جست‌وجوی استاد و پژوهشگر

• Physical Geography
• Soil Erosion
• Hydrology
• +۷ مورد دیگر

Artemio Cerda Bolinches is a Professor in the Department of Geography at the Faculty of Geography and History, University of Valencia, Spain. His academic work centers on Physical Geography, with a strong emphasis on soil erosion, hydrological processes, land degradation, and wildfire impacts. He leads the SEDER (Soil Erosion Rates and Runoff Generation) research group, reflecting his leadership in environmental process studies. His educational background includes a PhD from the Universitat de València in 1993, with a thesis on soil infiltration in the Valencian region, supervised by Dr. Adolfo Calvo Cases. This foundational research has evolved into a prolific career in geomorphology and environmental change. Cerda Bolinches’ research interests span soil erosion dynamics , wildfire-soil interactions , sustainable land management , and Mediterranean environmental systems . His work integrates field experiments, modeling, and global meta-analyses, often using GIS and machine learning to analyze spatial patterns of erosion and degradation. He explores biological influences on hydrology, post-fire recovery, and nature-based solutions for flood and erosion control. His recent publications (2022–2025) reveal a strong trend in interdisciplinary environmental science, with frequent studies on machine learning applications in soil mapping, fire impacts on hydrology, and sustainability in agricultural systems. His work spans regions including Spain, Iran, China, Ethiopia, and Bangladesh, indicating broad international collaboration and relevance. While no specific scientific awards are listed in the provided text, his leadership in special issues and editorial contributions (e.g., introducing FIRElinks and fire-hydrology special issues) highlights recognition in the academic community. He is actively involved in advising and research supervision, implied by his PhD and research group leadership. His projects often address applied environmental problems, including soil conservation in vineyards, wildfire management, and climate change adaptation. He has contributed to policy-relevant studies, such as the EU Soil Observatory’s role in erosion monitoring. Cerda Bolinches is affiliated with the SEDER research group, which conducts long-term experimental studies on soil erosion, such as at the El Teularet-Sierra de Enguera experimental station in Valencia. This lab supports field-based research on erosion processes, land management, and sustainable viticulture.

• Veterinary Medicine
• Dairy Cattle Health
• Reproductive Health
• +۴ مورد دیگر

Prof. Jocelyn Dubuc is a Full Professor at the Faculty of Veterinary Medicine (Université de Montréal), specializing in bovine population health and reproductive medicine. He leads the Department of Clinical Sciences , focusing on dairy cow uterine health, metabolic diseases, and epidemiology. His work bridges clinical practice and research, emphasizing evidence-based management strategies. Education: 2005: DVM, Université de Montréal 2007: MSc in Veterinary Sciences, Université de Montréal 2010: PhD in Veterinary Science, University of Guelph Research Focus: Uterine infections and postpartum disorders Metabolic diseases (e.g., ketosis) Antimicrobial stewardship On-farm diagnostic tools Reproductive tract disease epidemiology His studies have redefined understanding of postpartum endometritis and shaped clinical guidelines for dairy herd management. Awards: 2013: Prix Carl J. Norden for Teaching Excellence 2015: Journal of Dairy Science Loyalty Program Grants & Collaborations: Leading projects funded by MAPAQ, FRQNT, and industry partnerships. Key member of RQR (Reproduction Network) and Op+lait (Dairy Quality Optimization). Developed courses on uterine health monitoring and metabolic diagnostics. Teams: Collaborates with over 100 researchers in networks like Vetmétabo (AI-driven veterinary medicine) and the Québec Dairy Health Benchmarking Initiative.

• Computer Architecture
• High-Performance Computing
• Distributed Systems
• +۱۲ مورد دیگر

