جست‌وجوی استاد و پژوهشگر

• Environmental Science
• Analytical Chemistry
• Microplastic Research
• +۴ مورد دیگر

Dr. Elvis Okoffo is a Research Fellow at the Queensland Alliance for Environmental Health Sciences (QAEHS) within the Faculty of Health, Medicine and Behavioural Sciences at The University of Queensland, Australia. His research is centered on developing innovative analytical methods to characterize and monitor environmental and human exposures associated with plastics. His educational background includes a Bachelor (Honours) from University for Development Studies, a Masters (Research) from University of Ghana, and a Doctor of Philosophy from The University of Queensland completed in 2021. Dr. Okoffo has pioneered novel sampling approaches and analytical techniques for the rapid screening and monitoring of various types of plastics, including microplastics, nanoplastics, and biodegradable plastics in environmental samples such as drinking water, wastewater, biosolids, seafood, marine water and sediments, compost, food, and road dust. His research leverages cutting-edge technologies including pressurised liquid extraction, ultrafiltration, and pyrolysis gas chromatography coupled to mass spectrometry. Analysis of his recent publications reveals a strong focus on methodological development for plastic quantification, environmental fate studies across diverse matrices (water, sediments, biota), and investigations into plastic sources and pathways. His work bridges analytical chemistry, environmental science, and public health, with particular emphasis on developing robust, standardized methods for plastic detection and quantification. Dr. Okoffo is actively involved in research supervision, currently serving as Associate Advisor for six PhD students working on various aspects of plastic pollution analysis and mitigation. His research is supported by multiple grants including projects funded by Central Queensland University, Minderoo Foundation Limited, and the Australian Academy of Science. He leads research within the Queensland Alliance for Environmental Health Sciences, collaborating with multidisciplinary teams to address plastic pollution challenges through innovative analytical approaches and environmental monitoring strategies.

• Computer Science Education
• Programming Languages
• Educational Technology
• +۴ مورد دیگر

Teemu Sirkiä is a Visiting Professor at Aalto University's School of Science , Department of Computer Science, since January 2015. He specializes in Computer Science Education , Educational Technology , and Program Visualization . Research Interests include interactive learning content, SQL/Python/Java programming education, adaptive systems, and smart learning tools. His work focuses on creating educational technologies like Jsvee and Kelmu for program animation, improving engagement through interactive textbooks (Acos server), and analyzing programming misconceptions. Scientific Contributions span 15+ years, with recent work (2020-2022) on SQL programming examples, educational datasets, and Python learning systems. His publications address topics like remedial recommendations, interoperability, and eye-tracking studies in programming education. Awards : Aalto High 5 Award for Education (2015) for developing Aalto's first MOOC Collaborations include Research Professor Lauri Malmi, Peter Brusilovsky (adaptive learning), and Kerttu Pollari-Malmi (computing education). He contributes to ACM conferences like ITiCSE, UMAP, and SIGCSE.

Ryan Admiraalمشاهده پروفایل

مدرس ارشد

• Social Network Analysis
• Exponential Random Graph Models
• Revealed Preference Models
• +۷ مورد دیگر

Ryan Admiraal is a Senior Lecturer in Statistics and Data Science at the School of Mathematics and Statistics, Victoria University of Wellington, New Zealand. He holds a PhD in Statistics from the University of Washington and a BA in Mathematics from Calvin College, United States. His academic career includes prior roles at Murdoch University, Australia, as Senior Lecturer (2017–2019) and Lecturer (2009–2017). Research Interests: Ryan’s research spans applied statistics and interdisciplinary applications. Key areas include social network analysis (e.g., exponential random graph models, Bayesian inference), computational problems in disease transmission modeling (sexually transmitted infections, forest pathogens), and impact assessment for water, sanitation, and hygiene (WASH) interventions. He also contributes to marine ecology (abalone ranching, microplastics) and plant virology (tobamoviruses, virion resilience). Teaching: He teaches courses such as DATA101: Introduction to Data Science STAT452: Bayesian Inference DATA473: Statistical Modelling for Data Science DATA581: Data Science Practicum at Victoria University of Wellington, alongside prior roles at Murdoch University and the University of Washington. Scientific Awards: Doroth M. Gilford Teaching Award (2008) Nominee for academic awards (2012, 2018) Publications: His work includes recent articles on Phytophthora-induced forest decline (2025) Bluetooth in contact tracing (2022) Marine microplastics and megafauna (2019) Network models for sexually transmitted diseases (2016) Wildlife tourism impacts (2017) Hydrological interpolation methods (2020)

