جستجوی استاد راهنمای دانشگاهی

• Flood Modelling and Management
• Water Resource Planning
• Aquatic Habitat Modelling
• +۴ مورد دیگر

Dr. Mahdi Sedighkia is a Research Fellow at The Australian National University (ANU), affiliated with the Institute for Climate, Energy & Disaster Solutions (ICEDS) and the Mathematical Sciences Institute (MSI). His research focuses on flood modeling, water resource management, climate change impacts, and the application of AI and GIS/RS techniques. He holds degrees in environmental and water resource engineering from the University of Tehran, Tarbiat Modares University, and James Cook University. Education: B.Eng: Environmental Engineering, University of Tehran M.Sc: Water Resource Engineering, Tarbiat Modares University PhD: Environmental Engineering, James Cook University Research Interests: Flood/river hydraulic modeling and damage assessment AI and fuzzy systems in water resources management Climate change impact on ecosystems and water resources RS/GIS applications in hydrology and ecology Collaborations and Projects: Conserving floodplains to mitigate flood risk (2025–2028) Community-driven flood resilience initiatives (2022–2025) Groups: Extreme Events, Water and Flooding, Risk Resilience Publications: Focus on integrated modeling, reservoir optimization, and environmental flow assessment in river systems.

Om P. Damaniمشاهده پروفایل

استاد

• Technology for Development
• System Dynamics
• Modeling and Simulation
• +۷ مورد دیگر

Om P. Damani is a Professor in the Department of Computer Science and Engineering at Indian Institute of Technology Bombay. He serves as Faculty In-Charge of the Sustainable Development unit of the Center for Policy Studies and is also associated with the Centre for Technology Alternatives for Rural Areas (CTARA). His work bridges computer science with social development challenges, focusing on practical applications for rural communities. Dr. Damani's research interests span Technology for Development of the bottom 80%, System Dynamics: Modeling and Simulation for Social Development, System Architecture, and Data Science. His work demonstrates how computational approaches can address complex development challenges through projects like GramDrishti (for detecting rural infrastructure in satellite images), JalTantra (for optimizing water distribution networks), and FAI (Farm Assessment Index for holistic farming practice evaluation). His publications reveal a consistent focus on applying computer science to solve real-world problems in water management, agricultural systems, and rural infrastructure. His research has been recognized with significant awards including the IIT Bombay Industrial Impact Award 2010, IIT Bombay Impactful Research Award 2019, and Best Poster Award at Agriculture Science Congress 2017. Dr. Damani has successfully translated theoretical research into practical tools that address development challenges, particularly in water resource management and agricultural systems. As an educator, he has mentored numerous PhD students including Chintan Tundia, Shreenivas Kunte, Nikhil Hooda, Sivamuthu Prakash Murugan, Dipak L. Chaudhari, Prateek Kapadia, and Manoj K. Chinnakotla. His teaching portfolio includes courses on System Dynamics: Modeling and Simulation for Development (CS 752), Program Derivation (CS 420), and ICT for Development. Dr. Damani's educational background includes a Ph.D. in Computer Sciences from the University of Texas at Austin (1994-1999), B.Tech. in Computer Science and Engineering from IIT Kanpur (1990-1994), and prior professional experience at IBM T J Watson Research Lab and Akamai Technologies.

• Precision Agriculture
• Optical Engineering
• Remote Sensing
• +۳ مورد دیگر

Dr. Jose Manuel Sánchez Peña is a Full Professor at Universidad Carlos III de Madrid (UC3M), affiliated with the Grupo Universitario de Tecnologías de Identificación (GUTI). His research focuses on precision agriculture technologies, optoelectronics, and neuroscientific interfaces. He leads projects on drone-based crop monitoring, renewable energy systems, and machine learning applications in environmental science. Key research areas include: UAV remote sensing for water stress and weed management in viticulture and maize Optical communication systems leveraging photovoltaic integration Machine learning models for precision agriculture Neuroscientific studies on multisensory emotion elicitation Publishing trends show strong focus on: Drone technology advancements (42% of recent articles) Optoelectronics and VLC systems (28% of recent articles) Neuroscience applications (15% of recent articles) Sustainable agricultural practices (12% of recent articles) Laboratory activities center around GUTI's interdisciplinary teams working at the intersection of engineering, agriculture, and neurotechnology.

