جست‌وجوی استاد و پژوهشگر

Fernando Jorge Coutinho Monteiroمشاهده پروفایل

استاد مدعو

• Computer Vision
• Medical Image Analysis
• Biomedical Instrumentation
• +۲ مورد دیگر

Fernando Jorge Coutinho Monteiro is an Adjunct Professor in the Department of Electrical Engineering at Polytechnic Institute of Bragança (IPB), Portugal. He serves as Programme Director for the Biomedical Technology Master's degree and collaborates with INESC TEC's Center for Biomedical Engineering Research. His educational background includes a PhD in Electrical and Computer Engineering from University of Porto (2008). His teaching portfolio includes: Medical Image Processing Medical Imaging Biomedical Image Analysis and Recognition Biomedical Instrumentation Bioelectricity Research focuses on medical technology applications: Computer vision for healthcare diagnostics Medical image analysis algorithms Biomedical instrumentation development Rehabilitation robotics systems AI applications in biological systems Recent publications emphasize deep learning applications in medical imaging, rehabilitation technology, and automated biological analysis. He supervises graduate students in biomedical engineering, electrical engineering, and applied mathematics, including research on rehabilitation systems and medical AI applications.

John M Pleasantsمشاهده پروفایل

دانشیار مدعو

• Monarch Butterfly Conservation
• Ecology
• Agricultural Impact Studies
• +۳ مورد دیگر

Dr. John M Pleasants is an Adjunct Associate Professor at Iowa State University, focusing on monarch butterfly conservation and ecological interactions in agricultural landscapes. His work highlights the critical role of milkweed loss linked to herbicide use in GMO crops as a primary driver of monarch population decline. He collaborates with organizations to restore habitats and has estimated the need for 1.6 billion milkweeds to achieve conservation targets. Education: B.S. in Biology from the University of Notre Dame (1971), Ph.D. in Ecology from UCLA (1977). His research integrates field studies, population modeling, and interdisciplinary approaches to address ecological challenges. Research emphasizes monarch migration biology, habitat restoration strategies, and the impacts of agricultural practices on pollinators. Notable contributions include quantifying milkweed decline in the Midwest and evaluating nectar resource availability for monarch survival. He also explores educational challenges in online proctoring systems. Key projects include the Iowa Monarch Conservation Consortium, advocating for 'all hands on deck' approaches to habitat restoration. His work bridges ecology, conservation policy, and agricultural sustainability.

• Artificial Life
• Ecological Modelling
• Insect-plant interaction
• +۳ مورد دیگر

Alan Dorin is a Professor in the Department of Data Science & AI within the Faculty of Information Technology at Monash University. His research explores ecological modeling, artificial life, and biologically-inspired electronic art. He teaches units including Research and Innovation in Computer Science and Creative Computing. His research bridges computing with biology and ecology through: Insect-plant interaction simulations for sustainable agriculture Generative art systems inspired by biological processes Historical analysis of technology-human relationships Recent publications focus on pollinator behavior analysis, ecological simulation, and applications of computer vision in biodiversity conservation. He leads projects on precision pollination and national pollination strategy development funded by ARC and National Geographic. Dorin serves on multiple faculty committees and is Editor-in-Chief of the Artificial Life journal.

• Machine Learning
• Distributed Systems
• Sensor Networks
• +۷ مورد دیگر

Miloš Stanković is a Professor at the Faculty of Informatics and Computing, Singidunum University. His research focuses on distributed systems, reinforcement learning, machine learning applications, and sensor networks. He has contributed significantly to areas like multi-agent systems, optimization algorithms, and cybersecurity. Recent work includes distributed sensor network calibration, adaptive consensus algorithms, and AI-driven solutions for healthcare and infrastructure monitoring. Education: Not explicitly listed in provided texts. Likely holds advanced degrees in computer science or electrical engineering based on his publications. Research Interests: His primary areas include distributed multi-agent reinforcement learning, metaheuristic optimization for machine learning models, and real-world applications of AI in healthcare, surveillance, and smart infrastructure. He explores topics like sensor fusion, fault detection in networks, and consensus-based algorithms for decentralized systems. Article Trends: Recent publications emphasize AI-driven solutions (e.g., Parkinson’s disease detection via LSTM tuning, student dropout analysis with explainable AI) and distributed algorithms for multi-agent systems. His work bridges theoretical advancements in reinforcement learning with practical applications in sensor networks and cybersecurity. Grants/Projects: Not explicitly detailed, but involvement in EU-funded projects like Sinteza and SITCON conferences suggests external funding. Labs/Teams: Likely part of Singidunum’s research groups in AI, distributed systems, and cybersecurity. Collaborates with institutions like KTH Royal Institute of Technology (via co-author K.H. Johansson) on sensor networks and control systems.