Yolanda Becerra Fontal is a faculty member at the Universitat Politècnica de Catalunya (UPC), affiliated with the Department of Computer Architecture within the Barcelona School of Informatics (FIB). She is actively involved in research projects and collaborations, notably with the Barcelona Supercomputing Center, and is a member of prominent research groups such as the High Performance Computing Group (CAP) and CROMAI (Computing Resources Orchestration and Management for AI). Research Interests: Her research spans a broad spectrum of computer systems, with a consistent focus on performance, efficiency, and scalability. Key areas include Computer Architecture , High-Performance Computing (HPC) , Distributed and Cloud Systems , Resource and Energy Management in virtualized environments, and Data-Intensive Computing . More recently, her work has centered on innovative time-series database systems and data management for edge and cloud analytics. Publication Trends: Her recent scholarly output (2020-2022) shows a strong emphasis on time-series data management, proposing novel database architectures like NagareDB and strategies for polyglot persistence. Earlier work (2009-2013) was pivotal in MapReduce workload management, energy accounting for virtualized systems, and optical data center networks, demonstrating a long-standing contribution to foundational distributed computing challenges. Scientific Contributions: Her work has been published in top-tier journals and conferences such as Future Generation Computer Systems , IEEE Transactions , and Nucleic Acids Research . She has also contributed to significant competitive R&D projects and holds patents related to data flow management and distributed indexing. Advising and Grants: Dr. Becerra Fontal has served as a thesis advisor for doctoral students. Her research has been funded through competitive grants from national and regional programs, including Spanish State Research Plans (Plan Estatal de Investigación) and Catalonia's RIS3CAT strategy, supporting projects on high-performance computing and data management. Research Groups and Labs: She is a core member of the CAP - High Performance Computing Group and the CROMAI - Computing Resources Orchestration and Management for AI group at UPC. Her work is closely associated with the Barcelona Supercomputing Center (BSC) , one of Europe's leading supercomputing facilities, indicating access to advanced computational infrastructure.

Ross Wallerمشاهده پروفایل

پژوهشگر

• Molecular Biology
• Cell Biology
• Evolutionary Biology
• +۳ مورد دیگر

Ross Waller is a researcher at the Department of Biochemistry , University of Cambridge, focusing on the molecular evolution and cell biology of protists, particularly within the Alveolata infrakingdom. His work spans apicomplexan parasites (Plasmodium, Toxoplasma), dinoflagellate symbionts, and ciliates, investigating their subcellular organization, endosymbiotic partnerships, and genomic adaptations. His research provides critical insights into eukaryotic evolution and parasitism. Key research areas include: Adaptations in apicomplexan parasites for host exploitation Molecular processes of endosymbiont establishment Chromatin management in dinoflagellates without histones Cell biological innovations in coral-associated dinoflagellates Recent publications highlight advancements in understanding plastid evolution, secretory organelle dynamics, and metabolic adaptations across parasitic and symbiotic protists. The Waller Group is actively recruiting interns and researchers interested in experimental cell biology of marine protists.

Jiabi Duمشاهده پروفایل

استادیار

• Coastal Oceanography
• Climate Change Impacts
• Estuarine Hydrodynamics
• +۳ مورد دیگر

Jiabi Du is an Assistant Professor at Texas A&M University at Galveston, specializing in coastal oceanography and environmental modeling. His research focuses on understanding how coastal systems respond to climate change, extreme weather events like hurricanes, and human activities, with particular emphasis on hypoxia, flooding, and habitat loss. He employs advanced numerical models and long-term observations to study processes such as pollutant dispersion and larval transport in estuaries. Dr. Du holds a Ph.D. in Physical Oceanography from the Virginia Institute of Marine Science (2017), an M.S. in Oceanography from Nanjing University (2012), and a B.S. in Physical Geography from Nanjing University (2010). His awards include the 2019 Institutional Postdoc Fellowship and recognition for academic excellence during his undergraduate and graduate studies. His research interests span coastal hydrodynamics, hurricane impacts, and microplastic transport. Notable contributions include studies on Galveston Bay's hydrodynamic responses to Hurricane Harvey and the role of baroclinic processes in estuarine flushing. He teaches courses in Physical Oceanography and computing. Awards: Best Student Paper (2018), Zengxianzi Scholarship (2007-2009), National Inspiration Scholarship (2007-2008). Labs/Teams: Coastal Modeling Group, Galveston Oyster Larvae Tracker Project. Future research directions include expanding microplastic pollution studies and investigating compounding climate-hurricane effects on coastal systems.