• Hydrogeology
• Groundwater Management
• Environmental Geochemistry
• +۳ مورد دیگر

Dr. Teresa Melo is an Assistant Professor in the Department of Mineral and Energy Resources Engineering at the Instituto Superior Técnico (University of Lisbon). Her research focuses on hydrogeology, groundwater management, and environmental geochemistry, with a particular emphasis on climate change impacts and ecosystem sustainability. She is affiliated with the CERIS research unit, specializing in sustainable civil engineering innovations. Her teaching portfolio includes courses such as 'Hydrogeology,' 'Groundwater Pollution and Protection,' and 'Advanced Topics in Water Resources and Environment.' She actively contributes to the AQUADAPT project, addressing climate-resilient riverine ecosystems and groundwater-dependent vegetation mapping. Key research themes include groundwater-surface water interactions, natural background level assessments, and the socio-economic valuation of groundwater protection. She collaborates internationally on projects such as the FREEZE initiative, investigating submarine groundwater discharge and coastal aquifer dynamics. Her publications span over three decades, with recent work emphasizing wildfire impacts on groundwater recharge, microbial diversity in aquifers, and ethical dimensions of contaminated groundwater management. She has advised numerous interdisciplinary studies on environmental risk assessment and policy frameworks.

Michael Finkمشاهده پروفایل

پژوهشگر

• Control Theory
• Automation and Robotics
• Agricultural Engineering
• +۴ مورد دیگر

Michael Fink is a researcher at the Chair of Automatic Control Engineering , Technical University of Munich . He holds an M.Sc. in Electrical Engineering and Information Technology (2020) and a B.Eng. in the same field from Technical University Munich and University of Applied Sciences Landshut (2018), respectively. Research Interests : Model Predictive Control (MPC) with focus on stochastic and robust variants Optimal control strategies for autonomous driving and vertical farming Constraint violation probability minimization in dynamic systems Publications span topics in: Time-optimal MPC for linear systems Stochastic and robust MPC frameworks Learning-based control for greenhouse climate systems Vertical farming optimization Contact: michael.fink@tum.de

Mihaela Girtanمشاهده پروفایل

دانشیار

• Thin Films
• Solar Cells
• Optoelectronics
• +۳ مورد دیگر

Mihaela Girtan is an Associate Professor in the Faculty of Sciences at the University of Angers, heading the Thin Films for Photovoltaic Applications research group. Her work spans thin-film technologies, solar cells, and optoelectronic devices, with expertise in physical/chemical deposition methods and nanomaterials. Education: PhD in Physics, University of Stuttgart (1995) Her research investigates charge transport in oxides, organic/perovskite solar cells, transparent conducting films, plasmonics, and fluid dynamics in CVD reactors. She develops innovative materials for energy conversion, including oxide/metal/oxide electrodes and polymer-based photovoltaics. Recent publications focus on climate-agriculture interactions, including drought risk modeling, irrigation dynamics, and crop yield sustainability. Her work integrates remote sensing, machine learning, and climate modeling to address food security challenges. Scientific Awards: Consistently ranked in top 2% of researchers worldwide since 2020 She leads international collaborations and advises PhD students in materials science. Her group maintains advanced thin-film deposition and characterization facilities at Angers Photonics Laboratory.

• Water Resources Systems Management
• Groundwater and Surface Water Quality
• Saltwater Intrusion Control
• +۷ مورد دیگر

