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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
• +3 more

Alex Wong is an Assistant Professor of Computer Science at Yale University, specializing in computer vision, robotics, and medical imaging. His research focuses on sensor fusion, unsupervised learning, 3D vision, robust perception under adverse conditions, and medical image analysis. He holds degrees from the University of California, Los Angeles (UCLA), including a B.S., M.S., and Ph.D. in Computer Science. Wong’s work bridges theoretical advances with practical applications, particularly in depth estimation, autonomous systems, and medical diagnostics. He has received prestigious awards such as the NeurIPS Outstanding Student Paper Award (2011) and the ICRA Best Paper Award in Robot Vision (2019). His research often addresses challenges in unstructured environments, emphasizing robustness and adaptability. Recent projects include developing novel frameworks for unsupervised depth completion, adversarial robustness in vision systems, and multimodal fusion techniques. His contributions span conferences like CVPR, ICCV, and ICRA, with a strong focus on advancing AI for real-world applications in healthcare and robotics. Education: B.S., Computer Science, UCLA M.S., Computer Science, UCLA Ph.D., Computer Science, UCLA Awards: NeurIPS Outstanding Student Paper Award (2011) ICRA Best Paper Award in Robot Vision (2019) His lab at Yale Engineering focuses on AI-driven solutions for perception challenges, collaborating across disciplines to advance medical imaging and autonomous systems. Current efforts explore generative models, continual learning, and vision-language integration for robust scene understanding.

• Sensor fusion
• Unsupervised learning
• 3D vision
• +2 more

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
• +12 more

Dr. Matthew Brookhouse is a Senior Lecturer at the Fenner School of Environment & Society, part of the Australian National University's Institute for Climate, Energy & Disaster Solutions. With a PhD in Dendroclimatology from ANU, he specializes in using forest structural complexity and tree-ring analysis to understand climate interactions and ecological responses in Australian subalpine environments. Research Focus: Sub-alpine ecology, Dendrochronology, CO2 responsiveness in eucalypt species Teaching: First-year research methods with emphasis on statistical application, advanced modeling and field botany Projects: Leading collaborative snow-gum dieback research and dendrochronological monitoring initiatives His publications span 2006-2025 with recent emphasis on machine learning applications for forest monitoring, tropical tree-ring chronologies for climate change, and climate sensitivity in Australian alpine ecosystems. Key collaborations include institutions like Australian Nuclear Science and Technology Organisation and University of Canberra researchers. Current projects focus on snow-gum woodland dieback mechanisms, high-resolution dendrometric monitoring, and integrating dendrochronology with environmental policy frameworks. He maintains active supervision of research students and contributes to both undergraduate and postgraduate curriculum development.

• Plant physiology
• Sub-alpine ecology
• Dendrochronology
• +2 more

Giorgio Ascoli is a University Professor in the Department of Bioengineering at George Mason University, where he has been since 1997. He is the Founding Director of the Center for Neural Informatics, Structures, & Plasticity (CN3) and Founding Editor-in-Chief of the journal Neuroinformatics . His affiliations span computational neuroanatomy, neuroinformatics, and hippocampal modeling. Education : PhD in Biochemistry and Neuroscience (1996), Scuola Normale Superiore; MS in Chemistry and Biochemistry (1993), Pisa University; BS in Chemistry and Physics (1991), Scuola Normale Superiore. Dr. Ascoli investigates the relationship between brain structure, activity, and function from cellular to circuit levels. His research focuses on anatomically plausible neural networks to model mammalian brains, particularly the hippocampus, with implications for understanding human memory and consciousness . He pioneered computational neuroanatomy, developing tools like L-Neuron for neuronal shape modeling and curating NeuroMorpho.Org , a central repository for digitally reconstructed neurons. His recent publications emphasize neuronal classification , connectome analysis , and biologically informed machine learning . Awards include the 2012 Outstanding Faculty Award (Virginia), 2022 AIMBE fellowship , and 2023 Presidential Faculty Excellence Awards . He has mentored over 20 graduate students and postdoctoral fellows, with funding from NIH, NSF, DARPA, and private foundations. Scientific Contributions : Over 137 peer-reviewed articles, 4 patents, 2 authored/edited books, and leadership in NeuroMorpho.Org and Hippocampome. Grants : $20M+ in cumulative funding, including NIH R01s, NSF BRAIN EAGERs, and Burroughs-Wellcome Trust support. Labs : Leads the Computational Neuroanatomy Group within CN3, focusing on hippocampal modeling, neuronal morphology, and consciousness theories.

