جست‌وجوی استاد و پژوهشگر

• Image Processing and Computer Vision
• Machine Learning
• Evolutionary Computation
• +۱ مورد دیگر

Seyed Jalaleddin Mousavirad (Jalal) serves as a Postdoctoral researcher at Mid Sweden University in Sundsvall, Sweden, within the Department of Computer and Electrical Engineering (DET) and affiliated with the STC Research Centre. His research focuses on advancing AI-driven solutions for sustainable technologies and complex optimization problems. He earned his PhD in Computer Engineering specializing in Artificial Intelligence from the University of Kashan, Iran. Previous academic appointments include Assistant Professor at Hakim Sabzevari University (Iran), instructor roles at the University of Tehran (2018-2019) and Azad University (2019-2020), and a Research Fellow position at the University of Beira Interior (Portugal) where he contributed to the European GreenStamp project on sustainable Android applications. Dr. Mousavirad's research spans Image Processing and Computer Vision, Machine Learning, Evolutionary Computation, and Applied Artificial Intelligence, with significant contributions in pattern recognition, metaheuristic algorithms, and neural network optimization. His work demonstrates strong interdisciplinary applications in healthcare diagnostics, power systems, and medical imaging. Recent publications reveal a pronounced trend toward federated learning frameworks for privacy-preserving medical analysis, adversarial robustness in diffusion models, and hybrid optimization techniques for ECG classification and brain tumor detection. This reflects a strategic focus on translating AI innovations into practical healthcare and sustainability solutions. He actively contributes to the academic community as a guest editor for journals including Computational Intelligence and Neuroscience, Entropy, and Mathematical Biosciences and Engineering. His editorial leadership extends to organizing special sessions at IEEE CEC and EvoApplications conferences. Dr. Mousavirad maintains extensive peer-review commitments across 50+ prestigious venues including IEEE Transactions on Evolutionary Computation and IEEE Transactions on Cybernetics. His collaborative research includes international engagements at Xi'an Jiaotong-Liverpool University (China) and current work within Mid Sweden University's STC Research Centre on energy-aware computing and neural network optimization.

• Functional Data Analysis
• Statistical Learning
• Machine Learning
• +۷ مورد دیگر

Rosa Elvira Lillo Rodriguez is a Full Professor in the Statistics Department at Charles III University of Madrid, affiliated with both the Flores de Lemus Institute and the UC3M-Santander Big Data Institute. Her research spans multiple disciplines including Statistics, Computer Science, Medicine, and Environmental Sciences. Her primary research interests focus on advanced statistical methodologies, particularly in functional data analysis, multivariate statistics, and machine learning applications. She has developed innovative techniques for outlier detection, variable selection, and classification algorithms with applications across healthcare, engineering, and social sciences. Her work bridges theoretical statistics with practical implementations in real-world problems. Her publication portfolio shows a clear trend toward interdisciplinary research, with recent work applying statistical methods to COVID-19 detection, hydraulic system monitoring, intimate partner violence risk assessment, and neural network interpretability. The articles demonstrate expertise in developing robust statistical frameworks that handle complex, high-dimensional data while maintaining computational efficiency. Dr. Lillo Rodriguez has secured significant research funding as principal investigator for projects including 'Advanced Statistical Modeling for Complex Systems in Health, Industry and Society (ASMOCS)' funded by the Spanish National Research Agency (2023-2027) and the 'UC3M-Universia Chair of Data Economics and Responsible Artificial Intelligence' (2024-2026). She also serves as researcher on multiple European Commission projects. She has supervised numerous doctoral theses on topics including functional modeling techniques, variable selection algorithms, and spatial depth-based methods for functional data, demonstrating her commitment to training the next generation of statisticians. Her current research involves developing statistical frameworks for big data applications across multiple sectors including healthcare, finance, and public policy.

Fabienne JÉZÉQUELمشاهده پروفایل

مدرس

• Numerical algorithms
• High-performance computing
• Numerical validation

Fabienne JÉZÉQUEL is a Lecturer in Computer Science at Paris-Panthéon-Assas University, affiliated with the Sorbonne University Computer Science Laboratory (LIP6) and leading the PEQUAN (Performance and Quality of Digital Algorithms) team. Her research focuses on Numerical algorithms , High-performance computing , and Numerical validation , with applications in precision control and simulation reliability. Habilitation to Supervise Research (HDR) in Computer Science, University of Paris 6 (2005) Doctorate in Computer Science, University of Paris 6 (1996) Research Themes : Numerical algorithms with dynamic precision control High-performance computing (HPC) reliability and reproducibility Stochastic arithmetic for error estimation GPU acceleration of numerical methods Recent Publications : Focus on compensated algorithms, half-precision validation, and numerical reproducibility in extreme-scale simulations. Notable contributions include advancing stochastic arithmetic for trustworthy HPC codes and optimizing CADNA for GPU performance. Administrative Roles : Member of the office of the department of economic sciences at Paris-Panthéon-Assas University Member of the LIP6 Scientific Council