Johan Barthelemyمشاهده پروفایل

عضو هیئت علمی

• Complex Systems
• Agent-based Simulation
• Computer Vision
• +۷ مورد دیگر

Dr. Johan Barthelemy is an Honorary Associate Professor at the University of Wollongong's Faculty of Sciences - SAEF, where he leads the SMART IoT Hub and Digital Living Lab. His research focuses on complex systems, agent-based simulation, AI for IoT, and smart cities. He holds a PhD in Applied Mathematics from the University of Namur (Belgium) and has contributed to projects like the mipfp statistical package for R. His work spans environmental monitoring, transportation modeling, and infrastructure resilience. He supervises higher-degree research students and collaborates with NVIDIA as a Deep Learning Institute Ambassador. Education: PhD in Applied Mathematics, University of Namur (2007–2014) MSc in Mathematics, University of Namur (2005–2007) BSc in Applied Mathematics, University of Namur (2003–2005) Research Interests: Agent-based simulation and synthetic population generation AI-driven video analytics for smart cities and environmental monitoring IoT sensor networks and edge computing GPU-based high-performance computing Climate change impact analysis via drones and multispectral imaging Funding & Projects: Lead investigator for ARC grants on future mobility and Antarctic environmental futures CSIRO-funded project on AI-driven sugarcane assessment Multiple University of Wollongong grants for IoT sensors, climate testing facilities, and disaster-resilient transport Labs & Collaborations: SMART Infrastructure Facility (UOW) Namur Center for Complex Systems (Belgium) NVIDIA Deep Learning Institute partnership

Qiyang Hanمشاهده پروفایل

دانشیار

• Mathematical Statistics
• High Dimensional Probability
• Empirical Process Theory
• +۷ مورد دیگر

Qiyang Han is an Associate Professor in the Department of Statistics at Rutgers, The State University of New Jersey, within the School of Arts and Sciences. His research lies at the theoretical interface of statistics, probability, and algorithms, with a strong focus on foundational and high-dimensional problems. His research interests include mathematical statistics , high-dimensional probability , empirical process theory , nonparametric and shape-restricted inference , and Bayesian nonparametrics . He also investigates high-dimensional statistics , convex optimization , and large-scale iterative algorithms , with increasing attention to gradient descent dynamics and message passing methods. His recent publications reveal a consistent focus on precise asymptotic analysis, universality phenomena, and inference under geometric constraints. Themes across his work include robustness, adaptivity, and the theoretical underpinnings of modern statistical learning in overparameterized regimes. Ph.D. in Statistics, University of Washington, 2018 Supervised by Professor Jon A. Wellner He has collaborated with prominent researchers such as C.-H. Zhang, Bodhisattva Sen, Kengo Kato, and Richard J. Samworth. His work is published in top journals including The Annals of Statistics , Journal of the Royal Statistical Society Series B , and IEEE Transactions on Information Theory . Although no formal advising list is provided, his collaborative output suggests active mentorship and research leadership. He is involved in theoretical research with implications for machine learning, signal processing, and statistical inference. His lab or research group focuses on developing rigorous mathematical frameworks for understanding complex statistical algorithms and models, particularly in high-dimensional settings.

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

Yann LeCun is the Chief AI Scientist at Meta and holds the Jacob T. Schwartz Professorship at New York University in Computer Science, Data Science, Neural Science, and Electrical and Computer Engineering. He is a member of the National Academy of Engineering, National Academy of Sciences, and Académie des Sciences, and a fellow of ACM, AAAI, AAAS, and SIF. Research Interests: AI, Machine Learning, Computer Vision, Robotics, Computational Neuroscience, Physics of Computation. Labs: CILVR Lab (Computational Intelligence, Learning, Vision, Robotics), Computational and Biological Learning Lab at Courant Institute, Meta FAIR (Fundamental AI Research). Scientific Awards include the ACM Turing Award (2018), Queen Elizabeth Prize for Engineering (2025), VinFuture Grand Prize (2024), and multiple honoris causa doctorates. He has mentored numerous PhD students and postdocs, including Ying Wang, Yilun Kuang, and Quentin Le Lidec. Recent Publications focus on self-supervised learning, world models, video analysis, and representation learning, with key contributions to autonomous machine intelligence architectures.

Miiamaaria Kujalaمشاهده پروفایل

پژوهشگر ارشد

• social cognition
• emotionality
• comparative cognitive neuroscience
• +۱۰ مورد دیگر

Miiamaaria Kujala is an Academy Research Fellow at the Department of Psychology, University of Jyväskylä. Her research focuses on social cognition and emotionality in humans and non-human animals, particularly domestic dogs, through interdisciplinary collaboration across psychology, cognitive science, biology, veterinary medicine, and biomedical engineering. Academy Research Fellow (2024) Docent in Comparative Cognitive Neuroscience Her work employs non-invasive physiological methods such as eye gaze tracking, EEG/ERPs, thermal imaging, and fMRI to study emotional expressions, cross-species interaction, and the neural basis of social perception. Key themes include the development of expertise in decoding nonverbal cues, human-animal bond dynamics, and One Health/One Welfare frameworks. Recent publications highlight interdisciplinary approaches to canine emotionality, pharmacological behavior management in pets, and advanced sensor technologies for behavior classification. Her 2024 articles explore olfaction, empathy, and activity tracking in dogs, while older works examine contagious behaviors, social brain circuits, and developmental psychology in human-animal interactions. Scientific awards include the Academy Research Fellow fellowship. She leads the "Interaction of Dogs and Humans" research group, integrating expertise from psychology, veterinary medicine, and engineering to advance understanding of emotional and cognitive processes across species.