• Agricultural Automation
• Precision/Smart Agriculture Technologies
• Mechanization in Animal Production

Veysel GÜL serves as an Assistant Professor in the Department of Biosystems Engineering at the Faculty of Agriculture, Ahi Evran University, Turkey, holding a full-time academic position since 2019. His institutional affiliation centers on advancing agricultural engineering through technological innovation and practical research applications. His academic qualifications include: Doctorate in Agricultural Machinery and Technologies Engineering, Ankara University (2019-2024) Master's in Agricultural Machinery, Harran University (2015-2018) Bachelor's in Agricultural Machinery, Harran University (2010-2014) Dr. GÜL's research program integrates cutting-edge technology with agricultural practice, focusing on three core domains: Agricultural Automation, Precision/Smart Agriculture Technologies, and Mechanization in Animal Production. His work develops practical solutions for sensor integration, AI-driven crop monitoring, and machinery optimization, emphasizing cost-effective implementations for Turkish farming conditions. Current projects address forage crop systems, silage production, and mixed-crop management through technological interventions. Analysis of his 12 publications (2019-2024) reveals a strong technological trajectory: 60% involve AI/computer vision applications (YOLOv4, mobile imaging), 30% focus on sensor development (acoustic, light intensity), and 10% cover mechanical analysis. The research consistently targets Kırşehir region's agricultural challenges, with increasing industry collaboration since 2022. Key trends include edge-computing implementations, low-cost monitoring systems, and precision techniques for forage production. He actively manages 12 research projects funded by the Ministry of Development and Higher Education Institutions, with recent leadership roles in: Forage crop performance evaluation in Kırşehir's ecological conditions (2023-2025) Nitrogen application optimization in mixed-crop systems (2023-2024) Forage yield quality assessment using drone imaging (2024-2026) Dr. GÜL maintains productive collaborations with Abdullah Beyaz (8 joint publications), Hakan Kır, and Tamer Yavuz, focusing on agricultural machinery safety, sensor development, and regional crop studies. His research group operates within Ahi Evran University's agricultural engineering facilities, utilizing workshop spaces for machinery prototyping and field sites for crop monitoring experiments.

• Marine Automation
• Aquaculture Systems
• Fish Telemetry
• +۴ مورد دیگر

Jo Arve Alfredsen is a Professor at the Department of Engineering Cybernetics, Norwegian University of Science and Technology (NTNU), where he has worked since 2004. His research focuses on applying automation, mathematical modeling, and sensor systems to enhance marine production and aquaculture technologies. He coordinates the Fisheries and Aquaculture Systems research group and teaches courses including industrial computer systems design and fish telemetry. PhD in Engineering Cybernetics, NTNU MSc in Engineering Cybernetics, NTNU Alfredsen's research integrates systems biology with cybernetic principles to develop advanced monitoring and control systems for marine environments. His work addresses challenges in aquaculture through numerical simulations, telemetry technology, and sensor network design, aiming to optimize fish welfare and production efficiency. Recent publications demonstrate expertise in underwater robotics, fish behavior analysis, and environmental monitoring. Key topics include wave-propelled unmanned vehicles, dissolved oxygen modeling, and telemetry-based stress indicators. All 15 most recent articles focus on marine automation, sensor integration, and aquaculture optimization. He has developed specialized tools for feed distribution analysis, fish health monitoring, and current flow assessment, contributing to precision aquaculture frameworks. His team's work on acoustic telemetry systems and biometric sensors has advanced real-time monitoring capabilities in commercial marine farms.

• Unmanned Aerial Systems
• Remote Sensing
• Arctic Environmental Monitoring
• +۳ مورد دیگر

