning
• Artificial Intelligence
• +۴ مورد دیگر

Dr. Piotr Koniusz serves as a Principal Research Scientist in Machine Learning at Data61/CSIRO, an Adjunct Associate Professor at the University of New South Wales (UNSW) in the School of Engineering, and an Honorary Associate Professor at the Australian National University (ANU). He earned his BSc in Telecommunications and Software Engineering in 2004 from Warsaw University of Technology, Poland, followed by a PhD in Computer Vision in 2013 from CVSSP, University of Surrey, UK. Prior to his current roles, he conducted postdoctoral research with the LEAR team at INRIA, France (2013-2015). Dr. Koniusz's research spans computer vision and machine learning with expertise in representation learning (contrastive & self-supervised learning, vision-language models, graph neural networks), deep learning architectures, image classification, action recognition, and specialized learning paradigms including zero-shot, one-shot, and few-shot learning. His work also addresses domain adaptation, incremental learning, object segmentation and detection, generative networks, adversarial robustness, and mathematical approaches like spectral learning, tensor methods, and optimal transportation. Sang Uk Lee Best Student Paper Award from ACCV'22 Runner-up APRS/IAPR Best Student Paper Award from DICTA'22 Dr. Koniusz has been recognized as an outstanding Area Chair by ICLR (2021-2023), served as Workshop Program Chair for NeurIPS'23 and The Web Conf. 2025, and held Senior Area Chair positions for NeurIPS'23-24, ICLR'24-25, AAAI'24-25, and ICML'24-25.

• Structural Mechanics
• Sustainable Construction
• Recycled Waste Materials in Concrete
• +۳ مورد دیگر

Dr. Yanni Bouras is a part-time Lecturer at the College of Sport, Health & Engineering , Victoria University, with a PhD in Structural Engineering (2020) and BEng (Hons) (2015). His research focuses on structural mechanics, sustainable construction, and waste material utilisation in concrete composites. Education BEng (Hons), Victoria University (2015) GCTE, Victoria University (2020) PhD, Victoria University (2020) Research Interests Yanni investigates the thermal stability of concrete structures, sustainable infrastructure rating tools, and kraft fibre reinforcement from waste cardboard in concrete composites. His work bridges structural engineering with environmental sustainability. Recent Research Trends His publications since 2020 highlight innovations in waste valorisation (cardboard, coffee cups), machine learning for concrete creep prediction, and fractional calculus-based modeling. Key themes include low-carbon concretes , lifecycle assessments , and multi-objective optimisation . Supervision & Grants Yanni serves as a joint supervisor for research on engineered cementitious composites. He contributed to the Social Value Creation for Transport and Infrastructure grant (2021–2022), focusing on sustainable infrastructure. Institute Affiliation He is affiliated with the Institute for Sustainable Industries & Liveable Cities at Victoria University, aligning his work with UNSDGs 12, 6, 7, and 9.

Sebastian Hoerningمشاهده پروفایل

پژوهشگر ارشد

• Geostatistics
• Stochastic Modeling
• Copula-based Non-linear Geostatistics
• +۵ مورد دیگر

Dr. Sebastian Hoerning is a Research Fellow at The University of Queensland's Gas & Energy Transition Research Centre within the Faculty of Engineering, Architecture and Information Technology. His work focuses on advanced geostatistical methods for energy transition and environmental applications. His educational background includes: Bachelor of Science from Universität Stuttgart Masters (Coursework) of Science from Universität Stuttgart Doctor of Philosophy from Universität Stuttgart Dr. Hoerning's research centers on geostatistics and stochastic modeling with applications in underground hydrogen storage, fugitive methane emissions, and reservoir characterization. His innovative work on copula-based non-linear geostatistics addresses directional asymmetry in spatial fields, providing more accurate representations of geological formations. He develops computational methods that bridge theoretical statistics with practical energy challenges, particularly relevant to Australia's energy transition. His recent publications demonstrate a clear focus on critical energy transition issues, with particular emphasis on underground hydrogen storage , fugitive methane monitoring , and advanced computational geostatistics . These works show progression from fundamental methodological developments to applied solutions for real-world energy challenges. Dr. Hoerning has secured significant research funding including: Novel statistical estimation of fugitive methane emissions using drones (Advance Queensland Industry Research Fellowships, 2022-2024) New Stratigraphy and Geostatistics for Gas and Water Resources (ARC Linkage Projects, 2020-2023) Impact of Geostatistical Techniques on Technically Recoverable Resources (Australian Energy Resource Growth Centre Ltd, 2018-2021) He actively supervises PhD students, serving as Principal Advisor for research on hydrogen storage repurposing of gas fields and Associate Advisor for waveform inversion techniques. His development of computational tools like RMWSPy enables spatial simulation for environmental applications, supporting both academic research and industry practice.

