جستجوی استاد راهنمای دانشگاهی

Arti Singh is an Assistant Professor in the Department of Agronomy at Iowa State University. Her research focuses on plant breeding, soybean diseases, genomics, and phenomics, with a strong emphasis on integrating artificial intelligence and high-throughput technologies into agricultural systems. She leads projects involving AI-driven disease identification, precision agriculture, and crop improvement strategies. Her expertise includes developing machine learning models for real-time weed and insect classification (e.g., WeedNet and InsectNet), deploying drones and ground robots for crop phenotyping, and leveraging genomic data to map traits like flowering time and disease resistance in legumes. Singh collaborates on initiatives like the AIIRA Institute for Resilient Agriculture and the BioTrove biodiversity dataset. Singh’s work spans plant stress phenotyping, digital twin technologies for plant sciences, and multi-sensor phenotyping for early disease detection. Her research bridges computational methods with traditional agronomy, aiming to enhance crop resilience and sustainability in the face of environmental challenges. Her recent projects include optimizing robotic navigation for precision agriculture, improving soybean yield estimation via video analysis, and dissecting genetic architectures of traits in mungbean and soybean using GWAS and genomic tools. She actively contributes to conferences and publishes in high-impact journals, advancing both foundational and applied aspects of agricultural science.

• Plant breeding
• Soybean diseases
• Genomics
• +۳ مورد دیگر

Adam Runions is a researcher in the Department of Computer Science at the University of Calgary, leading the MPG Partner Group in computational analysis of leaf development through collaborative work with Miltos Tsiantis. His group is embedded in the Graphics Cluster, focusing on interdisciplinary problems at the intersection of computer science and developmental biology. University of Calgary - Department of Computer Science MPG Partner Group (2022) Graphics Cluster affiliation His research explores computational modeling and analysis of plant form and development across multiple scales, integrating geometric modeling, physically-based simulation, and computer-aided design. Key themes include plant morphogenesis, self-organization of natural forms, and cross-disciplinary applications in computer graphics and animation. Recent publications emphasize plant development (leaf shape, bark patterning), mathematical modeling (auxin-driven patterning), and geometric techniques (subdivision surfaces, PUPs). Collaborations span institutions like the Max Planck Institute for Plant Breeding Research. Scientific Awards Marie Sklodowska-Curie Fellowship Best Paper Award (International Conference on Cyberworlds 2015) Best Student Paper Award (Computer Graphics International 2011) The group actively recruits BSc, MSc, and PhD students with backgrounds in computer science and mathematics for projects on plant form simulation and digital content creation. Research integrates evolutionary biology, biomechanical modeling, and computational techniques.

• Computational Modeling
• Developmental Biology
• Computer Science
• +۴ مورد دیگر

Craig Davis is a Professor and holds the Bollenbach Chair in Wildlife Management at Oklahoma State University's Department of Natural Resource Ecology & Management. He has been a faculty member since 2001, advancing from Assistant Professor (2001-2007) to Associate Professor (2007-2012), and has served as Bollenbach Chair since 2014. Davis earned his PhD in Wildlife Science from Texas Tech University (1996), an MS from Iowa State University (1991), and a BS from Ohio State University (1988). He is also a Certified Wildlife Biologist through The Wildlife Society. His research focuses on avian ecology, wetland restoration, and gamebird management, with specific interests in fire-grazing interactions, invertebrate communities, and climate change impacts on ecosystems. Key areas include grassland bird survival, wetland classification systems, and the effects of anthropogenic development on wildlife habitats. Davis actively collaborates with conservation organizations and agencies, addressing challenges like invasive species management and water infrastructure resilience. Teaching responsibilities include undergraduate courses on Wildlife Management Techniques and Wetland Ecology, as well as graduate courses like Advanced Wetland Ecology. His grants emphasize wetland restoration outreach, climate adaptation strategies, and studies on northern bobwhite and wild turkey populations. Notable projects include evaluating cellular transmission technology in wildlife monitoring and assessing the impact of extreme weather on gamebird survival. Grants (Selected): Expansion of potential wetland restoration opportunities in Oklahoma (2024-2027) Linking Research and Stakeholder Engagement for Wetland Conservation (2024-2026) Effects of Extreme Weather and Hunting on Northern Bobwhite (2023-2025) Research Themes: Aligns with UN Sustainable Development Goals 15 (Life on Land), 13 (Climate Action), 6 (Clean Water), 11 (Sustainable Cities), 14 (Life Below Water), and 9 (Industry/Infrastructure).