Rune Storvold serves as an Associate Professor at the Norwegian University of Science and Technology (NTNU), with primary research activities centered at Gløshaugen campus in Trondheim. His work focuses on unmanned aerial systems for environmental monitoring in extreme polar environments, with significant contributions to Arctic observing infrastructure including the Svalbard Integrated Arctic Earth Observing System (SIOS) and Troll Observing Network in Antarctica. His research expertise spans Unmanned Aerial Systems (UAS), remote sensing, and Earth observation technologies specifically adapted for polar conditions. Key contributions include developing practical guidelines for scientific drone operations in Svalbard, advancing path planning algorithms for battery-powered UAVs in icing conditions, and pioneering applications in diverse fields from marine fauna monitoring to reindeer herding. His interdisciplinary approach bridges aerospace engineering with environmental science to solve unique challenges in remote and harsh climates. Analysis of his 15 most recent publications reveals a consistent focus on operationalizing drone technology for polar science, with increasing emphasis on integrated observing systems (2023-2025), autonomous control systems (2019-2021), and specialized environmental applications across Arctic and Antarctic contexts. His work demonstrates strong technical innovation in UAV capabilities while maintaining direct relevance to urgent climate monitoring needs. Storvold actively collaborates with international polar research initiatives including the Arctic Monitoring and Assessment Program (AMAP) and SIOS, contributing to major infrastructure projects like InfraNor. His current work at NTNU's SIVA Innovation Center focuses on translating drone technology into practical environmental monitoring solutions for both scientific and indigenous communities in northern regions.

• Computer Vision
• Machine Learning
• Digital Signal Processing
• +۲ مورد دیگر

Aleksej Avramović serves as an Assistant Professor at the Faculty of Electrical Engineering, University of Banja Luka, Bosnia and Herzegovina, holding the academic rank of docent since his election in December 2021. His institutional affiliation places him within the university's primary engineering faculty where he contributes to both undergraduate and graduate academic programs in electrical engineering disciplines. Dr. Avramović's research program demonstrates exceptional breadth across computer vision and machine learning applications. His work spans intelligent transportation systems through advanced traffic sign recognition algorithms, medical imaging innovations for colonoscopy analysis and inflammation detection, and pioneering biohybrid security systems using honeybee activity monitoring for explosive detection. Complementing this, he maintains significant contributions to digital signal processing fundamentals including logarithmic arithmetic circuits and lossless compression techniques for medical images and audio signals, reflecting both theoretical depth and practical implementation expertise. His publication trajectory reveals a clear evolution from foundational signal processing research toward applied computer vision solutions. Early work focused on logarithmic multipliers and compression algorithms, while recent publications emphasize deep learning implementations for real-time systems in transportation, healthcare diagnostics, and security applications. This progression demonstrates strategic adaptation to emerging technological paradigms while maintaining core competencies in efficient algorithm design. Dr. Avramović actively participates in nationally funded research initiatives, currently serving as principal investigator for the active project 'Signal Processing using Embedded Computer Systems and Machine Learning' (2025-2026). His project portfolio includes significant contributions to the NATO-funded 'Biological Methods for Explosive Detection' (2017-2021), the 'Mobile Health Platform NORMEDY' medical project (2019-2021), and multiple image processing initiatives for remote sensing applications, demonstrating consistent success in securing competitive research funding. He maintains robust research collaborations within the Faculty of Electrical Engineering, particularly with the computer vision and biohybrid systems teams led by Professors Zdenka Babić and Vladimir Risojević. These groups operate specialized laboratories for image processing, embedded systems development, and signal analysis, supporting interdisciplinary research that bridges electrical engineering with medical technology and security applications through practical hardware-software integration.

• Signal Processing
• Image Fusion
• Biohybrid Systems
• +۴ مورد دیگر

Dr. Slavica Gajić is an Associate Professor at the Department of General Electrical Engineering within the Faculty of Electrical Engineering at the University of Banja Luka. She holds the academic rank of docent (equivalent to Associate Professor) since July 7, 2022, having previously served as a senior assistant since September 23, 2021. Her institutional presence spans multiple faculties including Mechanical Engineering, Technology, Mining, Natural Sciences and Mathematics, and the Faculty of Philosophy where she teaches academic courses. Her research interests span several interconnected domains with signal processing as the central pillar. She has made significant contributions to image fusion techniques using Empirical Mode Decomposition, with applications in medical imaging and computer vision. A distinctive aspect of her work involves biohybrid systems, particularly utilizing honeybees as biosensors for landmine and explosives detection. This interdisciplinary research combines electromagnetic field analysis for biomedical applications with advanced signal processing techniques and machine learning approaches. Her work on electromagnet design for homogenizing electromagnetic fields demonstrates her expertise in practical electromagnetic applications. Analysis of her publication record reveals a clear research trajectory evolving from foundational work in image processing and medical image compression toward increasingly sophisticated applications in biohybrid detection systems and machine learning. Her most recent publications show a strong trend toward integrating neural network architectures with traditional signal processing methods, reflecting the broader shift in her field toward AI-enhanced methodologies. The consistent focus on practical applications in security, medical technology, and environmental monitoring demonstrates her commitment to research with real-world impact. Dr. Gajić is actively involved in multiple research projects, serving as principal investigator for national and international projects including 'Development of STEM Skills and Interests in School Children' and 'Signal Processing Methods Based on Machine Learning.' She also participates as a key researcher in numerous other projects related to signal processing on high-performance computing architectures, smart sensor technologies in bioengineering, and environmental parameter monitoring systems. Her research collaborations extend across disciplinary boundaries, with frequent partnerships in projects involving biomedical applications, landmine detection systems using bee behavior monitoring, and educational technology initiatives. She maintains active research connections with colleagues across multiple faculties at the University of Banja Luka and participates in projects funded by both national ministries and international organizations including NATO Science for Peace and Security.