Oliver Rawashdehمشاهده پروفایل

مدرس ارشد

• Circadian Biology
• Neuroscience
• Chronobiology
• +۷ مورد دیگر

Dr. Oliver Rawashdeh is a Senior Lecturer in Biomedical Sciences at the School of Biomedical Sciences, Faculty of Health, Medicine and Behavioural Sciences at The University of Queensland. His research focuses on the intersection of circadian biology and neuroscience, particularly how biological clocks modulate learning, memory, and sleep processes across species. Education: Bachelor's in Biology (2001) from Yarmouk University in Jordan Master's in Science (2005) from University of Houston Ph.D. (2007) from University of Houston Dr. Rawashdeh's research centers on understanding how the circadian system regulates complex physiological processes, particularly learning and memory. His seminal 2007 Science paper demonstrated how melatonin modulates long-term memory consolidation. He investigates the mechanisms by which biological clocks shape daily variations in memory processing efficiency and how circadian disruption contributes to neurodegenerative diseases. His work spans from basic molecular mechanisms in model organisms to clinical applications in Parkinson's disease and Alzheimer's disease. Dr. Rawashdeh's extensive publication record (47 works including 40 journal articles) demonstrates a clear evolution from fundamental circadian mechanisms to translational research in neurodegeneration. His recent work shows increasing focus on circadian dysfunction in Parkinson's disease and other synucleinopathies, with multiple 2023-2025 publications examining sleep-circadian interactions in neurodegenerative conditions. He has developed methodological innovations like the CircaCompare statistical tool for circadian rhythm analysis. Dr. Rawashdeh is actively supervising PhD students on projects related to circadian biology and neurodegeneration. His current funding includes an NHMRC IDEAS Grant (2020-2024) titled 'The clock as a therapeutic target to improve sleep quality and circadian dysfunction in Parkinson's disease: fighting neurodegeneration by treating chronodegeneration.' He has previously secured equipment funding for advanced microscopy capabilities. He leads an interdisciplinary research program that spans chronobiology, neuroscience, pharmacology, engineering, and mathematics. His collaborative groups work on urgent translational research questions related to sleep and circadian rhythms in health and disease, with particular emphasis on developing therapeutic approaches to enhance human adaptability to temporal environmental changes and to treat circadian dysfunction in neurodegenerative conditions.

Timothy Ballardمشاهده پروفایل

پژوهشگر ارشد

• Decision-Making
• Motivation
• Fatigue
• +۶ مورد دیگر

Dr. Timothy Ballard is an ARC Future Fellow at the School of Psychology , University of Queensland, with affiliations to the Centre for Business and Organisational Psychology. His research program integrates statistical, computational, and mathematical models to address workplace health, safety, and performance dynamics. Key research areas: Decision-Making, Motivation, Fatigue, Stress, Computational Modeling Funding: Over $3 million from ARC, Commonwealth Defence Science and Technology Group, and Universities Australia His work explores: Cognitive mechanisms in self-other memory prioritization Neurochemical bases of decision strategies (dopamine, tDCS effects) Fatigue prediction models for naval and aviation environments Bayesian frameworks for dynamic change modeling Recent publications in Psychological Review , Journal of Neuroscience , and Neuropsychologia highlight methodological innovations and applications to real-world systems. Awards include: ARC DECRA and Future Fellowships Early Career Researcher Awards from Australian Psychological Society He supervises PhD candidates in: Workweek redesign for mental health Multigoal prioritization under friction Brain stimulation and metacognition His consultancy bridges organizational data analytics with cognitive science to optimize workforce strategies.