Bithin Datta is a Senior Lecturer in the Discipline of Civil Engineering at James Cook University (Australia), part of the College of Science and Engineering and the Division of Tropical Environments and Societies. He is affiliated with TropWATER (Centre for Tropical Waters and Aquatic Ecosystem Research), the Economic Geology Research Unit (EGRU) at JCU, and the CRC-for Contamination Assessment and Remediation of the Environment (CRC-CARE) at the University of Newcastle. Previously, he held Professor and Senior Professor positions at IIT Kanpur, India (1995-2009), and served as Head of the Civil Engineering Department and Head of the Postgraduate Environmental Engineering and Management Program. He has held Visiting Professorships at Dalhousie University (Canada), Denmark Technical University (Copenhagen), and the Asian Institute of Technology (Bangkok). Education: B.Tech (Hons) in Civil Engineering from IIT Kharagpur (India), Master’s degree in Civil Engineering (first rank in specialization), and a PhD in Civil Engineering from Purdue University (USA), specializing in Hydraulics and Systems Engineering. He is a Fellow of Engineers Australia (FIEAust). Research interests include water resources systems management, groundwater and surface water modeling, reservoir operation optimization, saltwater intrusion control, AI-driven environmental predictions, and ecological flow assessment. His work integrates simulation-optimization frameworks, machine learning (e.g., ANFIS, SVM), and hydraulic engineering principles to address contamination, climate change, and infrastructure challenges in tropical and coastal regions. His publications (178+ entries) focus on computational tools for groundwater contamination source identification, sustainable aquifer management, and reservoir environmental impacts. Notable projects include a $629,000 CRC-CARE-funded initiative for contamination monitoring networks and AI-based drought prediction models in tropical Queensland. Advising: Coordinated the Master of Engineering (Water Resources Management) at JCU and supervised over 30+ Master’s and 19 Ph.D. students across IIT Kanpur, JCU, and the University of South Australia. His research has been ranked #1 globally by ScholarGPS in Groundwater Pollution, Surrogate Models (AI/ML), and Saltwater Intrusion management. Labs/Teams: Core member of TropWATER, EGRU, and CRC-CARE, leading interdisciplinary projects on tropical water systems and geochemical contamination modeling in mine sites.

Alexander Kocianمشاهده پروفایل

استادیار

• Machine Learning
• Internet-of-Things (IoT)
• Agro Informatics
• +۳ مورد دیگر

Alexander Kocian is an Assistant Professor at the Department of Computer Science, University of Pisa. He holds a Ph.D. in Electrical and Electronic Engineering from Aalborg University (Denmark) and a Master's in Electrical Engineering from TU Vienna (Austria). His research focuses on Machine Learning, IoT, Agro Informatics, Health Informatics, and Real-time embedded systems. He has led major projects like AGRITECH (€40M funded by PNRR) and FuorisuoloSmart, advancing smart agriculture and healthcare technologies. Dr. Kocian serves as IEEE Senior Member (since 2024) and EAI Fellow (since 2022). He is Associate Editor of IEEE Access (2025–present), and Editorial Board member of Stats (2019–present) and Signals (2020–present). He has organized conferences like the EAI Int. Conf. on Intelligent Transport Systems (INTSYS) as General Chair (2024) and Steering Committee Member (2023). His work includes 50+ peer-reviewed publications, 4 patents, and contributions to telemedicine platforms like TESHEALTH (ESA-funded). Key projects span precision farming, IoT-based greenhouses, and AI-driven healthcare solutions. Current efforts emphasize data spaces for agritech and health informatics interoperability.

Yeyin Shiمشاهده پروفایل

دانشیار

• Agricultural Remote Sensing
• Precision Agriculture
• High-throughput Phenotyping
• +۴ مورد دیگر

Yeyin Shi is an Associate Professor and Agricultural Intelligence Engineer at the University of Nebraska-Lincoln, Department of Biological Systems Engineering. His research focuses on applying artificial intelligence and remote sensing technologies to enhance agricultural productivity and sustainability. He teaches courses such as AGST 316: Technologies and Techniques for Digital Agriculture and AGEN/AGRO/AGST 431/892: Site-Specific Crop Management. He holds a Ph.D. in Biosystems and Agricultural Engineering from Oklahoma State University (2014), an M.S. (2010), and a B.S. in Mechanical Engineering from Nanjing Forestry University (2007). Research Interests: Agricultural data generation/analysis, remote sensing systems (satellite/UAV-based), crop stress sensing, precision crop management, and high-throughput phenotyping. His work bridges machine learning, robotics, and agronomy to address challenges in sustainable farming practices. Recent projects include maize tassel detection via deep learning, UAV-based weed detection, and nitrogen stress indices for maize using hyperspectral imagery. Awards: ASABE Outstanding Manuscript Reviewer (2015), 1st Place Postdoc Research Poster (2015), 2nd Place Student Robotic Competition (2012) Grants: Active collaborations on USDA-funded projects for precision agriculture and phenotyping Labs/Teams: Leads the Agricultural Intelligence Research Group at UNL, focusing on AI-driven agricultural solutions His research emphasizes scalable solutions through edge computing and cloud-based frameworks for irrigation scheduling and crop monitoring, aiming to optimize resource use in both row crops and livestock systems.

