جست‌وجوی استاد و پژوهشگر

• Ecology
• Parasitology
• Animal Behavior
• +۴ مورد دیگر

Dr. Claire Fuller currently serves as Dean of the Jones College of Science, Engineering, and Technology and Professor of Biological Sciences at Murray State University. She holds a BA in General Biology from the University of California, San Diego, and MS/PhD in Zoology from Oregon State University under Dr. Andrew Blaustein. Her research focuses on ecological immunology, parasitism in social insects (e.g., termites), and environmental impacts on animal behavior and population dynamics. Research interests include: Parasite-host interactions in tropical termites Climate change effects on termite immunity Aquatic pollution impacts on dragonfly immunity Behavioral modifications induced by parasites Recent publications highlight work on Atrazine effects in dragonflies (2018), termite environmental adaptations (2014), and acanthocephalan parasite impacts (2003-2004). Funding sources include NSF, Howard Hughes Institute, and Kentucky EPSCOR grants. Advises numerous graduate/undergraduate researchers and collaborates with institutions like Northeastern University. Active in teaching courses such as Animal Behavior, Biological Inquiry, and Ecology.

Victoria Andreasenمشاهده پروفایل

پژوهشگر

• Wildlife Disease
• Veterinary Pathology
• Mitochondrial Physiology
• +۳ مورد دیگر

Victoria Andreasen is a Researcher in the Department of Population Health at the University of Georgia's College of Veterinary Medicine, affiliated with the Southeastern Cooperative Wildlife Disease Study (SCWDS). Her research focuses on wildlife health, mitochondrial physiology, and the impacts of stress and infection on animal systems. She specializes in investigating diseases affecting wildlife populations, including parasitic, fungal, and bacterial infections, with a particular emphasis on avian and mammalian species. Her work integrates pathology, ecology, and physiology to understand disease dynamics in natural populations. Notable areas include toxoplasmosis in lagomorphs, aspergillosis in birds, and the physiological consequences of stress during reproduction. Her recent studies highlight mitochondrial function as a key determinant of stress resilience and disease outcomes. Andreasen’s articles reflect a multidisciplinary approach to wildlife health, with trends in analyzing pathogen impacts, stress physiology, and avian health. Her research contributes to both diagnostic advancements and conservation efforts. She collaborates with SCWDS to address wildlife disease surveillance at regional and national scales. While no formal advisees are listed, her involvement in research labs and field studies suggests active engagement with student researchers. Grants and funding sources are not detailed in the provided information.

• Biomedical Engineering
• Medical Imaging
• Nanophotonics
• +۳ مورد دیگر

Young Kim is a Professor of Biomedical Engineering at Purdue University's College of Engineering, with affiliations in the Global Engineering Program. Their research focuses on integrating nanophotonics, biomedical optics, and wearable health technologies. Key areas include non-invasive blood hemoglobin assessments via smartphone-based imaging, photonic nanomaterials for medical applications, and biomimetic optical systems inspired by natural materials like silk. Kim has pioneered technologies such as mHealth diagnostics for anemia and malaria, quantum-based security apparatuses, and machine-learning-enabled wearable sensors for dietary monitoring. Education details are not explicitly provided, but their work demonstrates expertise in interdisciplinary biomedical engineering. Research interests emphasize translating optical and material innovations into clinical tools, with a focus on global health equity through accessible diagnostics. Over 15 recent publications span advancements in spectral imaging, wearable health solutions, and security systems leveraging optical physics. No specific awards are listed, but their contributions to mHealth and nanophotonics reflect impactful work in the field. Advising and grants are not detailed here, but their active research portfolio suggests involvement in funding initiatives. Lab activities likely center on biomedical optics, wearable technology development, and biomaterials engineering with applications in diagnostics and security.