Chun-Biu Liمشاهده پروفایل

دانشیار

• Computational Mathematics
• Statistical and Computational Methods in Biophysical Systems
• Information Theory
• +۴ مورد دیگر

Chun-Biu Li is an Associate Professor at the Department of Mathematics , Stockholm University , specializing in computational mathematics and statistical physics of biophysical systems. His research bridges information theory, machine learning, and nonequilibrium statistical mechanics to understand complex biological processes. Education: PhD in mathematical & statistical physics from the University of Texas at Austin (supervised by Ilya Prigogine), M.S. in mathematical physics from the University of Utah. Academic Experience: Associate Professor (2016–present) at Stockholm University, Associate Professor (2008–2016) at Hokkaido University, and JST/CREST Researcher (2005–2008) at Kobe University. Research Interests focus on data-driven statistical analyses, nonequilibrium biophysical systems, AI explainability, and fluctuation theorems. His work applies these methods to plant morphogenesis, molecular motor dynamics, and machine learning applications in life sciences. Teaching includes advanced courses on deep learning, reinforcement learning, and statistical methods for life science applications. His Supervision has guided over 30 students in topics ranging from protein mutation modeling to causal inference algorithms. Scientific Awards: Professional Development Award, University of Texas at Austin (2003) Summer Research Fellowship, University of Texas at Austin (2001) National Dean's List for Outstanding College Students (1997) Publications (110+) highlight his contributions to plant morphogenesis, single-molecule analysis, and statistical methods. Recent works examine DNA barcode clustering, rotary motor protein dynamics, and shape-aware data visualization techniques.

• Topological Data Analysis
• Dynamical Systems
• Machine Learning
• +۷ مورد دیگر

Firas Khasawneh is an Associate Professor at the Department of Computational Mathematics, Science and Engineering at Michigan State University. His research focuses on the intersection of topological data analysis, dynamical systems, and machine learning with applications in engineering, neuroscience, and biological systems. Topological Data Analysis - Persistent Homology, Zigzag Persistence, Data Assimilation Dynamical Systems - Bifurcation Detection, Delay Differential Equations, Nonlinear Dynamics Machine Learning - Applications in Signal Processing, Surface Texture Analysis, Neural Activity Modeling His recent publications (2023-2025) demonstrate a strong emphasis on topological approaches for analyzing complex systems, including neural activity characterization, vibration analysis in manufacturing processes, and data assimilation techniques for forecasting. He has developed computational tools like the Teaspoon Python package for topological signal processing.

Yonggang Liuمشاهده پروفایل

دانشیار

• Ocean Circulation
• Coastal Ocean Observing
• Numerical Modeling
• +۷ مورد دیگر

Dr. Yonggang Liu is an Associate Professor at the University of South Florida College of Marine Science , specializing in Physical Oceanography . He leads the Ocean Circulation Lab and focuses on coastal ocean dynamics, air-sea interactions, and environmental applications. Education: PhD in Physical Oceanography from University of South Florida, Postdoctoral work at University of Washington Email: yliu@usf.edu His research interests include: Coastal ocean circulation and Loop Current interactions Real-time monitoring systems (COMPS, TBON, HF Radar) Numerical modeling (WFCOM, TBCOM, EFCOM) Harmful algal bloom prediction (Karenia brevis) Storm surge and Sargassum tracking Pollutant/oil spill transport modeling Recent publication trends show expertise in: Coastal ocean model validation Eddy-resolving numerical simulations Machine learning applications (Self-Organizing Maps) Marine environmental hazard response Multi-decadal circulation analysis Hydrodynamic-biogeochemical coupling He contributes to scientific leadership as: Editor for Artificial Intelligence for the Earth Systems Guest Editor for Ocean Science Science Committee member at SECOORA