Dusan Medvedمشاهده پروفایل

دانشیار

• Electrical Power Engineering
• Electrothermal Technology
• Power System Modeling
• +۶ مورد دیگر

Associate Professor Dušan Medved serves at the Department of Electrical Power Engineering within the Faculty of Electrical Engineering and Informatics at the Technical University of Košice. As Head of the Electricity Generation and Distribution Department, he plays a key leadership role in shaping electrical engineering education and research at the institution. His extensive teaching portfolio spans fundamental electrical engineering concepts through to specialized topics in power systems and renewable energy technologies. Medved's research interests primarily focus on power system modeling, renewable energy integration, and smart grid technologies . His work demonstrates particular expertise in photovoltaic systems, electric vehicle integration, electromagnetic field analysis, and power quality assessment. He has developed significant expertise in using EMTP-ATP software for power system transient analysis and has published extensively on modeling techniques for electrical power engineering applications. An analysis of his recent publications (2023-2024) reveals a strong emphasis on the integration of renewable energy sources into power grids, with particular attention to photovoltaic systems, electric vehicle charging infrastructure, and energy storage solutions. His work bridges theoretical modeling with practical implementation challenges, addressing critical issues such as grid stability during high renewable penetration, optimal sizing of energy storage systems, and maximizing self-consumption of locally generated renewable energy. The interdisciplinary nature of his research connects electrical engineering with energy economics and environmental considerations. Medved has been actively involved in teaching a wide range of courses including Fundamentals of Electrical Engineering, Electrothermal Technology, Electrical Energy Transformations, and Modeling in Electrical Power Engineering. His teaching materials demonstrate a hands-on approach with practical assignments covering resistance furnace design, arc steelmaking furnace analysis, and power system modeling using EMTP-ATP software. His commitment to education is evident in his development of numerous teaching resources and student projects spanning from 2012 to the present.

Rajesh Bhaskaranمشاهده پروفایل

مدرس ارشد

• Engineering Simulation
• Computational Fluid Dynamics
• Finite Element Analysis
• +۲ مورد دیگر

Rajesh Bhaskaran is a Senior Lecturer and Swanson Director of Engineering Simulation at Cornell University's Sibley School of Mechanical and Aerospace Engineering. He spearheads the 'democratization of simulation' initiative through integration of industry-standard tools into engineering education, directs the Swanson lab, and developed the globally adopted SimCafe.org platform for finite-element and CFD simulations. His educational background includes: B.Tech. in Aerospace Engineering from Indian Institute of Technology (1989) M.S. in Aerospace Engineering from Iowa State University (1992) Ph.D. in Aerospace Engineering from Iowa State University (1996) Bhaskaran's research centers on engineering applications of simulation technology, reliable deployment of advanced simulation by generalist engineers, and conceptual change in learners. His methodology transforms how students approach simulations—moving beyond button-pushing to expert-level understanding—across fluid mechanics, heat transfer, solid mechanics, and numerical analysis courses. His publications reveal a consistent focus on simulation-based engineering education, emphasizing accessible online resources (SimCafe.org) and pedagogical frameworks for CFD/FEA. Work spans practical applications from aquaculture raceways to curriculum-wide integration, demonstrating how simulation bridges theoretical concepts and real-world problem-solving for complex geometries. Key recognitions include: Dennis G. Shepherd Teaching Award, Cornell Engineering (2017) National Academy of Engineering Frontiers of Engineering Education participation (2011) Multiple academic excellence awards from IIT Madras, Iowa State, and Phi Kappa Phi Honor Society While specific advising details are unreported, Bhaskaran's global impact manifests through his free Ansys-based MOOC (200,000+ enrollments), the eCornell Fluid Dynamics Simulation Certificate, and industry partnerships that prepare engineers for simulation-driven workplaces. His Swanson lab remains central to developing open educational resources adopted by institutions worldwide. The Swanson lab under Bhaskaran's direction pioneers simulation tool deployment for educational purposes, creating scalable frameworks used across Cornell courses and global professional development. Its work with Ansys and eCornell exemplifies how academic-industry collaboration transforms engineering pedagogy through practical, accessible simulation training.