• Avian Ecology and Management
• Terrestrial and Aquatic Invertebrate Ecology
• Wetland Ecology and Assessment
• +۶ مورد دیگر

Yin Bao is an Assistant Professor in Plant and Soil Sciences and Mechanical Engineering at the University of Delaware since 2023, previously holding the same position at Auburn University's Department of Biosystems Engineering (2019-2023). He holds a BE in Mechanical Engineering from China Agricultural University (2012) and a PhD in Agricultural and Biosystems Engineering from Iowa State University (2018), followed by postdoctoral research there until 2019. His research focuses on automation technology for agriculture and forestry, leveraging robotics, machine learning, and sensing systems to develop tools for precision farming and plant phenotyping. Key areas include unmanned systems (UGVs/UAVs), spectral imaging, and AI-driven predictive models for crop and livestock management. Recent work emphasizes automated inventory systems for forest nurseries, UAV-based vegetation assessment, and machine learning applications in crop yield prediction. His publications span robotic guidance systems, root segmentation in X-ray CT scans, and equine gait analysis using deep learning. Notable projects include the Robotic Assay for Drought (RoAD) system and the 'smart canopy' sorghum initiative. Collaborative efforts involve integrating multifrequency microwave sensing and electronic nose technologies for crop quality analysis.

• Robotics and Controls
• Agricultural Automation
• Precision Farming
• +۴ مورد دیگر

Jörg Bohlmann is a Professor in the Department of Forest and Conservation Sciences at the University of British Columbia , affiliated with the Michael Smith Laboratories, Botany Department (Faculty of Science), and Wine Research Centre. His research spans genomics, biochemistry, and chemical ecology of plant specialized metabolism, focusing on terpenoids and phenolics for applications in forest health and bioproducts. Research Streams : Plant defense against insects/pathogens, metabolic engineering of bioproducts, forest genomics, and molecular evolution of terpenoid pathways. Collaborations : National and international partnerships with academia, government, and biotech industries. Recent Publications highlight genomic insights into Western Redcedar (2023), including its low genetic diversity and adaptation mechanisms despite self-fertilization. Earlier work (2001–2022) covers conifer defense systems, Arabidopsis terpenoid pathways, cannabis flavor genetics, and mass spectrometry infrastructure. Scientific Awards include: NSERC E.W.R. Steacie Fellow (2015), Fellow of the Royal Society of Canada (2015), Feodor Lynen Postdoctoral Fellowship (1995–1998), and Distinguished University Scholar (UBC). Funding Sources : NSERC (Discovery/Strategic grants), CFI, Genome Canada/BC, provincial/federal agencies. Labs & Facilities : Michael Smith Laboratories (UBC), National Centre of Excellence, Forest Sciences Centre, and a dedicated mass spectrometry lab for metabolite analysis.

• Plant Defense Mechanisms
• Terpenoid Biochemistry
• Forestry Genomics
• +۱۲ مورد دیگر

Manu Magar is a Researcher at the School of Biological Sciences , University of Western Australia , with a focus on plant genetics and climate resilience. They also hold an external position as a Biotechnologist at the National Biotechnology Research Center, Nepal Agricultural Research Council since May 2014. M.Sc.Ag. in Agricultural Science from Acharya N G Ranga Agricultural University (2012) B.Sc.Ag. in Horticulture from Tribhuwan University (2009) Research Interests Their work centers on plant breeding , gene expression , and crop genomics to combat heat stress in wheat. Key areas include transcription factor analysis , ERF gene regulation, and drought tolerance mechanisms. Article Trends Magar’s publications (2022–2025) emphasize AP2/ERF superfamily genes in wheat, heat tolerance pathways, and ethyline signaling during grain filling. Their work bridges genomic studies and transcription factor roles in stress response. Collaborations & Research Active in international collaborations between Australia, Nepal, and India, Magar contributes to crop improvement via genomic analysis and biotechnology .