• Signal Processing
• Machine Learning
• Data Science
• +۷ مورد دیگر

Yuejie Chi is the Sense of Wonder Group Endowed Professor of Electrical and Computer Engineering in AI Systems at Carnegie Mellon University, holding courtesy appointments in the Machine Learning department and CyLab. She earned her Ph.D. and M.A. in Electrical Engineering from Princeton University and B.Eng. (Hon.) from Tsinghua University. Her research centers on theoretical and algorithmic foundations of data science with expertise in signal processing, machine learning, and inverse problems. Key application areas include sensing, imaging, decision-making systems, and societal-scale data challenges. Her work bridges mathematical theory with real-world implementations through preconditioning techniques, overparameterization frameworks, and diffusion models for ill-conditioned estimation problems. Major recognitions include: Presidential Early Career Award for Scientists and Engineers (PECASE) IEEE Signal Processing Society Early Career Technical Achievement Award IEEE Signal Processing Society Young Author Best Paper Award Goldsmith Lecturer by IEEE Information Theory Society Distinguished Lecturer by IEEE Signal Processing Society IEEE Fellow (2023) for contributions to statistical signal processing with low-dimensional structures Dr. Chi serves as Associate Editor for IEEE Transactions on Information Theory, IEEE Transactions on Signal Processing, IEEE Transactions on Pattern Recognition and Machine Intelligence, Information and Inference: A Journal of the IMA, and SIAM Journal on Mathematics of Data Science. Her research program integrates theoretical guarantees with practical implementations in AI systems, particularly through collaborations with CyLab on security-aware data science frameworks.

• Operations Research
• Artificial Intelligence
• Public Policy
• +۳ مورد دیگر

Sheldon H Jacobson is a Founder Professor of Computer Science at the University of Illinois at Urbana-Champaign, where his research applies operations research and artificial intelligence to public sector problems and public policy. His educational background includes: B.Sc in Mathematics from McGill University Ph.D. in Operations Research from Cornell University Dr. Jacobson's research spans high-impact public policy domains: foundational risk-based aviation security models that informed TSA PreCheck design, computational redistricting algorithms to combat gerrymandering (hosted at redistricting.cs.illinois.edu ), and NCAA basketball analytics as a STEM educational platform (at bracketodds.cs.illinois.edu ) attracting over 800,000 page views since 2012. His work bridges theoretical optimization with real-world policy implementation across security, political science, and sports analytics. His scientific recognition includes: INFORMS Impact Prize Aviation Security Research Award from Aviation Security International Guggenheim Fellowship Elected Fellow of INFORMS Elected Fellow of IISE Elected Fellow of AAAS Dr. Jacobson maintains significant government engagement through briefings for the Office of Science and Technology Policy and Advisory Committee on Immunization Practices, committee service for the National Research Council and National Academy of Medicine, and leadership of NSF-funded initiatives including the Broader Impacts Innovation Roadmap workshop. His prior role as NSF Program Director (2012-2014) demonstrates deep integration with federal research infrastructure. His research group operates two major public-facing platforms: the computational redistricting project serving as both policy tool and academic resource, and the NCAA analytics laboratory functioning as a large-scale STEM education environment for students nationwide.