• Structural Engineering
• Computational Mechanics
• Timber Engineering
• +۳ مورد دیگر

Joonas Jaaranen is a Lecturer in the Department of Civil Engineering at Aalto University, specializing in structural engineering, computational mechanics, and sustainable construction materials. His research focuses on timber engineering, composite structures, and advanced numerical simulation techniques. High-resolution studies on glued laminated timber beam mechanics Development of finite element models for wood material behavior Innovative applications of salvaged timber in structural design Experimental validation using digital image correlation and photogrammetry Investigations into two-way timber-concrete composite systems His recent publications highlight interdisciplinary approaches combining experimental testing, computational modeling, and sustainable material utilization, particularly in timber-based structural elements and composite systems. Key methodologies include continuum-damage mechanics, nonlinear finite element analysis, and data-driven structural characterization. Contact: joonas.jaaranen@aalto.fi

Martin Hofmannمشاهده پروفایل

استاد

• Fracture Mechanics
• Crack Pattern Formation
• Forming Process Simulations
• +۳ مورد دیگر

Dr.-Ing. Martin Hofmann is a Professor at Dresden University of Technology (Technische Universität Dresden) affiliated with the Chair for Mechanics of Multifunctional Structures . His research focuses on fracture mechanics, crack pattern formation, and forming process simulations, combining theoretical analysis with experimental techniques like X-ray tomography and radiography. University: Dresden University of Technology Department: Chair for Mechanics of Multifunctional Structures Academic Rank: Professor Research Interests: Hofmann's work addresses fundamental and applied aspects of mechanical behavior in materials, including: Fracture mechanics of composite membranes Thermal shock crack scaling laws Hexagonal basalt column formation mechanisms Damage modeling for limited-ductility materials Process-induced defect analysis in mechanical joining Publication Trends: His research spans 15+ years, combining computational modeling (e.g., bifurcation analysis, GISSMO simulations) with experimental validation in both artificial and natural material systems. Key subfields include hydrogel composites, volcanic rock fracture dynamics, and advanced manufacturing defect mitigation. Labs & Teams: As chair holder, Hofmann leads research on multifunctional structures, collaborating with institutions like the American Physical Society and participating in international conferences such as ESAFORM and LS-DYNA Forum.

• Autonomous Systems
• Biomimetic Robotics
• Unmanned Underwater Vehicles
• +۷ مورد دیگر

Dr Euan W McGookin is a Senior Lecturer in Autonomous Systems & Connectivity at the University of Glasgow, based in the Aerospace Sciences division of the James Watt Building South. He coordinates Glasgow-delivered aerospace degree programmes in Singapore and serves on the IFAC Technical Committee on Marine Systems, underlining his sustained engagement with both local and international academic activities. Education: 1st Class Honours Master of Engineering in Avionics, University of Glasgow PhD in Optimisation of Sliding Mode Controllers for Marine Applications, University of Glasgow (1997) Research Interests Dr McGookin’s core expertise lies in the design, simulation, control and physical realisation of autonomous robotic systems. His work spans Autonomous Underwater Vehicles (AUVs) , Unmanned Aerial Vehicles (UAVs) , Planetary & Terrestrial Rovers , and Biomimetic Robotics . He is particularly recognised for applying biologically inspired principles to robotic locomotion, navigation and control. Complementary themes include advanced control methodologies—Sliding Mode Control, H-infinity, Inverse Model Control—optimisation heuristics, guidance & navigation, fault detection & isolation (FDI), and system health monitoring for both terrestrial and space applications. Publication Trends Across 80 publications from 1995 to 2025, his work has evolved from early genetic-algorithm-based controller optimisation for marine vessels to cutting-edge multi-rover mission planning and health monitoring for planetary exploration. Recent outputs (2022–2025) concentrate on micro-rover coordination, friction modelling for planetary soils, reinforcement-learning-driven sensor fusion, and robust health-monitoring architectures, reflecting a strategic pivot toward space robotics while retaining strong roots in control theory and autonomous systems. Scientific Awards & Fellowships Member, IFAC Technical Committee on Marine Systems Grant & Advising Narrative While specific grant values are not disclosed, his continuous funding stream is evidenced by sustained publication output, international conference leadership, and ongoing supervision of postgraduate projects. Dr McGookin advises a steady cohort of PhD and MSc students whose theses align with his research themes—ranging from rover fault diagnosis to biomimetic AUV coordination—thereby fostering the next generation of control and robotics engineers. Laboratory & Team Dr McGookin heads research activities within the James Watt Building South, leveraging interdisciplinary laboratories that integrate simulation suites, rapid-prototyping facilities for AUV and UAV subsystems, and dedicated test rigs for biomimetic propulsion and rover mobility studies. Collaborative networks extend across the University of Glasgow’s Aerospace Engineering group, Singapore Institute of Technology partners, and international consortia such as ESA and IFAC.