• Plant breeding
• Tissue culture for plant breeding
• Gene expression
• +۵ مورد دیگر

Claudio Sillero is a Professor of Conservation Biology at the University of Oxford and Section Head of Ecology & Conservation at the Wildlife Conservation Research Unit (WildCRU). He leads global efforts to conserve endangered species, particularly the Ethiopian wolf, and chairs the IUCN Canid Specialist Group. His work integrates behavioral ecology, disease mitigation, and transfrontier conservation strategies. Since joining WildCRU in 1988, he has pioneered research linking fundamental biology to practical conservation solutions. As founder and director of the Ethiopian Wolf Conservation Programme (EWCP), he focuses on safeguarding Afroalpine ecosystems through vaccination campaigns and habitat protection. His IUCN role oversees conservation strategies for all canid species worldwide. Research interests include carnivore behavioral ecology, human-wildlife conflict mitigation, and the role of networks in conservation. Notable projects include resolving taxonomic ambiguities in wolf lineages and developing low-cost wildlife tracking technologies. His work emphasizes interdisciplinary approaches, combining ecological data with socio-political analysis to address conservation challenges. Key roles: Professor at University of Oxford, WildCRU Section Head, EWCP Director, IUCN Canid Specialist Group Chair Primary research sites: Ethiopian highlands, South American forests, African savannahs Key collaborations: Panthera, African Wild Dog Conservancy, local communities in Ethiopia and Bolivia Students and staff under his mentorship include Claire Marr (jaguar conservation), Dr. Sandra Lai (postdoctoral research on Ethiopian wolves), and Emily Madsen (conservation genetics). His work has led to breakthroughs in understanding canid disease dynamics and carnivore spatial ecology.

• Conservation Biology
• Wildlife Disease Ecology
• Carnivore Conservation
• +۳ مورد دیگر

Raul Astudillo Marban is a Postdoctoral Scholar Research Associate in the Department of Computing and Mathematical Sciences at Caltech, hosted by Professor Yisong Yue. He will join MBZUAI as a tenure-track Assistant Professor in August 2025. His research focuses on adaptive learning and decision-making in complex, data-intensive environments, with applications in personalized healthcare, engineering design, and scientific discovery. He earned his Ph.D. in Operations Research and Information Engineering from Cornell University under Professor Peter Frazier and holds an undergraduate degree in Mathematics from the University of Guanajuato and the Center for Research in Mathematics. His work integrates Bayesian optimization and machine learning to address real-world challenges such as protein engineering, plant breeding, and computational biology. Key contributions include steering generative models with experimental data, preferential multi-objective optimization, and cost-aware Bayesian strategies. He has received recognition as a Rising Star in Management Science and Engineering (Stanford) and a Rising Star in Data Science (University of Chicago/UCSD). Recent research highlights include optimizing protein fitness through generative models, active learning in directed evolution, and Bayesian optimization for budget allocation in agriculture. His publications span top venues like NeurIPS, Nature Communications, and TMLR. He actively recruits students/researchers for projects in machine learning and optimization.

• Machine Learning
• Bayesian Optimization
• Decision-Making Systems
• +۵ مورد دیگر

Angela D. Kent is a Professor in the Department of Natural Resources and Environmental Sciences at the University of Illinois Urbana-Champaign, where she also serves as Director of the Program in Ecology, Evolution, and Conservation Biology within the School of Integrative Biology. She is affiliated with the Carl R. Woese Institute for Genomic Biology. Her research focuses on microbial communities in agroecosystems and natural environments, particularly their roles in nitrogen cycling, soil health, and sustainable bioenergy production. Key research interests include microbial interactions in plant-microbe systems, the impact of genetic variation in crops on microbial processes, and the ecological and biogeochemical implications of soil microbiomes. She has authored over 99 publications and supervised datasets on topics such as denitrification dynamics, rhizosphere microbiome assembly, and microbial contributions to nitrogen retention. Dr. Kent has received the NACTA Educator Award (2012) and has contributed to high-impact studies on topics like microbial community responses to environmental stressors and the application of stable isotopes in bioenergy research. Her work bridges microbial ecology, agronomy, and environmental science, emphasizing practical solutions for sustainable agriculture and ecosystem management.