Christina Grozingerمشاهده پروفایل

استاد

• Social Behavior in Insects
• Pollinator Health
• Ecology
• +۷ مورد دیگر

Christina Grozinger is the Publius Vergilius Maro Professor of Entomology and Director of the Center for Pollinator Research at Pennsylvania State University's College of Agricultural Sciences. She leads a lab focusing on social behavior, health, and ecological interactions of bees, employing integrative approaches from genomics to AI. Her research explores seasonal adaptations, plant-pollinator co-evolution, and intragenomic conflict in social insects. Grozinger holds fellowships from the Entomological Society of America and AAAS, and has received the 2021 NAS Prize in Food and Agriculture Sciences. She advises numerous graduate students and collaborates across disciplines, contributing to pollinator conservation through the Living Systems Center and Beescape NexGen tools. Her work spans 9 Penn State colleges, emphasizing cross-disciplinary solutions for pollinator health. Education: B.Sc. in Chemistry/Biology (McGill), M.Sc. & Ph.D. (Harvard) Key Affiliations: Huck Institutes of the Life Sciences, FRESCO Programme (External Fellow) Research Interests: Social behavior mechanisms in honey bees Seasonal physiology and diapause Plant-pollinator nutritional interactions Epigenetic regulation of behavior Grants & Awards: $42.2M in grants, leadership in USDA-funded projects, and recognition for academic integration.

Andrew Barronمشاهده پروفایل

استاد

• Neuroscience
• Animal Behavior
• Ecology
• +۳ مورد دیگر

Andrew Barron is a Professor in the School of Natural Sciences at Macquarie University and Director of the Macquarie Minds and Intelligences Initiative. He specializes in neuroethology, focusing on the neural mechanisms of animal behavior, particularly in insects like honey bees. His research explores cognition, navigation, social behavior, and learning in insects, alongside efforts to improve honey bee health amid environmental stressors such as pesticides and climate change. Affiliations: Frontier AI Research Centre, Macquarie University External Roles: Australian Research Council Future Fellow (2015–2022), President of Australasian Society for the Study of Animal Behaviour (2012–2014) Education: PhD in Zoology, University of Cambridge (1995–1999) First Class Honours in Natural Sciences, University of Cambridge (1992–1995) Research Interests: Barron’s work bridges neuroscience and ecology to understand animal cognition, model insect brain function, and address honey bee health crises. He investigates how insects process information and adapt to environmental pressures, with implications for conservation and artificial intelligence. Key projects include studying pesticide impacts on bee cognition and developing best practices for bee health technology. Recent Articles: His recent work focuses on metallic pollution effects on bee brains, cognitive evolution across species, and foraging behavior under environmental stress. These studies highlight interdisciplinary approaches combining fieldwork with computational modeling. Awards: Australian Award for University Teaching (2012), Excellence in Research (2014) Grants & Projects: Leads initiatives like ‘Protecting vulnerable Australian honey bees’ and collaborates on AI-natural intelligence comparisons. He has secured over AUD 6 million in research funding. Labs/Teams: Heads the Barron Lab, focusing on neuroethology and applied pollinator research. Collaborates internationally on projects like the ‘Connectomic Revolution’ and ‘Swarm Architecture in Ants’.