• Signal Processing
• Image Processing
• Machine Learning
• +۷ مورد دیگر

Jian Qiu Zhang is a Professor at Fudan University in the School of Information Science and Technology , affiliated with the Key Laboratory for Information Science of Electromagnetic Waves and Research Center of Smart Networks and Systems in Shanghai, China. Previously, he was at the University of Greenwich (1999-2002) and earned his PhD in 1996 from Harbin Institute of Technology in the Department of Electrical Engineering . His research interests span Signal Processing , Image Analysis , and Machine Learning , with a focus on applications in Biomedical Imaging , Hyperspectral Data Analysis , and Smart Network Systems . His work often integrates Wavelet Transforms , Tensor Decomposition , and Bayesian Filtering to solve complex problems in Medical Imaging and Wireless Sensor Networks . Recent publications highlight advancements in Deep Learning for 3D Ultrasound , PARAFAC Decomposition , and Graph Neural Networks for Hyperspectral Classification . His technical contributions include Adaptive Filtering Algorithms , Nonlinear Unmixing , and Wavelet-Based Sensor Analysis . Key collaborations include researchers from institutions such as Harbin Institute of Technology, University of Greenwich, and international teams in IEEE Transactions and IGARSS conferences.

• Computer Science
• Machine Learning
• Medical Imaging
• +۵ مورد دیگر

Hong Liu is a Professor at Shandong University's School of Computer Science and Technology, with an extensive publication record spanning multiple disciplines within computer science and engineering. His research spans computer vision, machine learning, medical imaging, robotics, and signal processing, with over 500 publications listed in the dblp database from 1993 to 2025. Dr. Liu's research interests focus on the intersection of artificial intelligence and practical applications across various domains. His recent work demonstrates expertise in deep learning architectures, medical image analysis, robotics navigation, and computer vision systems. He has made significant contributions to medical imaging techniques, particularly in segmentation methods using quaternion mathematics and self-attention mechanisms, as well as applications in liver disease diagnosis and pediatric fracture detection. The publication trends show increasing activity in recent years, with substantial contributions in 2023-2025 across IEEE journals and conferences. His work frequently appears in high-impact venues including IEEE Transactions on Medical Imaging, IEEE Access, and Pattern Recognition, demonstrating both theoretical rigor and practical applications. His research bridges theoretical computer science with real-world engineering and medical challenges, particularly in China's healthcare and technology sectors. Dr. Liu has collaborated extensively with researchers across Chinese institutions including Shandong University, Harbin Institute of Technology, and Huazhong University of Science and Technology, as well as international partners. His work shows strong interdisciplinary connections between computer science, electrical engineering, and medical applications.

BUKET TOPTAŞمشاهده پروفایل

مدرس

• Machine Learning
• Medical Imaging
• Deep Learning
• +۶ مورد دیگر

Buket Toptaş is a Lecturer at the Department of Software Engineering, Faculty of Engineering and Natural Sciences at Bandırma Onyedi Eylül University. She previously served as a Research Assistant (2019–2022) before transitioning to her current role. Her research focuses on machine learning, medical imaging, deep learning, and image processing, with applications in healthcare diagnostics and biomedical engineering. She has contributed to projects such as the Early Diagnosis of Diabetic Retinal Aneurysms with Retinal Image Analysis , completed in 2022. Her academic duties include teaching courses like Machine Learning, Data Mining, and Image Processing at both undergraduate and graduate levels. She is currently supervising a Master’s thesis on Colonoscopic Image Polyp Segmentation with Yaren Akgöl. Her work spans over 30 publications in journals like Soft Computing , Biomedical Signal Processing and Control , and IEEE Access , with a focus on retinal imaging, polyp detection, and algorithm optimization. Her conference contributions include papers on optimization algorithms (e.g., Biogeography-Based Optimization) and flame detection systems. She actively participates in university research projects and maintains an extensive portfolio of peer-reviewed articles addressing challenges in medical image analysis and deep learning.

• Wireless Communications
• Signal Processing
• Image Steganography
• +۵ مورد دیگر