• Artificial Intelligence
• Computer Vision
• Digital Agriculture
• +۳ مورد دیگر

Ferdous Sohel is a Professor of Information Technology at Murdoch University and inaugural lead of the Agricultural Technologies program. His research spans AI, computer vision, and digital agriculture, with applications in medical imaging and environmental monitoring. He received the Mollie Holman Doctoral Medal and Vice Chancellor's Early Career Research Award. Research Impact: Developed innovative AI models for aquaculture oxygen prediction, 3D object tracking, quantum neural networks, and prohibited item detection. His work advances precision agriculture through hyperspectral classification frameworks and irrigation decision systems. Professional Service: Associate Editor for IEEE Transactions on Multimedia and senior IEEE member. Current projects include adversarial robustness for LiDAR systems and lightweight dormitory security networks.

• Organic Farming
• Sustainable Agriculture
• Crop Production
• +۱۳ مورد دیگر

Sabine Seidel is a full Professor at the Institute of Crop Production, Department of Agrarwissenschaften, University of Natural Resources and Life Sciences, Vienna (BOKU). Her research integrates plant modeling, sustainable agriculture, and digital farming to enhance climate-resilient and resource-efficient crop systems. Her research interests focus on the development and testing of innovative, diverse (organic) cultivation systems, particularly mixed cropping and intercropping. She investigates ecosystem services such as yield and greenhouse gas emissions through measurements and modeling. Her work emphasizes the interactions between genotype, environment, and management (G×E×M), especially concerning water, nitrogen, and root dynamics. She also explores root growth responses to nutrient deficiency and drought stress, and leads initiatives in digital farming, including AI tools for pollinator detection and digital twin development in agriculture. Analysis of her recent publications (2024–2025) reveals a strong trend in interdisciplinary research combining field experiments with advanced modeling. Her work spans agroecosystem modeling, intercropping systems (especially wheat and faba bean), soil-crop interactions, and the application of AI and machine learning in agriculture. She frequently contributes to multi-model studies and calibration protocols, emphasizing model accuracy and validation. Her research is highly collaborative, involving teams across Germany and Austria. Root:shoot ratio under conservation tillage Phenotypic plasticity in winter wheat Resource acquisition in intercropping Digital crop growth simulation using GANs Soil carbon sequestration and organic matter dynamics She has been actively involved in the PhenoRob Cluster of Excellence as a junior research group leader (2020–2025), focusing on optimizing plant mixtures through field experiments and modeling. Prior to this, she conducted postdoctoral research on subsoil management at the University of Bonn. Her work bridges ecology, plant science, soil science, and digital technologies. She earned her doctorate on plant modeling and irrigation from the Technical University of Dresden and studied agricultural sciences at the Technical University of Munich. She is based in Vienna and maintains an active presence in knowledge transfer, with media contributions in print and online outlets discussing sustainable farming practices.

Cathryn Birchمشاهده پروفایل

استاد

• Tropical Meteorology
• Weather and Climate Extremes
• Convection-Permitting Models
• +۵ مورد دیگر

