Find Academic Supervisors

James BuckleyView profile

Lecturer

• Ecology
• Conservation Biology
• Plant Defense Mechanisms
• +3 more

Dr. James Buckley is a Lecturer in Ecology at the School of Biological and Marine Sciences, University of Plymouth. He specializes in plant defense mechanisms, ecological genetics, and climate change impacts on plant populations. His teaching roles include leading the BSc Conservation Biology programme and instructing modules such as Ecology and Diversity of Life, Statistics, and Applied Conservation Biology. He is actively involved in field courses annually, combining theoretical and practical ecological research. Research focuses on plant adaptation to environmental changes, including herbivore interactions, genetic diversity under inbreeding conditions, and evolutionary responses to climate shifts. Key themes include plant chemical defenses, transposable element roles in maintaining heterozygosity, and the ecological consequences of warming on high-elevation species. His work contributes to Sustainable Development Goals related to life on land (SDG 15) and climate action (SDG 13). No scientific awards are listed, though his publications reflect impactful contributions to ecological and evolutionary research. Advising and grant details remain unspecified, while his involvement in fieldwork underscores a commitment to applied conservation and ecological education.

Gigliola VagliniView profile

Professor

• Distributed Systems Verification
• Model Checking
• Machine Learning Applications
• +2 more

Gigliola Vaglini is Full Professor of Computer Engineering at the University of Pisa's Department of Information Engineering. She teaches Software Systems Engineering and Databases, with research focusing on formal specification and verification of concurrent/distributed systems. Her work integrates model checking methodologies with machine learning techniques for industrial anomaly detection and mobile security applications. She has participated in multiple research projects funded by the Italian Ministry of University and Research, National Research Council, and European Community. Research Focus: Vaglini's work bridges theoretical computer science and practical applications, developing verification frameworks for complex systems while creating AI solutions for real-world problems. Her current investigations span swarm intelligence coordination, structural monitoring via digital twins, and multimodal deep learning architectures. Recent publications demonstrate cross-disciplinary approaches combining formal methods with machine learning, particularly in environmental monitoring, structural engineering, and neural architecture design. This reflects a consistent pattern of translating theoretical computer science concepts into applied technological solutions.

Kate LajthaView profile

Professor

• Biogeochemistry
• Soil Carbon Sequestration
• Nutrient Cycling
• +3 more

Kate Lajtha is a Professor in the Department of Crop and Soil Science at Oregon State University's College of Agricultural Sciences. Her research focuses on biogeochemical cycling in disturbed ecosystems, particularly nutrient dynamics, soil organic matter formation, and climate change impacts. She holds a Ph.D. from Duke University (1986) and a B.A. from Harvard University (1979), with prior academic positions at Boston University and Ohio State University. Dr. Lajtha's research examines detrital controls on soil carbon, nitrogen attenuation in terrestrial ecosystems, and biogeochemical responses to environmental change. Her work integrates field experiments (like the long-term DIRT network) with molecular analysis to understand carbon stabilization mechanisms. Current investigations include wildfire impacts on soil carbon, climate gradient studies, and litter manipulation effects. Her publications demonstrate consistent focus on soil carbon dynamics under changing climate conditions, with recent work exploring: Wildfire legacy effects on carbon persistence Root versus litter contributions to soil organic matter Climate-driven alterations in forest carbon pools Land management impacts on carbon sequestration Awards & Honors: Fellow, American Geophysical Union (2020) ASLO John Martin Award (2018) Springer Woman Scientist of Merit (2013) R.M. Wade Teaching Excellence Award (2021) Murray Buell Award, ESA (1986) She serves as Editor-in-Chief of Biogeochemistry and leads multiple committees for the American Geophysical Union. Dr. Lajtha co-founded OSU's sustainability degree program and teaches Environmental Ecology (BI 306H) and Introduction to Environmental Science (SUS 102).

Jocelyn A. SessaView profile

Associate Professor

• Ocean acidification
• Mollusks
• Climate change
• +1 more

Jocelyn A. Sessa, PhD, is an Associate Professor in the Department of Biodiversity, Earth and Environmental Science at Drexel University. She is also an Associate Curator in the Invertebrate Paleontology Department at the Academy of Natural Sciences of Drexel University. Her research integrates fossil and modern data to study mollusk faunas' responses to environmental changes across geological timescales. Education : PhD in Geosciences (Pennsylvania State University, 2009), MS in Geology (University of Cincinnati, 2003), BA in Geological Sciences (SUNY Geneseo, 2000). Her work focuses on ocean acidification, climate change, and paleobiology, using mollusks as model organisms. She investigates mass extinctions, past climatic shifts, and employs stable isotope analysis and CT scanning techniques. Her recent publications highlight mollusk responses to global warming and projects like the extending Ocean Drilling Pursuits (eODP) to synthesize geological data. Students mentored by Sessa have contributed to studies on pteropods, ammonites, and sediment traps, with their work often appearing in journals like Frontiers in Marine Science and Geological Society of America Bulletin . Fieldwork spans the US Gulf Coast, California, Angola, and Romania. Her scholarship emphasizes accessibility in science, with outreach efforts since 2007 targeting under-represented communities in the Philadelphia area.