Dr. Peter Vial is a Senior Lecturer at the School of Electrical, Computer and Telecommunications Engineering, University of Wollongong. He holds a PhD in Electrical Engineering and has over three decades of experience in academia and industry. His academic journey includes a Bachelor's (1987), Master's (1997), and PhD (2009) from the University of Wollongong. Before academia, he worked at BHP Steel (1981-1991) and transitioned into teaching roles from 1992, becoming a Lecturer in 2004 and Senior Lecturer in 2022. Research Interests: Dr. Vial’s work focuses on wireless communication systems, including MIMO, spread spectrum, and ultra-wideband (UWB) technologies. He also explores signal processing applications in medical imaging (e.g., capsule endoscopy), steganography, energy harvesting, and robotics. His research integrates machine learning and embedded systems for practical solutions in healthcare, telecommunications, and sensor networks. Teaching & Supervision: Dr. Vial teaches courses in telecommunications, digital signal processing, and electronics. He has led laboratory development in embedded systems and supervised over 15 postgraduate students, including current PhD candidates in Delay Tolerant Networks (DTN), 60GHz Ad Hoc networks, and UWB channel measurements. His supervision spans topics like AI-driven sign language recognition, steganography, and energy-efficient generator design. Grants & Funding: He led an internal grant (2008-2009) developing an immersive learning platform for microcontroller education. His research has been supported by institutional funding, with outputs published in journals like Neurocomputing , Signal Processing , and IEEE Sensors . Labs & Teams: Dr. Vial has developed engineering laboratories in embedded Internet systems, telecommunications, and digital signal processing. He collaborates with industry partners and interdisciplinary teams on projects combining hardware/software systems for healthcare, energy, and robotics.

Rikkert Frederixمشاهده پروفایل

مدرس ارشد

• High-Energy Particle Physics
• LHC Phenomenology
• Quantum Chromodynamics (QCD)
• +۳ مورد دیگر

Rikkert Frederix is a Senior Lecturer at Lund University's Department of Physics, Faculty of Science. His research focuses on high-energy particle physics phenomenology, particularly at the Large Hadron Collider (LHC). He specializes in improving theoretical predictions for LHC processes using advanced event generators like MadGraph5_aMC@NLO, aiming to resolve discrepancies between data and theory, enhance prediction accuracy, and explore beyond the Standard Model physics. Research interests include precision calculations of top quark pair production, electroweak corrections, and Monte Carlo methods for event generation. His work addresses algorithmic challenges such as negative weight reduction in NLO matching and optimization for high-luminosity LHC conditions. Publications span topics like tt̄ production dynamics, Z-boson angular coefficients, and software frameworks for collider physics. Collaborations emphasize interdisciplinary approaches between theory and experimental data analysis.

• Digital Image Processing
• Signal Processing
• Soft Computing
• +۵ مورد دیگر

Prof. Annamária Várkonyiné Kóczy is a Professor at the Department of Informatics within the Faculty of Economics and Informatics at J. Selye University. She holds a joint appointment as a professor at Óbuda University's Institute of Software Design and Software Development. Her academic journey includes: Electrical Engineering studies (Measurement and Control) at Technical University of Budapest (1975-1981) Mechanical Engineering degree (Mechanical Engineer-Teacher) from the same institution (1978-1983) PhD in Computer Science from Technical University of Budapest (1996) DSc (Doctor of Sciences) from Hungarian Academy of Sciences (2010) Habilitation from Széchenyi István University (2017) Her research spans digital signal processing, soft computing, and hybrid techniques for complex systems, with applications in medical diagnostics, intelligent control, and sustainable technologies. She leads projects in computational intelligence and has developed novel algorithms for real-time processing in resource-constrained environments. Recent publications demonstrate strong focus on AI-driven solutions: machine learning for bioacoustic analysis (beehive swarming), fuzzy logic optimizations for edge computing, medical imaging diagnostics (COVID-19 detection), and sustainable energy control systems. Her work consistently bridges theoretical models with practical implementations in healthcare, environmental monitoring, and industrial diagnostics. She has secured multiple research grants including: OTKA K 105846: Intelligent Space and robotics (2012-2017) OTKA K 78576: Intelligent techniques in signal/image processing (2009-2013) GVOP-3.3.1: Intelligent 3D modeling systems (2006-2007) EU Structural Funds projects on vehicle industry collaborations She mentors graduate researchers in applied informatics and leads international collaborations across Europe and Asia, focusing on intelligent systems development.