James Blakeمشاهده پروفایل

دانشیار

• Fluid-Structure Interaction
• Marine Vehicle Design
• Sustainable Composite Materials
• +۴ مورد دیگر

James Blake is an Associate Professor in Sustainable Composites and High Performance Marine Vehicles at the University of Southampton, where he also serves as the Director of Programmes for Maritime Engineering. His research focuses on fluid-structure interaction , sustainable composite materials , and high-speed marine craft performance , with applications in boat design, structural reliability, and experimental material analysis. Education : First-class BSc in Ship Science (1993), MSc in Maritime Engineering Science, and PhD in high-speed planing craft motion prediction from the University of Southampton. Research Groups : Member of the Southampton Marine and Maritime Institute. His academic career spans industry roles at Halyard Marine, Vosper Thorneycroft, and BMT Seatech, combined with academic leadership in maritime engineering. Key research themes include: Composite Material Analysis : Natural fiber composites, hybrid composites, and interface fracture mechanics. Marine Structural Dynamics : Skin-stiffener debonding, high-speed planing craft simulation, and lifeboat mooring stability. Sustainability Initiatives : Development of eco-friendly composite boat materials through projects like HyMedPoly and RNLI Advanced Technology Partnership. His publications (10 most recent) span composite modeling, autonomous vessel design, and marine structural reliability, reflecting interdisciplinary collaborations with EPSRC, European Union, and RNLI. Awards include Fellow of the Higher Education Academy and leadership roles in the World Sailing Sustainability Commission. Teaching : Delivers modules on yacht design (SESS3027), composite engineering (SESG6039), ship science fundamentals (SESS6065), and marine structures in fluids (SESS6071). Supervises PhD student Darren Roderick. External Roles : Invited speaker on composite boatbuilding at 2011 conferences.

• Algorithm design and analysis
• Cellular networks
• Connected cars
• +۱۱ مورد دیگر

Carla Fabiana Chiasserini is a Full Professor and Deputy Director at the Department of Electronics and Telecommunications (DET) at the Polytechnic University of Turin. She serves as a Component of the CARS@PoliTO Interdepartmental Center - Center for Automotive Research and Sustainable Mobility and acts as a Spoke leader for research and innovation activities. Her academic career spans multiple prestigious institutions and she maintains active collaborations worldwide. Professor Chiasserini's research interests span algorithm design and analysis, cellular networks, connected cars, edge computing, heterogeneous wireless networks, Internet of Things, machine learning, mobile networks, mobile services, and performance evaluation. Her work bridges theoretical algorithm development with practical applications in next-generation telecommunications systems. She leads the TNG research group at DET and focuses on Machine Learning for Networking, with specific research lines in Network Slicing in 5G, Connected autonomous cars, and Opinion dynamics in social networks. Her research aligns with Sustainable Development Goals including Industry, Innovation and Infrastructure; Sustainable Cities and Communities; and Climate Action. Her recent publications demonstrate a strong trend toward integrating machine learning with edge computing, 5G/6G systems, and automotive applications. The research spans from theoretical algorithm development to practical implementations for XR offloading, distributed service provisioning, reliability assessment of AI-based automotive systems, and satellite networking. Her work shows increasing focus on practical implementations with industry applications, particularly in the automotive sector and next-generation telecom infrastructure. Best Paper Award - Wireless Telecommunications Symposium (WTS) 2018 Best Paper Award - IEEE WoWMoM 2016 Best Paper Award Runner-up at ACM MSWiM 2016 Top Paper Award at the ACM CoNEXT 2016 Cloud-Assisted Networking (CAN) Workshop Best Paper Award at SPACOMM 2014 Best Paper Award at AD HOC NOW 2014 2010 Editor of the Year Award for the Ad Hoc Networks journal (Elsevier) IEEE Fellow (2018-) ACM Fellow (2024-) Professor Chiasserini actively advises numerous PhD students working on cutting-edge topics in network systems, with recent graduates focusing on edge services in 5G networks, resource-aware learning in mobile networks, and deployment of microservices at the network edge. She leads multiple significant research grants including O-RAN (2024-2027), CSI-Future (2023-2025), RESTART - Spoke 4 (2023-2025), PREDICT-6G (2023-2025), and several others funded by PNRR, EU Horizon programs, and industry partnerships. Her work has substantial practical impact through numerous patents including OffloaDNN and SEM-O-RAN. She leads the TNG research group within the Department of Electronics and Telecommunications and participates in the CARS@PoliTO Interdepartmental Center for Automotive Research and Sustainable Mobility. Her laboratory work focuses on practical implementations of theoretical concepts, particularly in the areas of connected vehicles, edge computing, and 5G/6G systems. She maintains strong industry connections through projects with Intel Corporation and other technology partners, ensuring her research has direct real-world applications.