Lorrie ReaView profile

Research Professor

• Marine Ecotoxicology
• Stable Isotope Analysis
• Mercury Dynamics in Ecosystems
• +3 more

Lorrie Rea is a Research Professor at the University of Alaska Fairbanks, affiliated with the Marine Ecotoxicology and Trophic Assessment Laboratory (METAL) and the Water and Environmental Research Center. Her work focuses on mercury dynamics, stable isotope analysis, and physiological adaptations in marine mammals. Current projects include mercury transport in Aleutian food webs Stable isotope applications for diet assessment Physiological responses to environmental stressors Biochemical adaptations during marine mammal fasting Research grants from NSF, NOAA, and industry partners fund her work on contaminant pathways, conservation physiology, and marine ecosystem health. Her publications examine mercury concentrations, lipid dynamics, and biomarker development in Steller sea lions and related species. Collaborations span multiple institutions including the Alaska Department of Fish and Game and Hilcorp Alaska.

Ali KeyvaniView profile

Lecturer

• Environmental Engineering
• Sediment Transport
• Fluid Dynamics
• +2 more

Ali Keyvani is a Lecturer in the Department of Civil and Environmental Engineering at the University of Houston . His work focuses on sediment dynamics in transitional environments between rivers and marine systems, particularly examining flocculation processes, settling velocity equations, and hydroacoustic monitoring techniques. Email: akeyvanighamsari2@uh.edu Office: N107 Engineering Building 1, Houston, TX 77204-4003 Phone: 713-743-4250 Research Interests include: Sediment flocculation under variable shear conditions Hydroacoustic measurement of suspended particles Settling velocity modeling for cohesive sediments River-mouth plume dynamics and deposition Environmental fluid mechanics applications Scientific Contributions span studies on: Mud aggregation in turbulent shear fields Instrumentation challenges in floc size measurement Sediment yield analysis in river systems

Reza MolaeiView profile

Assistant Professor

• Fatigue and Fracture
• Multiaxial Fatigue
• Additive Manufacturing
• +3 more

Reza Molaei is an Assistant Professor in the Department of Mechanical Engineering at Auburn University. He holds a Ph.D. and M.S. from the University of Memphis and Sharif University of Technology, respectively, and a B.S. from Sharif University of Technology. His research focuses on fatigue and fracture mechanics, multiaxial fatigue, additive manufacturing, and mechanical behavior of materials. He explores topics such as defect characterization in additively manufactured metals, effects of surface treatments like laser shock peening, and fatigue performance under complex loading conditions. Molaei’s work emphasizes experimental and modeling approaches to understand fatigue behavior in materials like Ti-6Al-4V and 17-4 PH stainless steel, with applications in aerospace and industrial components. He is affiliated with the National Center for Additive Manufacturing Excellence (NCAME) at Auburn. His publications analyze crack propagation, notch effects, and the impact of processing parameters on material integrity. Current research trends include optimizing additive manufacturing processes to enhance fatigue life and developing predictive models for multiaxial fatigue scenarios.

J. Crawford DownsView profile

Professor

• Ocular biomechanics
• Glaucoma
• Computational modeling
• +3 more

J. Crawford Downs is a Professor in the Department of Ophthalmology at the University of Alabama at Birmingham (UAB). He serves as Vice-Chair of Research and founding director of UAB's Ocular Biomechanics and Biotransport Program, which investigates glaucoma mechanisms through computational/experimental methods. BA & MA in Economics from Tulane University Undergraduate coursework at University of New Orleans M.S. & Ph.D. in Biomedical Engineering from Tulane University Research focuses on intraocular pressure (IOP) effects, aging, and African heritage in glaucoma progression. His work includes developing IOP telemetry methods and eye-specific finite element models. Recent publications address viscoelastic modeling, translaminar pressure gradients, and ocular perfusion dynamics in nonhuman primates. Current affiliations include: Heersink School of Medicine at UAB Ocular Biomechanics Laboratory Collaborations with LSU Eye Center and Devers Eye Institute