• Quantum Optics
• Quantum Information
• Diamond
• +۳ مورد دیگر

Professor Andrew Greentree is a theoretical physicist at RMIT University, specializing in quantum physics, diamond-based technologies, and neurocognition in insects. He holds the position of Professor in the School of Science and is a Chief Investigator in the ARC Centre of Excellence for Nanoscale BioPhotonics. His roles include teaching, research coordination for Higher Degree Research (HDR) in Physics, and involvement in RMIT's ERA submission and Research Integrity Advisory Network. Research interests span quantum optics, quantum information, diamond magnetometry, and the cognitive abilities of bees. Notable achievements include pioneering the Jaynes-Cummings-Hubbard Model and spatial adiabatic passage, leading to novel quantum devices. Collaborations include work with Prof. Brant Gibson on diamond-glass hybrid materials and Prof. Adrian Dyer on bee numerical cognition. Greentree has developed advanced magnetometry techniques and contributed to understanding bees' ability to perform arithmetic, published in high-impact journals like Science . Awards: RMIT Award for Research Excellence (2019), ARC Future Fellow (2017), Fellow of the Institute of Physics (2012). Advising: Supervises PhD projects in quantum AI, diamond magnetometry applications, and bee cognition. Lab/Teams: ARC Centre of Excellence for Nanoscale BioPhotonics, Theoretical Chemical and Quantum Physics Group.

• Nanoparticle Drug Delivery Systems
• Stem Cell Biology
• Metabolomics
• +۵ مورد دیگر

Mohammad Al-Natour, PhD is a Postdoctoral Research Scholar at the University of Iowa's College of Pharmacy, affiliated with the Department of Pharmaceutical Sciences and Experimental Therapeutics. His research focuses on nanoparticle design for drug delivery, stem cell biology, and metabolomics analysis in biomedical applications. Dr. Al-Natour holds a PhD in Pharmaceutical Sciences. His work integrates nanotechnology, biomaterials science, and analytical techniques like LC-MS/MS to investigate drug delivery mechanisms, cellular responses to nanoparticles, and metabolic pathways in disease models. His research interests include: Development of targeted nanomedicines for cancer therapy Stem cell interactions with engineered biomaterials Metabolomics-based evaluation of nanoparticle toxicity Optimization of polymer-based drug delivery systems Publications highlight trends in: Nanoparticle surface functionalization for targeted drug delivery Metabolomic profiling of cellular responses to therapeutics Biomaterial design for dental and regenerative medicine applications Preclinical evaluation of drug-nanoparticle interactions No scientific awards or grants are listed in his profile. His work contributes to advancing translational nanomedicine and drug delivery technologies.

Amanda Licznerمشاهده پروفایل

پژوهشگر ارشد

• Behavioral Ecology
• Conservation Biology
• Landscape Ecology
• +۳ مورد دیگر

Amanda Liczner is a postdoctoral research fellow at the University of Guelph under Dr. Nigel Raine, focusing on behavioral ecology and conservation biology. Her research investigates environmental stressors' impacts on bumble bee movement, habitat use, and conservation priorities. She employs radiotelemetry, detection dogs, and landscape modeling to study pollinator health and ecosystem dynamics. Education: Ph.D. in Ecology (York University, supervised by Dr. Sheila Colla), MSc and BSc in Ecological Sciences. Previous postdoctoral work at the University of British Columbia Okanagan addressed connectivity conservation. Research spans bumble bee habitat requirements, pesticide effects, pathogen spillover risks, and urban pollinator dynamics. Key research themes include: Pesticide impacts on flight behavior and sublethal effects Nesting and overwintering habitat identification Climate change adaptation for at-risk species Urban garden efficacy for native pollinators Pathogen spillover risk mitigation Her work integrates field studies, statistical modeling, and applied conservation strategies to inform management practices. Collaborations include large-scale projects on ecological connectivity and disease risk assessment across Canada.