• Computational Neuroanatomy
• Neuroinformatics
• Neuronal Morphology
• +5 more

Dr. John M. Ruter is the Allan M. Armitage Professor and Director of the UGA Trial Gardens within the College of Agricultural & Environmental Sciences at the University of Georgia. His work integrates plant breeding, genetics, and sustainable nursery crop production, focusing on ornamental plants for southeastern landscapes. Education: B.S. in Ornamental Horticulture, California Polytechnic State University (1984) M.S. in Ornamental Horticulture and Landscape Design, University of Tennessee (1986) Ph.D. in Horticultural Science, University of Florida (1989) Research interests include developing climate-resilient ornamental plants (e.g., Camellia oleifera , hibiscus, crape myrtle), mutation breeding via gamma irradiation, and optimizing nursery production systems. Recent projects focus on polyploid conifer evaluation and tea oil crop development for the southeastern U.S. Recent publications highlight advancements in induced mutagenesis (EMS, gamma irradiation), disease resistance screening (Cercospora leaf spot), and genetic characterization of native and ornamental species. Key subfields include ornamental breeding , genomic analysis , and sustainable production practices . As Director of the UGA Trial Gardens, he leads plant evaluation programs that inform regional landscaping decisions and cultivar development.

• Ornamental Plant Breeding
• Nursery Crop Production
• Plant Genetics
• +4 more

Pingfu Fu, PhD, is a Professor in the Department of Population and Quantitative Health Sciences at Case Western Reserve University's School of Medicine. He is also a member of the Developmental Therapeutics Program at the Case Comprehensive Cancer Center. His expertise spans biostatistics, mathematics, and computer science, with a focus on cancer research and HIV/AIDS. Dr. Fu advises researchers on study design and statistical methodology for clinical and pre-clinical studies. He teaches courses in survival data analysis and clinical trials, and was recognized as 'Professor of the Year' in 2010 by the Department of Epidemiology and Biostatistics. Education: PhD in Biostatistics (Case Western Reserve University, 2001), MS in Statistics (Case Western Reserve University, 1996), MS in Mathematics (Xiangtan University, 1988), and BS in Mathematics (Jiangxi Normal University, 1984). His research interests include survival analysis, tree-based methods, clinical trials, and statistical applications in medical research. He has co-authored numerous peer-reviewed articles, focusing on cancer disparities, radiomics, and computational pathology. Professional memberships include the American Statistical Association, American Mathematical Society, and American Cancer Society. Dr. Fu holds editorial roles at Reviews on Recent Clinical Trials , Journal of Clinical Oncology , and Journal of the National Cancer Center . His work has addressed mathematical challenges in stochastic processes and resolved statistical issues in study design and tree-based models. Notable contributions include developing risk prediction models for cancer outcomes and advancing interdisciplinary collaborations across oncology, biostatistics, and computer science. His lab focuses on integrating computational methods with clinical data to improve patient outcomes.