Amin EtminanView profile

Assistant Professor

• Energy Systems
• Thermo-fluids
• Fluid Dynamics
• +5 more

Amin Etminan is a Teaching Assistant Professor in the Mechanical Engineering Department at Memorial University of Newfoundland (MUN). He holds a Ph.D. from MUN (2022) and has 11 years of academic experience, including roles as an instructor at Azad University (Iran) and a postdoctoral fellow at MUN's Microfluidics Lab. His expertise spans energy systems, thermo-fluids, multiphase flow, and sustainable energy. He teaches thermo-fluids courses and supervises projects in energy systems, two-phase flows, and CO2 capturing. Education: B.Eng. (Persian Gulf University, 2004), M.Sc. (Yazy University, 2007), Ph.D. (MUN, 2022). Professional memberships include CSME, ASME, and reviewer roles at journals like Nature Scientific Reports and ASME Transactions. Awards include the Dr. Jack Clark Graduate Award (2020) and top research awards (2011-2013). Research focuses on fluid dynamics, heat transfer in micro/milli-channels, Taylor flow, and nanoparticle-enhanced heat exchangers. His recent work includes modeling liquid-based cooling systems for gaming computers and CO2 capturing technologies. Publications span 50+ peer-reviewed articles in journals like International Journal of Heat and Mass Transfer and Canadian Journal of Chemical Engineering . Grants include Mitacs Accelerate (2023) and PEGNL Professional Development (2023). His lab collaborations involve experimental and numerical analysis of multiphase flows, with applications in renewable energy systems and thermal management.

David McKinnonView profile

Professor

• Homeostatic Regulation of Ion Channels
• Cardiac Electrophysiology
• Neurocardiovascular Stress Responses
• +3 more

David McKinnon is a Professor of Neurobiology and Behavior at the Renaissance School of Medicine, State University of New York at Stony Brook. He holds a Ph.D. in Physiology from the Australian National University (1987) and has been at Stony Brook since 1991, progressing to full professor in 2005. His research focuses on homeostatic regulation of ion channel expression, particularly in cardiac and neuronal systems. Key areas include understanding how ion channel expression adapts to genetic perturbations and environmental stressors like chemotherapy. Current projects investigate long-term stress effects on nervous and cardiovascular systems and cognitive impacts of chemotherapeutic agents. McKinnon's lab employs conditional knockout mice to study ion channel loss in adult organisms. Notable contributions include identifying KCNQ2/KCNQ3 as molecular correlates of the M-channel and clarifying the role of Kv4.3 channels in transient outward currents. His work bridges evolutionary biology and molecular physiology, exploring how genetic changes influence physiological systems. Publications highlight advanced techniques like single-cell RNA sequencing and computational modeling to analyze ion channel distribution and stress-induced transcriptional changes. Collaborations include Barbara Rosati (Research Assistant Professor) and Shian-Ren Liou (Postdoctoral Associate). Lab resources include the Thomas Hartman Center for Parkinson's Research and affiliate institutes.

Hadi AbbaszadehpeivastiView profile

Researcher

• Optimization Methods
• Machine Learning
• Convergence Rate Analysis
• +4 more

Hadi Abbaszadehpeivasti is a researcher at the Department of Econometrics and Operations Research within the Tilburg School of Economics and Management at Tilburg University. His work focuses on optimization methods, machine learning, and convergence rate analysis using semidefinite programming techniques. Education: Master’s Degree in Statistics (Normal and Generalized Gamma Estimation), Sabanci University (2019–2020) Master’s Degree in Stochastic Kriging Meta-Modeling for Simulation Optimization, Sharif University of Technology (2012–2014) His research interests include convergence rate analysis of first-order optimization algorithms, performance estimation in non-convex settings, and applications of semidefinite programming to machine learning. He explores conditions like the Polyak–Łojasiewicz inequality for linear convergence and works on saddle-point problems and ADMM variants. Recent publications span convex-concave optimization, gradient descent-ascent methods, and ADMM convergence analysis, with a focus on non-asymptotic guarantees and exact worst-case bounds. His studies often bridge theoretical insights with practical algorithm design. His work also involves collaborations with researchers like Etienne de Klerk and Moslem Zamani, contributing to operations research and computational optimization theory.

Zhe ShandianView profile

Associate Professor

• Artificial Intelligence
• Machine Learning (Theory and Modeling)
• Physics-informed Machine Learning
• +7 more

Zhe Shandian is an Associate Professor at the Kahlert School of Computing, University of Utah. His research focuses on advancing machine learning methodologies, particularly in physics-informed machine learning, operator learning, and Bayesian methods. He explores applications in differential equations, multi-omics data, and engineering simulations. His work emphasizes scalable algorithms and data efficiency in complex systems. Education details are not explicitly provided in the text, but his professional trajectory aligns with a strong computational and mathematical background. Research interests include developing novel frameworks for neural operators, symbolic regression, and functional Bayesian decomposition. Key research trends from his articles highlight advancements in physics-guided AI models, multi-fidelity simulation, and scalable kernel-based methods. His contributions span domains like material science, cancer prediction, and traffic flow modeling. No scientific awards are mentioned in the provided text. Zhe Shandian has not listed any advisees, and specific grants or labs are not detailed here. His work often involves collaboration across disciplines, leveraging both theoretical and applied machine learning techniques.