Joseph P. Havlicekمشاهده پروفایل

استاد

• Signal Processing
• Image Processing
• Video Processing
• +۷ مورد دیگر

Dr. Joseph P. Havlicek is the Gerald Tuma Presidential Professor in the Gallogly College of Engineering at the University of Oklahoma, where he has served since 1997. He directs the OU Center for Intelligent Transportation Systems and is a full member of the OU Institute for Biomedical Engineering, Science, and Technology. His extensive career spans both academic and professional realms, with significant contributions to signal processing, image analysis, and transportation systems. His educational background includes: BS in Electrical Engineering from Virginia Tech (1986) MS in Electrical Engineering from Virginia Tech (1988) PhD in Electrical and Computer Engineering from the University of Texas at Austin (1996) Dr. Havlicek's research spans multiple domains including signal, image, and video processing; modulation domain signal processing; target tracking; medical imaging; and intelligent transportation systems. His work bridges theoretical signal processing with practical applications in healthcare and transportation. He has pioneered techniques in AM-FM signal and image modeling, uncertainty measures, and developed innovative approaches for medical image analysis and infrared target tracking. Analysis of his recent publications reveals a strong interdisciplinary trend, with significant work at the intersection of signal processing and medical imaging, particularly in bone marrow assessment and cancer treatment monitoring using PET/CT imaging. His computer vision research focuses on infrared object detection and tracking, with recent work on dual-band infrared systems improving small object detection. The publications also demonstrate his continued theoretical contributions to signal processing, particularly in modulation domain techniques and entropy-based uncertainty measures. His scientific achievements have been recognized with numerous awards: University of Oklahoma Outstanding Faculty Advisor Award (2006) University of Oklahoma College of Engineering Brandon H. Griffith Faculty Award (2003) University of Oklahoma IEEE Favorite Instructor Award (1998, 2000) Department of the Navy Award of Merit for Group Achievement (1990) University of Texas Engineering Foundation Award for Exemplary Engineering Teaching (1992) Dr. Havlicek has been exceptionally successful in securing research funding, serving as PI or co-PI on more than 100 externally funded grants and contracts totaling over $25 million. His professional service includes editorial positions with IEEE Transactions on Image Processing and IEEE Transactions on Industrial Informatics, as well as leadership roles in major conferences including ICIP and ICASSP. He has chaired both graduate and undergraduate studies committees in the ECE department. He leads the OU Center for Intelligent Transportation Systems, which develops advanced technologies for traffic management and traveler information systems. His biomedical engineering work through the OU Institute focuses on medical image analysis, particularly for cancer treatment monitoring and bone marrow assessment. His research teams regularly collaborate with medical institutions to translate signal processing techniques into clinical applications.

• Physical Layer Security
• 6G Network Security
• Wireless Communications
• +۲ مورد دیگر

Dr. Simone Soderi is an Assistant Professor at IMT School for Advanced Studies Lucca within the SySMA research unit, with additional adjunct appointments at the University of Padua and University of Oulu. He holds a doctoral degree from the University of Oulu specializing in industrial wireless communications security. Research focuses on cybersecurity for hybrid wireless systems including physical layer security for 6G networks, optical wireless communications security, covert channel detection, and critical infrastructure protection. Recent projects investigate RIS-aided visible light communication security, federated learning vulnerabilities, and railway cybersecurity frameworks. Professional service includes Senior IEEE membership, editorial roles for IEEE Transactions on Information Forensics and Security, and coordination for national cybersecurity initiatives. Teaching encompasses graduate courses on security in hybrid wireless communications and risk management certifications. Patent portfolio includes innovations in vehicular communication security and distance estimation systems. Laboratory activities involve the CINI National Laboratory for Cybersecurity and collaborations within international research consortia including COST Action CA22168 for 6G physical layer security.

• Insect Physiology
• Behavioral Ecology
• Thermal Biology
• +۷ مورد دیگر

Goggy Davidowitz is a Professor in the Department of Entomology at the University of Arizona. His research focuses on insect physiology, behavioral ecology, and evolutionary adaptations, particularly in pollinators and their interactions with environmental factors such as temperature, humidity, and resource availability. His work explores topics like thermal tolerance, melanin pigmentation plasticity, nectarivory strategies, and the impacts of habitat fragmentation on insect physiology. Davidowitz's research spans diverse areas including the physiological costs of melanin production, the role of nectar resources in flight performance and oxidative stress mitigation, and the ecological implications of insect body size. His studies often integrate field observations with controlled laboratory experiments to understand how insects adapt to environmental challenges, particularly in arid and warming climates. Notably, he has investigated how insects prioritize resource allocation between growth, reproduction, and survival under varying conditions, including the trade-offs between flight energy expenditure and fecundity. His work also addresses applied topics such as using insect physiology to improve pest management strategies and exploring the viability of insects as sustainable protein sources. Davidowitz has received grants for collaborative projects, including studies on thermal limits in aquatic insects and the effects of landscape fragmentation on physiological trade-offs. His research has been published in leading journals and has contributed to broader discussions on climate change impacts on ecological mutualisms.