• Survival analysis
• Clinical trials
• Cancer research
• +4 more

Noel Michele Holbrook is the Charles Bullard Professor of Forestry at Harvard University, affiliated with the Department of Organismic and Evolutionary Biology and the Harvard University Center for the Environment. She directs the Harvard Forest, a Long-Term Ecological Research site. Her work focuses on plant vascular transport mechanisms, particularly the physics and physiology of water and solute movement in plants. Affiliations: Harvard Forest, Harvard University Center for the Environment, Environmental Science & Engineering (affiliate). Research Areas: Plant hydraulics, xylem and phloem transport, wood anatomy, cavitation resistance, and plant ecological adaptations. Her lab investigates how constraints on vascular transport influence ecological and evolutionary processes. Key projects include studying embolism propagation, stomatal mechanics, and the role of vascular networks in plant survival. Recent work involves analyzing conifer needle transfusion tissues and the structural basis of Carlquist’s Law in xylem anatomy. Notable contributions include discoveries about moss vascular function and the impact of environmental factors on plant water dynamics. Her team has also explored crop responses to elevated CO2 and agricultural climate effects. Advising & Grants: Supervises undergraduate researchers (e.g., Nya Nicholson and Addison Harris) and postdoctoral fellows (e.g., Cade Kane). Research is supported by grants from the National Science Foundation and other institutions. Labs/Teams: Holbrook Lab at Harvard and Harvard Forest, collaborating with interdisciplinary teams in plant biology and ecology.

• Plant Physiology
• Plant Hydraulics
• Ecological Processes
• +4 more

Stavros G. Vougioukas is a Professor and Vice Chair in the Department of Biological and Agricultural Engineering at the University of California, Davis. His research focuses on agricultural robotics, mechanization, and automation for specialty crops, with particular emphasis on robotic harvesting systems and precision agriculture technologies. He leads initiatives in developing actuator systems, perception, and control mechanisms to optimize crop management. Key areas of expertise include robotic fruit harvesting, autonomous vehicle navigation in orchards, and site-specific pest management strategies. His work integrates mechanical engineering principles with advanced automation to address labor shortages and improve agricultural efficiency. Recent projects emphasize data-driven solutions for yield estimation, worker activity analysis, and economic viability of robotic systems. Academic contributions span over 50 peer-reviewed publications (2023-2025), with a focus on robotic orchard platforms, crop transport systems, and sensor-based automation. Notable innovations include vacuum suction end-effectors for fruit harvesting and GNSS-free navigation systems for autonomous vehicles. He also explores sustainable agricultural machinery through techno-economic analyses of electric/hybrid tractors. Current research bridges robotics and agricultural economics, addressing labor cost optimization and precision irrigation. His lab collaborates with industry partners to translate prototypes into field-ready solutions, emphasizing practical applications for specialty crop production systems.

• Agricultural Robotics
• Mechanization of Specialty Crops
• Automation in Harvesting
• +5 more

Nathan G. Swenson is a Professor in the Department of Biological Sciences at the University of Notre Dame and serves as the Gillen Director of the Environmental Research Center (UNDERC). He has held prior academic positions at the University of Maryland and Michigan State University, advancing from Assistant to full Professor. His research integrates genomics, ecology, and evolutionary biology to understand forest biodiversity and dynamics. Research Interests: Ecology and Environmental Biology Evolutionary Biology Genetics and Genomics Global Change Biology Forest Ecology Functional and Phylogenetic Ecology Tree Physiology and Demography His research focuses on leveraging intra- and interspecific variation in tree performance to predict forest biodiversity patterns. He employs integrative approaches from genomes to forest canopies and utilizes large-scale global datasets. Recent publications emphasize intraspecific trait variation, transcriptomic responses to drought, ecological forecasting, and functional group dynamics in tropical and temperate forests. Scientific Awards: Winner of 2017 British Ecological Society John Harper Prize (awarded to J. Zambrano; Swenson was senior author) Advising and Grants: Dr. Swenson has mentored numerous researchers, including M.N. Umana, S.J. Worthy, and J. Yang, who frequently co-author high-impact papers. His lab receives substantial research funding, evident from large collaborative projects and participation in global networks like ForestGEO and the TRY plant trait database. He has secured support for long-term ecological research, genomic studies, and international fieldwork. Labs and Teams: He leads the Swenson Lab, which conducts research on woody plant ecology in dynamic environments. The lab emphasizes community transcriptomics, functional trait analysis, and large-scale ecological modeling. It collaborates widely across institutions and is involved in major initiatives such as ForestGEO and NEON.