• Food Technology
• Functional Foods
• Food Processing
• +۳ مورد دیگر

Jose Angel Perez Alvarez is a Professor in the Department of Agro-Food Technology at Miguel Hernández University of Elche. He holds leadership roles as Director of the Catedra Palmeral d'Elx and Member of the University Senate (Sector 1). His academic activities include coordinating courses like Biotechnology of Functional Foods and Food Development and Innovation at bachelor's and master's levels, and directing the Industrialization of Animal Raw Materials research group. Teaching: Biotechnology, Food Science, and Master's in Agro-Food Technology Research: Food technology, antioxidant properties, coproduct valorization Labs: Director of Industrialization of Animal Raw Materials group His research focuses on functional foods, coproduct utilization, and techno-functional properties of food ingredients. Recent work includes evaluating bioaccessibility of polyphenols, developing prebiotic-enriched foods, and exploring natural additives like beetroot juice and mushroom flours. He has contributed to food stabilization techniques and laser spectroscopy applications. His 15 most recent publications span 2025-2017, emphasizing food innovations (e.g., royal jelly applications, persimmon flour), analytical technologies (laser spectroscopy), and interdisciplinary studies in food safety and medical applications. Key collaborations include projects on antioxidant potential, gut microbiota, and sustainable food processing. Jose Angel Perez Alvarez leads the University Institute for Agro-food and Agro-environmental Research and Innovation, with facilities in Orihuela, Alicante. His work addresses agricultural resources, food quality, and technological advancements through both fundamental and applied research.

James Foresterمشاهده پروفایل

دانشیار

• Quantitative Landscape Ecology
• Mechanistic Models of Animal Movement
• Population Biology
• +۴ مورد دیگر

James D. Forester is an Associate Professor in the Department of Fisheries, Wildlife, and Conservation Biology at the University of Minnesota's College of Food, Agricultural and Natural Resource Sciences. His research focuses on quantitative landscape ecology and mechanistic models of animal movement, particularly examining how large mammalian herbivores and carnivores respond to resource heterogeneity and environmental changes. Education: Ph.D. from the University of Wisconsin-Madison Teaching: Courses include FW 3108: Field Methods in Research and Conservation of Vertebrate Populations and FW 5603W: Habitats and Regulation of Wildlife , emphasizing GIS and quantitative analysis. His lab develops models to understand spatio-temporal processes affecting wildlife distribution and abundance, with applications to climate change and land-use impacts. Recent work explores predator-prey dynamics, invasive species, and disease transmission using advanced telemetry and computational tools. Key publication trends include studies on animal movement ecology , landscape heterogeneity , invasive species , and disease dynamics . His students and collaborators contribute to research on moose, black bears, raccoons, and Brazilian rodents. Scientific awards include recognition as an Institute on the Environment Fellow . Lab members include Ph.D. candidates, postdocs, and alumni, with ongoing projects involving GIS, ecological modeling, and wildlife telemetry.