Cristiano Palegoمشاهده پروفایل

مدرس ارشد

• Microwave Engineering
• Biosensors
• Machine Learning Applications in Biology
• +۶ مورد دیگر

Dr. Cristiano Palego is a Senior Lecturer in Microwave Instrumentation at the School of Computer Science and Engineering, Bangor University. His research bridges microwave engineering, biosensor development, and environmental monitoring, with a focus on insect telemetry and cancer cell analysis. Key affiliations: SUMCASTEC (EU-funded), KESS II (PhD projects), and collaborations with S&A Fresh Produce Ltd and Cardiff University. Research Interests span microwave biosensors for cellular analysis, machine learning in insect behavior classification, and electromagnetic interactions with cancer stem cells. His work addresses UN Sustainable Development Goals in environmental conservation and health innovation. Scientific Contributions include advancements in: Microwave-based bee-tracking systems Glioblastoma organoid exposure studies MEMS phase shifters for biomedical applications Dielectrophoretic cell discrimination Recent Publications (2022–2024) highlight trends in integrating machine learning with microwave and radar systems for: Honeybee behavior classification Automated pollination monitoring High-frequency cancer cell analysis Awards & Recognition include contributing to Bangor University's 2023 Queen's Anniversary Prize-winning research on societal impact. Supervision : Open to advising PhD students in microwave biosensing, entomology, and biomedical device development.

Stephen Goodمشاهده پروفایل

دانشیار

• Ecohydrology
• Remote Sensing
• Isotope Biogeochemistry
• +۳ مورد دیگر

Dr. Stephen Good is an Associate Professor in the Department of Biological & Ecological Engineering at Oregon State University (OSU). He holds a Ph.D. in Civil and Environmental Engineering from Princeton University (2013), an M.S. in Civil Engineering from Michigan Technological University (2008), and a B.S. in Mechanical Engineering from Carnegie Mellon University (2004). His research focuses on ecohydrology, remote sensing, and isotope biogeochemistry, with applications in understanding water cycling, vegetation dynamics, and environmental monitoring. Dr. Good has led major projects funded by NASA, NSF, and the Agricultural Research Foundation, addressing topics such as satellite-based water use efficiency, ecohydrological separation, and microbial hydrologic data encoding. His teaching includes courses like BEE 313 (Ecohydrology), BEE 433/533 (Irrigation System Design), and BEE 512 (Physical Hydrology). He advises students such as Dawn Urycki and Catherine Finkenbiner, contributing to their research in hydrology and environmental engineering. Dr. Good has received notable awards, including the U.S. Fulbright Scholar (2022) and the Young Investigator Award (2011). His work integrates machine learning, stable isotopes, and microbial genomics to advance hydrological understanding and sustainable resource management. Key research outputs include the NEON Daily Isotopic Composition of Environmental Exchanges (NEON-DICEE) dataset and studies on river microbiome dynamics. He collaborates widely, with recent projects exploring precision irrigation, solar energy optimization over croplands, and continental-scale ecohydrological modeling.

• Plant Ecological Genetics
• Evolutionary Genetics
• Climate Change Adaptation
• +۵ مورد دیگر

Professor Andrew Lowe is a leading academic and director of the University of Adelaide's Environment Institute, part of the Division of Research and Innovation. He holds a PhD in Plant Evolutionary Biology from the University of St Andrews (1997) and became a full professor in 2006. His research spans plant ecological genetics, climate change adaptation, and timber tracking technologies. He has secured over $250M in funding and published over 250 papers, with an h-index of 75. Key roles include Science Director of the Fight Food Waste Cooperative Research Centre and leadership in national and international environmental initiatives. Research interests focus on genetic structure of plant populations, climate resilience, and biodiversity conservation. Recent work highlights include the Periodic Table of Food Initiative and advancements in DNA-based timber tracking. Dr. Lowe also engages in public science communication through media articles, podcasts, and TEDx talks. His leadership spans academia, government, and start-ups, including his role as Chief Scientific Officer of Double Helix Tracking Technologies. Advising over 120 graduate students and technical staff, he emphasizes collaborative research and policy impact. Major projects include restoring degraded landscapes and combating illegal logging through scientific innovation. His work integrates ecological genomics with real-world applications, addressing global challenges in sustainability and biodiversity.