• Ecology and Environmental Biology
• Evolutionary Biology
• Genetics and Genomics
• +10 more

Gregory Michael Peck is an Associate Professor and Director of Undergraduate Studies for the Plant Sciences Major at Cornell University's School of Integrative Plant Science, Horticulture Section. His research focuses on sustainable tree-fruit production, particularly in organic apple systems , cider apple germplasm evaluation , and crop-load management through pollen tube growth modeling . Award-winning educator (2021 Cornell Teaching, Advising & Mentoring Award) 2018 Grower Advocate of the Year (American Cider Association) Active in outreach through field days, extension publications, and social media Peck's work spans tree-fruit physiology , soil health , and mechanization of orchard practices . He co-teaches Cornell's popular cider appreciation course with microbiologist Kathy Arnink, combining apple production science with fermentation expertise. His research explores phenolic development , nitrogen management , and yeast interactions in cider production systems. Recent publications highlight collaborations in rootstock effects , compost applications , and fermentation chemistry . Peck's career has included work in California, Washington, New York, and Virginia, with training spanning horticulture, plant physiology, soil science, and agricultural economics.

• Tree fruit production
• Hard cider research
• Organic agriculture
• +7 more

Professor Jill Edmondson serves as a Professor of Ecosystem Sustainability and NERC Knowledge Exchange Fellow at the School of Biosciences, University of Sheffield, where she has been a Senior Lecturer since 2021. Her research focuses on enhancing ecosystem sustainability and resilience in urban and agricultural contexts through interdisciplinary approaches bridging soil science, plant ecology, and social dimensions. Her core research pillars include: Urban Horticulture , where she leads the national MYHarvest citizen science project quantifying home-grown food production while assessing ecosystem co-benefits and soil pollutant risks; Soil Carbon Dynamics , specializing in black carbon's role in urban soil carbon sequestration; and Urban Forest Ecology , investigating how pollution and infrastructure encasement impact tree health and ecosystem services like heat mitigation. Her work consistently integrates field studies with policy-relevant applications for city planning. Analysis of her 2020-2025 publications reveals intensifying focus on climate adaptation, with dominant themes including urban food security quantification, soil contaminant bioavailability, green infrastructure performance, and urban tree resilience. Methodologically, she pioneers citizen science integration and interdisciplinary field measurements, yielding actionable insights for urban sustainability policy. Her major recognitions include: NERC Knowledge Exchange Fellow (2022-present) EPSRC Living with Environmental Change Fellow (2016-2021) Professor Edmondson supervises undergraduate literature reviews and research projects across multiple programs (MBiolSci, MEnvSci, MSc, MRes), mentoring the next generation of sustainability scientists. Her grant portfolio features competitive fellowships supporting urban ecosystem research with direct policy applications through partnerships with local governments and environmental NGOs. She directs the MYHarvest citizen science initiative and collaborates extensively with the University of Sheffield's Institute for Sustainable Food, leading a multidisciplinary team spanning soil science, ecology, and engineering to develop evidence-based strategies for resilient urban ecosystems.