Andre Filiatraultمشاهده پروفایل

استاد مدعو

• Earthquake Engineering
• Structural Dynamics
• Seismic Isolation
• +۴ مورد دیگر

Andre Filiatrault is an Adjunct Professor at the Department of Civil Engineering within McMaster University . His research spans seismic engineering, structural dynamics, and performance-based design, focusing on nonstructural components, damping systems, and wood/steel structures. Key contributions include seismic isolation, passive energy dissipation, and experimental validation of building systems. Research Interests: Earthquake Engineering, Structural Dynamics, Performance-Based Seismic Design, Nonstructural Components, Steel and Wood Structures, Seismic Retrofit Recent Trends: Advanced studies on viscous dampers, seismic loss estimation for acceleration-sensitive elements, and integration of building information modeling with seismic analysis.

Michael Swiftمشاهده پروفایل

استاد

• Operating Systems
• Computer Architecture
• Device Drivers
• +۴ مورد دیگر

Michael Swift is Professor of Computer Sciences at the University of Wisconsin-Madison within the College of Letters and Sciences. He leads the Sonar research group and co-leads the Multifacet architecture group with Mark Hill, while contributing to the Wisconsin Institute on Software-defined Datacenters (WISDoM). His research centers on operating system/hardware interaction, with seminal work in device driver reliability (Nooks, Shadow Drivers), memory systems (storage-class memory integration), and cloud security. Projects like Microdrivers and Carburizer address driver complexity and fault tolerance, while recent work explores learned OS policies and heterogeneous processor support. Analysis of his 2023-2025 publications reveals intensifying focus on memory tiering, security in cloud environments, and hardware-accelerated systems, with growing integration of machine learning for system optimization. Key awards include: Best paper award at OSDI 2004 Best paper award at SOSP 2003 Best paper award at the 3rd Asia-Pacific Workshop on Networking (2019) Professor Swift mentors numerous PhD students (current and past) and secures research funding through NSF grants CNS-0915363 and CNS-0745517 plus Google support. He serves as Instructional Program Director and chairs both the Space committee and Diversity, Equity, and Inclusion committee. The Sonar group drives innovation in system support for emerging hardware technologies, while Multifacet focuses on computer architecture advancements, particularly in heterogeneous computing and memory systems.

Patrick Brewickمشاهده پروفایل

استادیار

• Data Analytics
• System Identification
• Structural Health Monitoring
• +۱۰ مورد دیگر

Patrick Brewick is an Assistant Professor in the Department of Civil and Environmental Engineering and Earth Sciences at the University of Notre Dame. His research bridges data analytics, mechanics, and computational modeling to address challenges in structural resilience and material behavior under extreme conditions. Ph.D., Columbia University (2014) M.S., Civil Engineering and Engineering Mechanics, Columbia University (2010) B.S., Civil Engineering, University of Notre Dame (2009) Professor Brewick’s work focuses on transforming noisy or incomplete data into accurate predictive models. Key research areas include: System Identification : Uncovering physics of seismic protection systems. Uncertainty Quantification : Developing Bayesian frameworks for model calibration. Damage Detection : Identifying nonlinear structural transitions. Microstructural Modeling : Investigating corrosion and material heterogeneity. Hybrid Modeling : Balancing high- and low-fidelity simulations. Wind Energy Applications : Using distributed fiber optics for turbine monitoring. His publications span disciplines like structural mechanics, materials science, and biomedical engineering, emphasizing multi-fidelity approaches and probabilistic methods. Current projects address infrastructure resilience against climate change, naval structural reliability, and microstructural impacts on corrosion. The Brewick Group collaborates extensively, offering open-source tools and inviting partnerships. Students in his lab, such as Ph.D. candidates Reza Farzad and Jichuan Tang , explore cutting-edge applications in structural dynamics and material modeling. Before Notre Dame, Prof. Brewick conducted research at the U.S. Naval Research Laboratory, focusing on predictive modeling for heterogeneous systems, including marine structures and brain tissue mechanics.