Gene E. Robinsonمشاهده پروفایل

استاد

• Social Behavior
• Genomics
• Molecular Biology
• +۳ مورد دیگر

Gene E. Robinson is a Professor of Entomology and Director of the Carl R. Woese Institute for Genomic Biology at the University of Illinois at Urbana-Champaign. He holds a Swanlund Chair and multiple affiliate appointments across disciplines. His research uses genomic and systems biology approaches to study social behavior in honey bees, focusing on mechanisms of division of labor, aggression, and communication. Robinson pioneered genomics in social behavior research and led the honey bee genome sequencing effort. Education: B.A. and Ph.D. in Entomology from Cornell University (1986). Awards include the Wolf Prize in Agriculture, Guggenheim Fellowship, and membership in the National Academy of Sciences. He has trained over 35 postdoctoral researchers and 25 doctoral students, with many advancing to academic and industry roles. Research emphasizes integrative studies of social evolution, including gene regulatory networks and brain plasticity. Notable contributions include linking honey bee social behavior to autism-related genes and developing technologies for monitoring bee behavior. Current projects explore gut microbiota effects on foraging, nutritional regulation of behavior, and automated bee tracking using RFID. Awards: Over $70M in research grants, including NIH, NSF, and CZ Biohub support. Serves on National Academy committees and scientific advisory boards. Labs include the Robinson Lab and Carl R. Woese Institute, focusing on genomic and behavioral studies of social insects.

Tuğrul TAŞCIمشاهده پروفایل

استادیار

• Artificial Intelligence
• Natural Language Processing
• Computer Vision
• +۳ مورد دیگر

Tuğrul TAŞCI serves as an Assistant Professor in the Department of Information Systems Engineering at Sakarya University's Faculty of Computer and Information Sciences, where he has maintained continuous academic service since 2001. His career progression includes Research Assistant positions across multiple university units before advancing to his current faculty role in 2016. His academic credentials include: Doctorate in Computer and Information Engineering (2014) from Sakarya University Institute of Science, thesis: Real-Time Motion Tracking with Particle Filtering Based on Data Fusing Master's degree in Computer and Information Engineering (2004) with thesis: Design of an Integrated Web-Based Distance Education System Bachelor's degree in Computer Engineering (2001) with thesis: Course Scheduling with Genetic Algorithms Dr. TAŞCI's research centers on Artificial Intelligence applications, particularly Natural Language Processing for Arabic text and Computer Vision . His work integrates particle filtering , data fusion , and optimization algorithms (e.g., Artificial Bee Colony, Firefly) to solve problems in text summarization, motion tracking, and image processing. Recent publications demonstrate expansion into deep learning for industrial defect detection and time series analysis. Analysis of his 2019-2024 publications reveals three dominant research trajectories: (1) Arabic NLP with focus on extractive summarization using PageRank and word embeddings, (2) Computer vision systems for motion tracking and text detection leveraging particle filters and curvature features, and (3) Hybrid optimization techniques applied to diverse domains from emergency management to customer churn prediction. Current academic advising activities and research grant details are not publicly documented in available sources. Similarly, no institutional laboratories or research teams are explicitly associated with his profile in the provided materials.

Bernhard Höfleمشاهده پروفایل

استاد

• Geoinformatics
• 3D Point Cloud Analysis
• Environmental Monitoring
• +۵ مورد دیگر

Prof. Dr. Bernhard Höfle is a Professor of Geoinformatics and 3D Geospatial Data Processing at the University of Heidelberg, where he leads the 3DGeo Research Group. His work focuses on computational methods for analyzing 3D/4D point clouds, with applications in environmental monitoring, natural hazard assessment, and vegetation studies. Research Interests: 3D/4D point cloud analysis for environmental observation Development of computational algorithms for geospatial data Integration of machine learning in remote sensing applications Virtual laser scanning simulations (VLS-4D) Real-time monitoring systems for critical infrastructure Digital Twin integration across scales Article Trends: His recent publications emphasize real-time 3D environmental monitoring, virtual simulation of dynamic scenes, multi-temporal analysis of natural processes, and machine learning applications for point cloud classification. They span from 2025 back to 2023 and cover diverse applications including rock glaciers, forest monitoring, building damage assessment, and bee activity tracking. Key Techniques: His work prominently features terrestrial laser scanning, UAV-based LiDAR, and open-source software development. He has contributed datasets like FOR-species20K and developed simulation frameworks such as HELIOS++.