• Urban Horticulture
• Ecosystem Services
• Urban Forestry
• +6 more

Lailiang Cheng is a Professor in the Horticulture Section of Cornell University's School of Integrative Plant Science, specializing in the physiological processes of deciduous fruit crops (particularly apple). His research focuses on sugar/malate metabolism, mineral nutrition, and environmental stress responses to improve orchard productivity and fruit quality. He integrates physiological, biochemical, and molecular approaches to study sorbitol signaling and nutrient management in high-density orchards. Education: Doctorate, Oregon State University (1999) Master of Science, Shandong Agricultural University (1989) Bachelor of Science, Shandong Agricultural University (1984) Research Focus: Cheng's work investigates carbon partitioning, malate accumulation, and nutrient transport dynamics in apple trees under abiotic stresses. His extension program delivers nutrient management strategies to the apple industry, while his teaching emphasizes analytical techniques (PLSCI 6170) and crop nutrition principles (PLSCI 4551/6551). Publication Analysis: Recent articles (2021-2025) reveal dominant themes in molecular regulation of fruit acidity, transporter biology, stress-responsive transcription factors, and omics-assisted breeding. Over 70% of publications involve collaborative work on apple genomics, with consistent emphasis on translating basic research into orchard management solutions. Awards & Recognition: No scientific awards mentioned in source materials. Academic Contributions: Advises graduate students in Horticulture; research supported by Cornell University Agricultural Experiment Station. Collaborates extensively with pomology breeders, extension specialists, and molecular biologists globally.

• Plant Physiology
• Fruit Crop Nutrition
• Sugar Metabolism
• +5 more

Eldan Cohen serves as an Assistant Professor of Industrial Engineering within the Department of Mechanical & Industrial Engineering at the University of Toronto's Faculty of Applied Science and Engineering. His academic journey includes a PhD from the same department followed by a postdoctoral fellowship in Computer Science at the University of Toronto and the Vector Institute for Artificial Intelligence. His educational background is detailed as follows: PhD in Mechanical & Industrial Engineering, University of Toronto Postdoctoral Fellowship in Computer Science, University of Toronto and Vector Institute for Artificial Intelligence Dr. Cohen's research centers on machine learning, deep learning, heuristic search, and optimization with strong emphasis on interpretable and human-compatible AI systems. His work bridges theoretical advancements with practical applications in healthcare (e.g., patient-physician interaction analysis, surgical safety diagnostics), automated planning, natural language processing, and software engineering. Recent projects develop interpretable clustering methods for medical data and optimization techniques for constrained sequence generation. Analysis of his 2023-2025 publications reveals a concentrated focus on healthcare AI applications, particularly using large language models for clinical text analysis and diagnostic support systems. Significant work also addresses interpretable machine learning for medical imaging, diverse plan selection in optimization, and constrained sequence generation in domains like vehicle routing. No major scientific awards or fellowships are documented in the available information. As an academic advisor, Dr. Cohen mentors graduate students in mechanical and industrial engineering, guiding research in optimization and machine learning. His OptiMaL research group fosters collaboration between computer science and industrial engineering to solve real-world decision-making challenges through human-centered AI approaches. The Optimization and Machine Learning (OptiMaL) research group, led by Dr. Cohen, serves as the primary hub for developing scalable, interpretable AI solutions for complex healthcare, planning, and engineering problems, with active projects in medical diagnostics and automated planning systems.

• Machine Learning
• Deep Learning
• Optimization
• +6 more

Dr. Jonathan Cale is an Assistant Professor in the Department of Forest Ecology and Management at the University of Northern British Columbia, affiliated with the NRES Graduate Program. His research program merges basic and applied approaches to investigate fungal ecology and forest pathology, focusing on how fungus-tree interactions influence forest health challenges. Specializes in forest fungi roles across disturbance stages: development, impact, and recovery Key interests: emerging forest diseases, climate change impacts on fungi, bark beetle-fungus interactions, chemical defense mechanisms Supervises graduate students in Biology and Forestry (MSc NRES) and serves as a media-contactable expert in Forest Pathology His recent publications address topics such as fungal community dynamics in disturbed forests, chemical defense responses in pines, and bark beetle-fungus coevolutionary mechanisms. No scientific awards are mentioned in the provided text.

• Forest Ecology
• Fungal Ecology
• Forest Pathology
• +4 more