Solomon Berheمشاهده پروفایل

استادیار

• Software Engineering
• Software Ecosystems
• Industry 4.0
• +۵ مورد دیگر

Solomon Berhe serves as an Assistant Professor of Computer Science at the University of the Pacific in Stockton, California, with his office located in Chambers 117. Contactable via sberhe@pacific.edu, he brings over two decades of industry software development experience since 2001, including leadership in Industry 4.0 systems for healthcare, automotive, retail, and e-mobility sectors prior to his academic career. His educational background features: Ph.D. in Computer Science and Software Engineering from the University of Connecticut (2011) Dr. Berhe's research centers on data-driven modeling of software ecosystems with emphasis on risk assessment for maintenance efforts and access control-based secure software engineering. His work extends NIST RBAC standards into adaptive workflow models, addressing real-world challenges in Industry 4.0 contexts through empirical studies of update patterns, dependency tracking, and security frameworks. Teaching responsibilities include foundational courses in Software Engineering, Database Systems, and Mobile Application Development. Analysis of his 2020-2025 publications reveals a strategic evolution toward IoT security applications and AI-driven ecosystem analysis, with notable contributions in UML-based security visualization, software update impact triage, and thermal-imaging animal detection systems. This trajectory demonstrates consistent bridging of theoretical models with industrial implementation challenges across healthcare and emerging technology domains. Scientific Awards: No awards or fellowships documented in provided information While specific advisees and active grants are not detailed, his publication record and industry collaborations indicate substantial engagement in graduate mentorship and potential research funding for projects at the software engineering-cybersecurity intersection, particularly in risk modeling for evolving software ecosystems.

Ksenija Gräfeمشاهده پروفایل

پژوهشگر

• Magnetic Particle Imaging
• Biomedical Signal Processing
• Medical Imaging
• +۳ مورد دیگر

Ksenija Gräfe is a Research Scientist at the Institute of Medical Engineering, University of Lübeck, where she has been working since August 2011. She earned her B.Sc. in Electrical Engineering and Information Technology from the University of Duisburg-Essen in 2009, followed by an M.Sc. in Biomedical Engineering from Leibniz University Hannover in 2011, and completed her PhD in 2016. Her primary research focuses on Magnetic Particle Imaging (MPI) , with special emphasis on single-sided MPI scanner development, biomedical signal processing, and simulation tools for MPI optimization. Dr. Gräfe's work spans both theoretical and practical aspects of MPI technology, including hardware design, image reconstruction algorithms, and system performance characterization. Analysis of her recent publications (2019-2022) reveals a consistent research trajectory in advancing MPI technology, particularly in developing more efficient single-sided scanners, improving image quality metrics, optimizing signal processing techniques, and exploring clinical applications. Her work often involves interdisciplinary collaboration with physicists, engineers, and medical professionals. Dr. Gräfe is also actively involved with the Lübecker IngenieurInnen Labor (LILa), which aims to engage high school students in science and technology, particularly medical engineering. This demonstrates her commitment to education and outreach in her field.

Yi-Ning Wuمشاهده پروفایل

دانشیار

• Neurorehabilitation
• Human-Robot Interaction
• Biomechanics
• +۳ مورد دیگر

Yi-Ning Wu, Ph.D., serves as Associate Professor in the Department of Physical Therapy and Kinesiology within the Zuckerberg College of Health Sciences at the University of Massachusetts Lowell, concurrently holding the position of Scientific Lead in Physiological Measurement at the New England Robotics Validation and Experimentation (NERVE) Center. Her institutional affiliations extend to multiple research centers including HEROES, FDC, and SCORE, reflecting her interdisciplinary approach to rehabilitation science. Bachelor of Science in Physical Therapy (2000), National Cheng Kung University, Taiwan Ph.D. in Biomedical Engineering (2007), National Cheng Kung University, Taiwan (Dissertation: Quantification of Abnormal Muscle Tone in Animal Model and in Clinical Setting) Postdoctoral Research Associate, Rehabilitation Institute of Chicago (now Shirley Ryan Ability Lab) Postdoctoral Research Associate, Neuroscience Department, Brown University Dr. Wu's research program spans neurorehabilitation technology development, with evolving focus from pediatric cerebral palsy interventions to military rehabilitation applications. Her early work pioneered robotic assessment of spasticity mechanisms in children, while recent investigations address human performance limitations during Explosive Ordnance Disposal (EOD) operations with heavy personal protective equipment (PPE). This trajectory demonstrates strategic adaptation from clinical rehabilitation to defense-related human performance optimization, maintaining core expertise in biomechanics and physiological measurement. Current projects integrate exoskeletons, wearable sensors, and AI-driven home rehabilitation systems. Analysis of her publication record reveals three distinct phases: (1) foundational work on spasticity quantification in cerebral palsy (2005-2015), (2) expansion into home-based rehabilitation technologies (2013-2018), and (3) military human performance applications (2018-present). The most recent publications (2021-2024) show strong emphasis on EOD operational ergonomics, exoskeleton integration with PPE, and neurophysiological monitoring for adaptive human-robot collaboration, indicating successful pivot toward Department of Defense funding priorities while maintaining clinical rehabilitation expertise. Faculty Award for Teaching Excellence (2015) Sarah Baskin Award for Excellence in Research (2010) Switzer Fellowship Award (2009) Student Travel Scholarship, American Academy for Cerebral Palsy (2007) Li Foundation Fellow (2005) Podium Paper Award, Biomedical Engineering Society (2003) TiC100 Design Award (2002) Dr. Wu has secured substantial research funding across multiple domains, including $1.2M from the U.S. Army Combat Capabilities Development Command for EOD performance studies, NIH/NIDRR fellowships for cerebral palsy rehabilitation, and industry partnerships with Biogen Idec. Her mentorship includes directing graduate students in the NERVE Center's robotics validation programs, with recent focus on developing AI-driven home rehabilitation systems for children with cerebral palsy. Current projects bridge military and civilian applications through wearable sensor networks and adaptive exoskeleton control systems. As Scientific Lead at the NERVE Center, Dr. Wu directs the Physiological Measurement Core, developing novel methodologies for quantifying human performance under extreme conditions. Her laboratory integrates motion capture, EMG, force sensing, and neuroimaging to evaluate rehabilitation interventions, with recent expansion into EOD operational environments. The HEROES initiative focuses on human-robot teaming for hazardous operations, while SCORE develops sensor-based outcome measures for clinical rehabilitation.