Jianya LuView profile

Lecturer

• Stochastic Processes
• Limit Theory
• Stochastic Algorithms
• +4 more

Dr. Jianya Lu is a Lecturer in the Department of Mathematical Sciences at the University of Essex, affiliated with the School of Mathematics, Statistics and Actuarial Science (SMSAS). He holds a PhD in Mathematics from the University of Macau (2022), following an MS.c in Probability Theory (Central South University, 2018) and a BS.s in Applied Mathematics (Henan Normal University, 2015). His research focuses on stochastic processes, stochastic algorithms, Stein’s method, and their applications in statistical learning, particularly in reinforcement learning and deep neural networks. He has contributed to methodologies in stochastic dynamics for algorithm interpretation and optimization. Education: PhD in Mathematics, University of Macau, 2022 MS.c in Probability Theory, Central South University, 2018 BS.s in Applied Mathematics, Henan Normal University, 2015 Research Interests: Dr. Lu’s work bridges theoretical probability and applied machine learning. Key areas include: Stochastic Algorithms : Analysis of reinforcement learning, deep neural networks, and stochastic gradient methods. Statistical Learning : Federated learning frameworks, distribution estimation via GANs, and change-point detection in time series. Limit Theorems : Invariance principles, moderate deviations, and convergence of stochastic processes. Publications: Recent work emphasizes algorithmic approximation (e.g., DQNs via stochastic delay equations) and statistical methodologies (e.g., Euler-Maruyama scheme analysis). Themes include optimization, numerical analysis, and probabilistic modeling in high-dimensional spaces. Labs/Teams: No specific lab affiliations mentioned, but his research aligns with computational statistics and stochastic modeling groups at the University of Essex.

Ellen DorrepaalView profile

Professor

• Plant Ecology
• Climate Change Ecology
• Tundra Ecosystems
• +5 more

Ellen Dorrepaal is a Professor in the Department of Ecology, Environment and Geoscience at Umeå University's Faculty of Science and Technology. She is based at the Abisko Scientific Research Station (CIRC) in northern Sweden, conducting field research in subarctic tundra near Abisko (68°21'N) and boreal forests near Arvidsjaur (65°59'N). Her research focuses on plant ecology in cold ecosystems , particularly how plants manipulate their micro-environments and interact with neighbors to survive harsh conditions. Key interests include: Climate change impacts on northern ecosystem functioning Plant-microbe interactions in carbon cycling Peatland and permafrost responses to warming Experimental manipulations of climate and vegetation Analysis of her recent publications reveals strong emphasis on Arctic carbon dynamics , with 12/15 articles examining carbon fluxes under climate change. Her work integrates field experiments (open-top chambers, snow manipulation), mesocosm studies, and global meta-analyses, frequently collaborating across Nordic and international networks. Notable methodological contributions include standardized warming experiments through the ITEX Network and novel approaches to studying Sphagnum metabolites. Her research group participates in long-term projects like the 2020 "Syntheses of decomposition and respiration responses across space and time," utilizing the unique Arctic environment of northern Sweden as a natural laboratory for climate change research.

Heidi BurdettView profile

Associate Professor

• Marine Biology
• Climate Change Mitigation
• Ecosystem Conservation
• +3 more

Heidi Burdett is an Associate Professor at Umeå University and affiliated with the Umeå Marine Sciences Centre (UMF). Her research focuses on understanding the fundamental mechanisms of photosynthesis in coastal marine environments and applying this knowledge to sustainable conservation challenges such as habitat restoration, carbon burial, and biodiversity loss. She leads a multidisciplinary team working across coralline algal reefs, mangroves, and coral reefs, emphasizing photosynthetic strategies under extreme light conditions. As Editor-in-Chief of Aquatic Conservation , she advocates for research-informed conservation policies. Her work integrates environmental monitoring, policy engagement, and community collaboration. Current research includes the impact of climate change on marine ecosystems, blue carbon dynamics, and coastal resilience. She supervises PhD students like Vu Hoang Long (SE Asia blue carbon policy) and Cristian Ramirez Gutierrez (optical properties of coralline algae). Ongoing projects are funded through grants focusing on environmental change experimentation and marine spatial planning. Burdenett actively participates in international conferences like the One Ocean Science Congress (OOSC), presenting on topics such as blue carbon ecosystems and policy. Her lab at UMF supports fieldwork, mesocosm experiments, and collaborative initiatives to bridge science with societal needs. She emphasizes open science, editorial careers, and advancing equity in marine research.