Thuan Yew Edward Chuahمشاهده پروفایل

مدرس

• Large-scale systems dependability
• Network security
• HPC reliability
• +۱۱ مورد دیگر

Dr. Thuan Yew Edward Chuah is a Lecturer in the Computing Science Department within the School of Natural and Computing Sciences at the University of Aberdeen. He received his PhD in Computer Science from the University of Warwick in 2020, following an MSc in Distributed Systems Engineering from Lancaster University (2004) and a BSc (Hons) in Computer Science from the University of Leicester (2003). Prior to his academic career, he worked in Singapore for approximately 11.5 years as a research engineer (8 years), software engineer (1.5 years), and lecturer (2 years). Dr. Chuah's educational background includes: PhD in Computer Science, University of Warwick (2020) MSc in Distributed Systems Engineering, Lancaster University (2004) BSc (Hons) in Computer Science, University of Leicester (2003) His research focuses on large-scale systems dependability, with particular emphasis on two key areas: network security and HPC reliability. Initially focusing on reliability aspects of dependability, his current work investigates security in large networks through data-driven approaches for identifying, detecting, and predicting threats. He also develops data-driven methods for diagnosing failures and predicting faults in large cluster systems. Dr. Chuah has developed several system log-based diagnostics tools including FDiag (a failure diagnostics toolkit), ANCOR (an anomaly-correlation approach), and CORRMEXT (a workflow for identifying error propagation patterns). His work has practical applications, with FDiag being used by HPC systems administrators at the Texas Advanced Computing Center to uncover previously unknown causes of compute node soft lockups. Dr. Chuah's publication record shows a consistent research trajectory in system dependability, with recent publications (2023-2025) increasingly focusing on applying deep learning techniques to network security challenges and failure prediction in cluster systems. His research bridges the gap between theoretical computer science and practical system administration needs, with publications spanning both high-performance computing reliability and cybersecurity domains. His notable scientific achievements include: J. Tinsley Oden Faculty Fellowship at The Oden Institute for Computational Engineering and Sciences, University of Texas at Austin (2011) The Alan Turing Institute Doctoral Studentship (2016-2020) Dr. Chuah actively supervises research students, with MR MOHAMMAD ALSAAD listed as a current supervisee. He has secured research funding as Principal Investigator for "An AI-based Approach for Detecting Advanced Persistent Threats (APT) in Large Networks" through an EPSRC SPRITE+ Academic-Industry-Meeting secondment grant (2024-2025, £10k). He serves the academic community through various roles including TPC member for IEEE conferences, track chair for international conferences, and reviewer for numerous journals including Expert Systems with Applications, IEEE Transactions on Big Data, and ACM Computing Surveys. He teaches a variety of courses ranging from Learning from Data to Software Engineering and Algorithm Analysis to both undergraduate and postgraduate students at the University of Aberdeen.

• Experiential Learning
• Teacher Induction
• Professional Development of Agricultural Educators
• +۵ مورد دیگر

Dr. Jon Ramsey is a Professor in the Department of Agricultural Education, Communication & Leadership at Oklahoma State University. He holds a PhD, MS, and BS in Agricultural Education from Oklahoma State University. His research focuses on experiential learning in agricultural education, teacher induction, and professional development of agricultural educators. He has received numerous awards, including the Oklahoma State University Award for Academic Advisement and the Distinguished Agricultural Educator Award. Dr. Ramsey teaches courses such as AGED 3101: Laboratory and Clinical Experiences and AGED 4200: Student Teaching in Agricultural Education. He has led grants including the USDA-funded ‘An Alternative Approach to Preparing Teachers to Develop a New Generation of Agricultural Leaders.’ Education: PhD in Agricultural Education, Oklahoma State University (2009) MS in Agricultural Education, Oklahoma State University (1997) BS in Agricultural Education, Oklahoma State University (1986) Recent Grants: USDA Grant: An Alternative Approach to Preparing Teachers (2024–2027) Turf Management Curriculum Development (2022–2025) Assessment of Teacher Wellness (2020–2021) His research emphasizes bridging theory and practice in agricultural education, with a focus on teacher support and program effectiveness. He has advised numerous graduate students and contributed to curriculum development for secondary and adult agricultural education programs.