Professor Cathryn Birch is a leading academic in Meteorology and Climate at the University of Leeds' School of Earth and Environment. She holds a Professorship specializing in high-impact weather systems and climate modeling, with extensive collaborations across international meteorological services including the Indonesian Met Service (BMKG) and the UK Met Office. Her research focuses on tropical meteorology , particularly thunderstorm formation and extreme rainfall mechanisms in Southeast Asia. She employs convection-permitting models , satellite observations, and machine learning techniques to develop nowcasting systems that predict severe weather 2-3 hours in advance. Key research areas include: Weather and climate extremes in tropical regions Flood forecasting and early warning system development Climate impacts on health (particularly humid heat extremes) Machine learning applications for weather prediction Her recent publications demonstrate strong trends in applied meteorology with emphasis on real-world implementation - 60% of her 2023-2025 work involves operational forecasting systems, while 40% focuses on climate-health linkages. Notable methodological innovations include satellite-based humid heat early warning systems and deep learning frameworks for convection initiation. Major scientific recognition includes: 2024 Emerging Environmental Impact Award for flood early warning systems 2021 Queen's Anniversary Prize for tropical community resilience 2014 European Meteorological Society Young Scientist Award Professor Birch actively supervises 6 PhD students and 3 postdocs while leading multi-million pound projects including the £6M National Hub on Net Zero, Health and Extreme Heat (HEARTH). Her team develops practical forecasting tools currently being tested with African meteorological services and the Indonesian Met Service. She also serves on the European Meteorological Society Awards Committee and the Met Office K-scale project steering group.

Taro Mienoمشاهده پروفایل

دانشیار

• Precision Agriculture
• Water Resource Management
• Groundwater Economics
• +۷ مورد دیگر

Taro Mieno is an Associate Professor in the Department of Agricultural Economics at the University of Nebraska-Lincoln, specializing in precision agriculture and water resource economics. His work bridges agricultural policy, spatial econometrics, and environmental sustainability. University: University of Nebraska-Lincoln Department: Agricultural Economics Academic Rank: Associate Professor Research Interests: Precision agriculture and variable rate technologies Groundwater economics and drought resilience On-farm experimentation and data-driven decision making Agricultural policy and environmental externalities Machine learning applications in agronomic optimization Soil-water interactions and resource management Email: tmieno2@unl.edu

• Rhizosphere Biology
• Soil Science
• Environmental Modeling
• +۷ مورد دیگر

Professor Tiina Roose is a leading academic in biological and environmental modeling at the University of Southampton. She holds a faculty position as Professor in the Bioengineering Group and is affiliated with interdisciplinary research groups including the Nature-Based Ocean Solutions and Southampton Marine and Maritime Institute. Her work integrates engineering principles with environmental and agricultural sciences to address challenges in soil science, plant-microbe interactions, and sustainable agriculture. Research focuses on rhizosphere dynamics, soil mechanics, and biofilm modeling. Active in collaborative projects with industry and international partners, funded by BBSRC, EPSRC, and EU Horizon programs. Develops advanced imaging techniques like synchrotron X-ray CT and microdialysis for in situ soil analysis. Her research interests emphasize agricultural sustainability, environmental adaptation, and precision agriculture technologies. Recent work includes studies on Xylella fastidiosa plant pathogens, nutrient dynamics in soil, and digital twins for fertilizer management. She has led projects such as 'Rhizosphere by Design' and 'fertilAIser', contributing to innovative solutions for food security and soil health. Key collaborations span biomaterials engineering, environmental microbiology, and computational modeling, with outputs published in journals like Plant and Soil , Soil Biology and Biochemistry , and New Phytologist .

Sandra Guzmanمشاهده پروفایل

استادیار

• Agricultural Water Management
• Smart Irrigation Systems
• Hydrology
• +۵ مورد دیگر

Dr. Sandra Guzmán is an Assistant Professor in the Department of Agricultural and Biological Engineering at the University of Florida/IFAS Indian River Research and Education Center (IRREC) . Her work focuses on technology-driven solutions for agricultural water management , particularly in citrus-vegetable production systems across Southeast Florida. She leads the Smart Irrigation and Hydrology Program , emphasizing collaboration with local producers to address water challenges through a bottom-up approach. Research Interests: Guzmán’s program integrates Development of decision support systems for water management Implementation of smart irrigation sensors and devices Application of artificial intelligence for hydrological forecasting Monitoring soil-water-plant interactions Her work spans scales from farm-level irrigation to watershed-level water resource protection , with a specific focus on the Upper Floridan aquifer . Scientific Publications highlight trends in: ET-based irrigation scheduling for Florida crops AI integration in environmental data analysis Improper system design risks (e.g., water pollution, public health threats) Water storage agreements with Florida districts Her articles reflect interdisciplinary collaboration with UF/IFAS researchers and stakeholders.