• Microbial Ecology
• Nitrogen Cycling
• Agroecosystems
• +۳ مورد دیگر

Karsten Borgwardt is a Professor and Director of the Department of Machine Learning and Systems Biology at the Max Planck Institute of Biochemistry. He holds a PhD in Computer Science (2007) from LMU Munich and has held academic positions at ETH Zürich, Universität Tübingen, and the Max Planck Institutes in Tübingen. His research focuses on machine learning applications in biology and medicine, including biomarker discovery, personalized medicine, and systems biology. Education: PhD in Computer Science (2007), LMU Munich M.Sc. in Biology (2003), University of Oxford Diplom (M.Sc. equivalent) in Computer Science (2004), LMU Munich Research Interests: Development of machine learning algorithms for large biomedical datasets Pattern recognition in genomic and clinical data Applications in sepsis biomarkers, antimicrobial resistance prediction, and personalized medicine Grants & Projects: Scientific Coordinator of Marie Curie Networks (2013-2022) Swiss National Science Foundation Starting Grant (2014) Personalized Swiss Sepsis Study (CHF 5.3M, 2018) Awards: Krupp Award (2013), Golden Owl Teaching Award (2017), multiple 'Top 40 under 40' recognitions (2014-2016). Labs: Leads the Machine Learning and Systems Biology Department at MPI, collaborating with 22+ labs in sepsis research and international networks.

• Machine Learning
• Systems Biology
• Bioinformatics
• +۳ مورد دیگر

Dr. Yunfei Jiang is an Assistant Professor in the Department of Plant, Food, and Environmental Sciences at Dalhousie University's Faculty of Agriculture. Her research focuses on improving crop resilience to climate change and sustainable agronomic practices in Atlantic Canada, with expertise in agronomy, crop physiology, and environmental stress responses. She holds a Ph.D. in Plant Science from the University of Saskatchewan (2017), an M.Sc. from Dalhousie University (2013), and a B.Sc. in Horticulture from Fujian Agriculture and Forestry University (2010). Her research includes evaluating enhanced efficiency fertilizers, biochar, and intercropping systems to enhance soil health and crop yields. She teaches courses such as AGRN2001 (Cereal-Based Cropping Systems) and PLSC2001 (Plant Propagation Techniques). Funding and awards details, along with her graduate students' projects, are available on her lab website at jiangdal.ca . Dr. Jiang is affiliated with professional organizations including the Nova Scotia Institute of Agrologists and the American Society of Agronomy. Her lab, the Agronomy and Crop Physiology (ACP) Lab, emphasizes sustainable agriculture and crop adaptation to environmental challenges. Contact her via email at yunfei.jiang@dal.ca or visit her lab's address: PO Box 550, Truro, NS B2N 5E3.

• Agronomy
• Crop Physiology
• Plant Response to Environmental Stress
• +۴ مورد دیگر

Sungkwon Park is a Professor in the Department of Food Science and Biotechnology at Sejong University, specializing in advanced food science and biotechnology research with a focus on meat science, cultured meat production, and sustainable food systems. His research integrates molecular biology, food biotechnology, and systems biology to develop innovative food solutions. His educational background includes a Ph.D. from Purdue University (2008), M.S. from Yeungnam University (2001), and B.S. from Yeungnam University (1999). Prior to his current position, he worked as a Postdoctoral Fellow at Virginia Tech (2008-2012) and as a Research Officer at the National Institute of Animal Science, RDA (2012-2015). Professor Park's research interests focus on livestock production optimization, meat processing for health functionality, environmentally friendly animal production systems, and in vitro meat production. His work has led to significant achievements including the identification of calcium and glucose interaction mechanisms in muscle metabolism, development of oleogel-based meat processing techniques, optimization of feed ingredients for sustainable livestock, and establishment of in vitro meat production systems. His recent publications (2023-2025) demonstrate a strong focus on cultured meat technology, meat science, and sustainable food production. The research spans cellular mechanisms for cultured meat production, safety and regulatory aspects of alternative proteins, comparative analysis of muscle satellite cells, and optimization of meat processing techniques. His work shows a clear trend toward developing practical applications for next-generation meat products with emphasis on health functionality and environmental sustainability. Professor Park actively serves as a reviewer for Frontiers in Veterinary Science and is an Editorial Board Member of the Korean Society of Animal Science. His laboratory, the M&M'a lab (Functional Food Lab), conducts research on high-value-added, health-functional BioFood and future foods using bio-convergence technologies.