• Internet of Things
• Edge Computing
• Smart Cities
• +۶ مورد دیگر

Seng Loke is Professor in Computer Science at Deakin University, Australia, where he co-directs the Platforms and Applications Lab within the Centre for Internet-of-Things ECOsystems Research and Experimentation (CITECORE) at the School of Information Technology. He concurrently serves as Research Theme Leader for 'Intelligent Built Environments' in the Live+Smart Research Lab at Deakin’s School of Architecture and Built Environment, while holding adjunct professorships at La Trobe University (School of Engineering and Mathematical Sciences) and Southern Cross University (School of Business and Tourism). Education: PhD, University of Melbourne, 1998 His research pioneers Internet of Things architectures , edge-cloud computing integration , and human-machine cooperative systems for smart cities and transportation. Key contributions span context-aware pervasive systems (detailed in his 2006 CRC Press book) and crowd-powered mobile computing frameworks (2017 Springer publication), with emphasis on cooperative vehicles and urban IoT ecosystems. Professor Loke has authored over 300 publications including 70+ journal papers in IEEE Transactions, ACM Computing Surveys, and IEEE Internet of Things Journal. His academic leadership includes program committees for AAMAS (2003-2005), Percom (2010-2011), and MDM (2003-2006), workshop organization for AwareCities (Percom 2016) and IoCAT (Mobiquitous 2017), and editorial board membership for Sensors journal's IoT section. He actively disseminates research through public lectures on cooperative IoT algorithms and automated city futures.

• High-dimensional Knapsack problems
• Sequence alignment
• Data structures
• +۵ مورد دیگر

M. Sohel Rahman is a Professor in the Department of Computer Science and Engineering (CSE) at Bangladesh University of Engineering and Technology (BUET). He has held visiting positions at King’s College London (2008-2011, 2014-15) and is a Senior Member of IEEE and ACM. His affiliations include the American Mathematical Society (AMS) and London Mathematical Society (LMS), and he serves as a Peer-review Associate College Member of EPSRC, UK. Education: Not explicitly detailed in the text. His research spans high-dimensional Knapsack problems, sequence alignment, data structures, string combinatorics, Hamiltonianicity, Machine Learning applications in Bioinformatics, and metaheuristics solutions for hard computational problems. He has led projects funded by the British Council, UGC-World Bank, ICT Division of Bangladesh Government, and BUET, and has published 86 peer-reviewed journal papers. Scientific awards include the Bangladesh Academy of Sciences Gold Medal, UGC Award, Commonwealth Scholarship/Fellowship, and ACU Titular Fellowship. He contributes as an Academic Editor for PLOS One , Associate Editor for BMC Research Notes , and has guest-edited special issues in journals like Theoretical Computer Science . He also serves on program committees for international conferences and writes reviews for Mathematical Review and ACM Computing Review.

• Computational Social Science
• Social Media Analysis
• Digital Demography
• +۷ مورد دیگر

Dr. Ingmar G Weber serves as Research Director for Social Computing at the Qatar Computing Research Institute (QCRI) in Doha, Qatar. He holds a PhD in Computer Science from the Max-Planck Institute for Computer Science (2003-2007) and an undergraduate Mathematics degree from Cambridge University (1999-2003). Prior positions include researcher roles at Ecole Polytechnique Federale de Lausanne (2007-2009), Yahoo Research Barcelona (2009-2012), and a visiting researcher position at Microsoft Research Cambridge (summer 2008). Dr. Weber's interdisciplinary research leverages large-scale social media data to study human behavior at scale, with core interests in computational social science and digital demography. His work examines obesity and population health patterns, quantifies international migration through digital footprints, and analyzes political polarization and extremism online. These research themes are reflected in his conference tutorials including 'Computational Social Science for the World Wide Web' (WWW'16) and 'Twitter and the Real World' (CIKM'13), demonstrating methodological innovations in social media analysis. As an active academic contributor, Dr. Weber serves on program committees for premier conferences such as ICWSM, KDD, WWW, ACL, VLDB, and WebSci, and sits on the editorial board for the Journal of Web Science. His research group at QCRI develops computational approaches to extract societal insights from online data, with applications in public health and policy domains. Scientific awards: None mentioned in the provided text. No information regarding student advising or research grants was provided in the text. Dr. Weber leads the Social Computing research group at QCRI, which focuses on advancing methodologies for analyzing social media data to address societal challenges in health, migration, and political discourse through interdisciplinary collaboration.