• Plant Physiology
• Biochemistry
• Redox Regulation
• +۵ مورد دیگر

Prof. Dr. Karl-Josef Dietz holds a Professorial Chair (C4) in Biochemistry and Physiology of Plants at the Faculty of Biology, Bielefeld University since 1997. He is Head of the working group 'Biochemistry and Physiology of Plants' at the Center for Biotechnology (CeBiTec). His academic career spans prestigious institutions including Julius-Maximilians-Universität Würzburg (where he completed his PhD and Habilitation), Harvard University (postdoc position), and numerous international research stays in France, Japan, and the USA. Prof. Dietz's research focuses on plant stress responses, redox regulation, and photosynthesis. His work explores how plants acclimate to multiple environmental stresses through molecular signal integration, with particular emphasis on reactive oxygen species (ROS) signaling, thiol peroxidases, and oxylipin pathways. His laboratory investigates the mechanisms of redox regulation in chloroplasts and mitochondria, stress sensing, and plant defense responses against pathogens and abiotic challenges. His recent publications reveal a strong focus on redox biology, stress acclimatization mechanisms, and the role of peroxiredoxins in plant stress responses. His work spans both fundamental biochemical investigations and applied research in plant protection and stress tolerance. Scientific Awards and Recognition: Science Prize of the University Foundation Würzburg (1985) Gay-Lussac-Humboldt Prize (2012) Prof. Dietz has served in numerous leadership roles including Dean of the Faculty of Biology (2004-2006), President of the German Botanical Society (2012), and as a member of the Science Board of the German Research Foundation (DFG). He serves on the editorial boards of several prestigious journals including Journal of Experimental Botany, Physiologia Plantarum, and Plant Physiology. His professional activities demonstrate extensive involvement in national and international scientific communities, including the German Society of Botany, the American Society of Plant Biologists, and the Federation of European Societies of Plant Biology.

• Infectious Disease Modeling
• Vector-Borne Disease Epidemiology
• Mathematical Forecasting
• +۴ مورد دیگر

Michael Johansson serves as a Research Professor at Northeastern University's Roux Institute, maintaining offices in London, UK and Portland, ME. His work bridges public health research and operational response through advanced statistical and mathematical modeling of infectious diseases, with primary focus on vector-borne pathogens including dengue, Zika, chikungunya, and West Nile virus. Previously with the CDC in Puerto Rico for over a decade, he co-founded the Epidemic Prediction Initiative and led modeling efforts during Zika, COVID-19, and dengue emergencies. His research integrates biological, ecological, climatic, socioeconomic, and behavioral factors to understand disease emergence and transmission dynamics. Key methodologies include network-based forecasting models, climate-disease interaction analysis, and development of early warning systems. Current work emphasizes improving surveillance, burden estimation, and control strategy evaluation for arboviral diseases through quantitative tools. Recent publications demonstrate expertise in dengue synchronization across the Americas, West Nile virus forecasting, and addressing biases in mobility data for outbreak modeling. His work spans from molecular-level antibody response analysis to global risk mapping, consistently emphasizing operational implementation of research findings. Johansson actively contributes to public health practice through conference presentations including the 2025 American Mosquito Control Association Annual Meeting. His modeling frameworks have directly informed CDC emergency responses and the development of collaborative forecasting initiatives that pioneer open, transparent disease prediction.

• Systems Biology
• Computational Modeling
• Knowledge Representation
• +۳ مورد دیگر

Natasa Miskov-Zivanov is an Assistant Professor at the University of Pittsburgh where she leads the MeLoDy Lab (Mechanistic, Logical, and Dynamic Modeling). She holds a PhD in Electrical and Computer Engineering from Carnegie Mellon University and conducts interdisciplinary research at the intersection of computational methods and biological systems. Her education includes: PhD in Electrical and Computer Engineering, Carnegie Mellon University (2009) MS in Electrical and Computer Engineering, Carnegie Mellon University (2005) BS in Electrical Engineering and Computer Science, University of Novi Sad (2003) Her research focuses on developing computational frameworks and tools for biological systems modeling. Primary interests include: Automated knowledge extraction from biomedical literature Dynamic network modeling of cellular signaling pathways Development of standardized knowledge representation formats (BioRECIPE) Hybrid modeling approaches for complex biological systems Applications in cancer systems biology and immunology Her publications demonstrate consistent focus on computational biology methods development, with recent work emphasizing: Context-aware knowledge selection systems Automated model assembly from literature Biomedical text mining frameworks Hybrid multi-resolution modeling Standards for executable biological models She leads several funded research initiatives including DARPA's Big Mechanism program (AIMCancer W911NF-17-1-0135) and University of Pittsburgh-supported projects. Her lab develops open-source tools like CLARINET, ACCORDION, and VIOLIN that facilitate biological network modeling and knowledge extraction.