• Livestock production & optimization
• Meat processing: healthy & functionality
• Establishment of environmentally friendly animal production
• +۶ مورد دیگر

Dr. Ian Stavness is a Professor and Department Head in the Department of Computer Science at the University of Saskatchewan. His research focuses on interdisciplinary applications of computer science, including deep learning in agriculture, biomedical computation, and 3D display technologies. He leads the Biological Imaging & Graphics (BIGLAB) laboratory, which develops tools for plant phenotyping and musculoskeletal modeling. Education: Ph.D. in Computer Engineering, University of British Columbia, 2010 M.A.Sc. in Computer Engineering, University of British Columbia, 2006 B.Sc. in Computer Science & B.Eng. in Electrical Engineering, University of Saskatchewan, 2004 Research Interests: Deep Learning for Plant Phenomics & Agriculture 3D Displays and VR/AR Technologies Musculoskeletal Biomechanical Simulation (OpenSim, ArtiSynth) Computer Vision and Image Analysis Awards: ACM CHI 2019 Honourable Mention ACM VRST 2018 Polyphony Digital Award Key Projects: Deep Plant Phenomics Platform Parametric Human Project (Digital Human Modeling) P2IRC (Plant Phenotyping & Imaging Research Center)

• Biomedical Computation & Visualization
• Computer Graphics
• 3D Displays
• +۶ مورد دیگر

Jennifer L. Clarke is a Professor in the Department of Statistics at the University of Nebraska–Lincoln and Director of the Quantitative Life Science Initiative. She holds leadership roles in enabling big data integration across the University of Nebraska system through collaborative research programs. Her affiliations include the Institute of Agriculture and Natural Resources (IANR) and the College of Agriculture and Natural Resources. Dr. Clarke's research focuses on statistical methodology for high-dimensional data, computational biology, bioinformatics, and bacterial genomics. Her work bridges statistical innovation with applications in oncology, microbiome analysis, and agricultural phenomics. Key areas include predictive modeling, machine learning, and genomic/metagenomic data integration. Her recent publications span cancer biomarker discovery, plant phenotyping methodologies, and microbial community analysis, reflecting her interdisciplinary approach. Articles emphasize translational applications like therapeutic target identification and precision agriculture. Dr. Clarke leads initiatives fostering collaboration between statisticians and domain scientists, including the Quantitative Life Science Initiative and contributions to the Agricultural Genome-to-Phenome Initiative (AG2PI). Her work advances data-driven solutions for healthcare and food security challenges. Notable projects include developing statistical tools for microbiome studies, analyzing root architecture via 3D imaging, and investigating cranberry-derived compounds' cancer-inhibitory mechanisms. Her methodological contributions include hybrid clustering techniques and predictive model validation frameworks.

• Statistical Methodology
• Bioinformatics/Computational Biology
• Data Mining/Machine Learning
• +۳ مورد دیگر

Nicolas Federico Martin is an Associate Professor in the Department of Crop Sciences at the University of Illinois at Urbana-Champaign, with additional appointments as Associate Professor in the Center for Latin American and Caribbean Studies, Center for Digital Agriculture, and the National Center for Supercomputing Applications (NCSA). His interdisciplinary work bridges traditional agricultural science with cutting-edge computational approaches. Dr. Martin's research focuses on the intersection of agriculture and data science, with particular emphasis on: Precision agriculture and on-farm experimentation methodologies Machine learning applications for crop management and yield prediction Nitrogen and nutrient management optimization Soybean and corn breeding and production systems Remote sensing and UAV applications in agriculture Sustainable agricultural practices including cover crop management His publication record demonstrates a clear trajectory toward increasingly sophisticated integration of artificial intelligence with agricultural science. Recent work shows heavy emphasis on using machine learning algorithms (particularly reinforcement learning, convolutional neural networks, and generalized additive models) to solve practical farming challenges related to crop management decisions, yield prediction, and resource optimization. This research has significant implications for both scientific understanding of crop-environment interactions and practical farm management. Dr. Martin actively collaborates across disciplines and institutions, as evidenced by his extensive co-authorship network spanning agronomy, computer science, environmental science, and economics. His work has garnered attention from numerous news outlets and social media platforms, indicating its relevance to current agricultural challenges. He is a key contributor to the Data-Intensive Farm Management project, which aims to transform agronomic research through on-farm precision experimentation. His affiliation with NCSA provides access to high-performance computing resources essential for processing large agricultural datasets. Additionally, his work in Latin American agriculture (particularly in Mexico and Argentina) reflects his commitment to addressing global food security challenges.

• Precision Agriculture
• Crop Science
• Machine Learning Applications in Agriculture
• +۷ مورد دیگر