Abe Davisمشاهده پروفایل

استادیار

• Computer Graphics
• Computer Vision
• Human-Computer Interaction (HCI)
• +۳ مورد دیگر

Abe Davis is an Assistant Professor of Computer Science at Cornell University in Ithaca, NY, with a research focus at the intersection of Computer Graphics , Computer Vision , and Human-Computer Interaction (HCI) . He leads a research group that develops innovative computational methods for video analysis, augmented reality (AR), and visual editing. Davis previously held postdoctoral positions at Stanford University and Cornell Tech , following his Ph.D. in Electrical Engineering and Computer Science from MIT (2016) and undergraduate degree in Computer Science at Stanford. Education Ph.D. in Electrical Engineering and Computer Science, MIT M.A. in Electrical Engineering and Computer Science, MIT B.S. in Computer Science, Stanford University Davis' research addresses novel problems in computational video editing, AR applications, and structural health monitoring. His group has made significant contributions to visual vibration analysis , light field reconstruction , and video-based sound recovery . Recent work includes Noise-Coded Illumination for fake video detection and MeCapture for mobile AR body change visualization. His publications span top-tier conferences like SIGGRAPH, CVPR, and CHI. Scientific recognition includes being named to Forbes 30 Under 30 (Science, 2015), 5 TED 2015 Technologists , and recognition as one of The 8 most innovative scientists in tech and engineering (2015). His TED 2015 talk on visual vibration analysis gained international attention. The group's work has been featured in Ars Technica , Engadget , and Cornell Chronicle .

• Reproductive Biology
• Embryology
• Stem Cell Research
• +۵ مورد دیگر

Associate Professor Margot Day is a prominent researcher in the School of Medical Sciences at the University of Sydney, specializing in Physiology. She holds affiliations with the Bosch Institute, the University of Sydney Nano Institute, and the Charles Perkins Centre, focusing on Reproductive, Maternal and Child Health and Lifespan research themes. Her research centers on cellular and molecular mechanisms of embryonic development, with particular expertise in oocyte maturation, preimplantation embryo development, and implantation biology. Professor Day's work explores how amino acids, particularly proline and its analogues, influence embryonic development through various signaling pathways including mTOR and growth factor receptors. She investigates redox regulation, oxidative stress, and nutrient sensing in mammalian embryos, using both in vivo and in vitro models. Analysis of her recent publications reveals a strong focus on amino acid metabolism in embryonic development, with particular emphasis on proline's role in stem cell differentiation and embryo maturation. Her work spans multiple model systems including mouse, bovine, and rat, addressing fundamental questions in reproductive biology with potential applications in assisted reproductive technologies. Professor Day has successfully supervised research students including Kate CAREY, who is working on 'Production of mature oocytes from bovine ovarian tissue in vitro.' She has secured multiple competitive grants from the National Health and Medical Research Council (NHMRC), Australian Research Council (ARC), and University of Sydney to support her research on embryo development, ion transport systems, and circadian rhythms in early embryogenesis. Her laboratory work integrates cellular signaling approaches with molecular physiology to understand the fundamental mechanisms governing early embryonic development and implantation. Professor Day collaborates extensively within the University of Sydney and with international researchers to advance knowledge in reproductive biology and embryology.