• Ecology
• Evolutionary Biology
• Biodiversity Patterns
• +۳ مورد دیگر

Gopal Murali is a Postdoctoral Research Associate and Affiliated Faculty at the University of Arizona's Wiens Lab. His research focuses on ecology, evolution, and biodiversity patterns, particularly under environmental changes. He holds a PhD in Ecology and Evolution from the Indian Institute of Science Education and Research (IISER) Thiruvananthapuram, preceded by an M.S. in Biology and a B.Tech. in Bioengineering. Research Interests: Murali applies macroecological and macroevolutionary frameworks to study biodiversity dynamics. His work addresses how climate change impacts species distributions, thermal tolerances, and predator-prey interactions. Key themes include evolutionary rarity, habitat heterogeneity effects, and global threats to vertebrates. Publications highlight contributions to understanding sexual dimorphism, viviparity in cold climates, and the role of temperature extremes in biodiversity loss. His work bridges theoretical models with field observations, emphasizing conservation implications. Labs/Teams: Active in the Wiens Lab, focusing on integrative ecology and evolution. Collaborates globally, including with researchers at Ben-Gurion University and institutions in India.

Brenda Bradleyمشاهده پروفایل

استاد

• Evolutionary genomics
• Molecular anthropology
• Comparative primate genomics
• +۶ مورد دیگر

Brenda Bradley is Professor of Anthropology and Core Faculty at the Center for the Advanced Study of Human Paleobiology (CASHP) within George Washington University. Her lab is located at SEH 6100, and she can be contacted via office phone at (202) 994-2391. Education includes: Ph.D. in Anthropological Sciences (2003) from Stony Brook University M.A. (1998) from Stony Brook University B.A. (1995) from Arizona State University Dr. Bradley's research bridges behavioral ecology and evolutionary genomics, focusing on: Comparative primate genomics and molecular anthropology Sensory ecology including color vision and pigmentation Evolutionary mechanisms of hair/fur variation in primates Population genetics and molecular ecology She currently co-leads an NSF-funded project investigating proximate and ultimate mechanisms of primate pelage evolution. Her recent publications (2022-2025) demonstrate strong interdisciplinary focus, with major themes in: Primate epigenetics and neurogenetics Canine cognition and human-animal communication X-chromosome evolution and disease susceptibility Integrative approaches to morphological variation Teaching responsibilities include: Anth 2406: Human Evolutionary Genetics Anth 6491: Topics in Anthropological Genetics Homp 6202: Lab Techniques in Paleoanthropology

Marcus A Brubakerمشاهده پروفایل

دانشیار

• Computer Vision
• Machine Learning
• Statistics
• +۳ مورد دیگر

Marcus A Brubaker is an Associate Professor of Computer Science at York University in Toronto and a Faculty Affiliate at the Vector Institute. He also serves as a Status-only Professor at the University of Toronto and conducts research consulting for Samsung AI Centre and Borealis AI in Toronto. His work focuses on interdisciplinary applications of machine learning, computer vision, and statistics, particularly in computational biology, medical imaging, and sensor systems. Brubaker's research interests include developing novel algorithms for 3D reconstruction (e.g., neural radiance fields), cryo-electron microscopy (Cryo-EM) analysis, noise modeling, and generative models. He has contributed significantly to methods like dynamic normalizing flows for stochastic processes, geometry-aware diffusion models, and text-guided image editing techniques. His work bridges theoretical machine learning with practical applications in bioimaging and computer graphics. His publications span over two decades, with recent trends emphasizing Bayesian methods, efficient neural network architectures, and multi-view scene understanding. Brubaker collaborates extensively with industry partners (e.g., Samsung AI) and academic institutions to advance AI-driven solutions in microscopy, image processing, and 3D modeling. Brubaker’s research has led to impactful tools like cryoSPARC for Cryo-EM structure determination and Wavelet Flow for high-resolution image analysis. He actively engages in academic outreach, as evidenced by his participation at ICCV2023 and mentorship of early-career researchers.