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Tiffany SchrieverView profile

Associate Professor

• Community and ecosystem ecology
• Freshwater ecology
• Herpetology
• +4 more

Dr. Tiffany Schriever is an Associate Professor jointly appointed in the Department of Biological Sciences and the School of Environmental, Geography, and Sustainability at Western Michigan University. Her research focuses on community and ecosystem ecology in freshwater habitats, emphasizing how environmental variability influences ecological dynamics across scales. Key areas include hydrology's impact on communities, stable isotope-based trophic studies, and biodiversity patterns in temporary water bodies. Education : Ph.D., Ecology and Evolutionary Biology, University of Toronto (2010) Postdoctoral Research, Oregon State University (2010-2012) M.S., Biology, Southeastern Louisiana University (2005) B.S., Biology, Winona State University (2003) Research Interests : Dr. Schriever investigates freshwater ecosystems, particularly wetlands and streams, exploring topics such as hydrologic variability effects, food web structures using stable isotopes, and functional traits influencing biodiversity. Her lab employs experimental and comparative field methods, with recent focus on Great Lakes interdunal wetlands and montane desert streams. Awards & Grants : While specific awards are not listed, her active research program suggests sustained grant support from environmental agencies or foundations, given the complexity of her fieldwork and isotopic analyses. Lab & Advising : Her research group includes PhD students Adam Austin and Sara Diller, and M.S. student Jennifer Shamel. The Schriever Lab maintains an active webpage and collaborates widely, as evidenced by publications in journals like Ecosphere and Ecology. Labs/Teams : Primary affiliation with the Schriever Lab at Western Michigan University, focusing on freshwater ecology and environmental dynamics. Collaborations likely exist with regional conservation agencies and universities.

John CressmanView profile

Associate Professor

• Neuronal Dynamics
• Non-Equilibrium Physics
• Biophysics
• +3 more

John Cressman is an Associate Professor in the Physics & Astronomy Department at George Mason University, with affiliations in the Neuroscience Program and the Krasnow Institute for Advanced Study. His research focuses on dynamical systems in driven systems, particularly exploring their roles in brain function and non-equilibrium physics. He investigates transient correlated dynamics in biological processes and natural phenomena like tornados and fluid systems. Cressman's work bridges physics and neuroscience, addressing topics such as ion concentration dynamics in neurons, seizure mechanisms, and energy flow in neuronal systems. His research interests emphasize understanding how transient dynamical structures influence biological and physical systems, with a strong focus on neuronal behavior and the physics of non-equilibrium systems. Key themes include the interplay of excitatory and inhibitory conductances during seizures, ion concentration homeostasis, and the application of advanced imaging techniques like NIR-II fluorescent nanoprobes for biomedical applications. Recent articles highlight innovations in nanoparticle-based sensing and imaging, including DNA-based sensors for bioelectrical signals and fluorescent probes for tumor imaging. These studies reflect a trend toward integrating biophysics with cutting-edge nanotechnology for medical and neuroscientific advancements. Cressman’s work also explores turbulence and energy dissipation in complex systems, linking statistical physics principles to experimental observations. Labs and collaborations are centered at the Krasnow Institute, where interdisciplinary approaches to neurophysics and systems biology are prioritized. His research has implications for understanding neurological disorders and developing novel diagnostic tools.

Stephen AncoView profile

Professor

• Nonlinear Differential Equations
• Symmetry Analysis
• Integrability and Solitons
• +4 more

Stephen Anco is a Professor in the Department of Mathematics and Statistics at Brock University's Faculty of Mathematics and Science. His research focuses on nonlinear differential equations, symmetry analysis, integrability, solitons, and mathematical physics. He received his BSc from Caltech and MS/PhD from the University of Chicago. Anco's research interests include nonlinear wave equations, geometric curve flows, conservation laws, and integrable systems. His work connects mathematical physics with applications in fluid dynamics, magnetohydrodynamics, and gauge field theories. His publications demonstrate strong themes in soliton dynamics, conservation law derivation, and symmetry methods for PDEs. Recent work explores peakon equations, fluid invariants, and geometric integrable systems. Distinguished Research Award, Faculty of Mathematics & Science (2015) Anco has supervised over 25 graduate students (PhD and MSc) in mathematics and theoretical physics, with research spanning soliton interactions, conservation laws, and geometric flows. He maintains international collaborations and has co-authored influential textbooks on symmetry methods for differential equations.

• Operations Research
• Optimization Algorithms
• Logistics
• +6 more

Dr. Mahdi Shavarani is a Lecturer in Business Analytics at the Kent Business School, University of Kent. He holds two Ph.D.s: one in Industrial Engineering from Eastern Mediterranean University (2018), and another in Multi-Objective Optimization and Multi-Criteria Decision-Making from the University of Manchester. His research focuses on optimizing real-world business challenges through advanced algorithms, with specialties in logistics, supply chain management, transportation, and manufacturing systems. Education: - Ph.D. in Industrial Engineering, Eastern Mediterranean University (2018) - Ph.D. in Multi-Objective Optimization and Multi-Criteria Decision-Making, University of Manchester Research Interests: Dr. Shavarani specializes in developing sustainable optimization models using machine learning and interactive evolutionary algorithms. His work emphasizes reducing decision-makers' cognitive load while improving computational efficiency. Key areas include multi-criteria decision-making, dimension reduction in high-dimensional objective spaces, and simulating decision-making behaviors. He is affiliated with the Decision and Cognitive Science Research Center at Alliance Manchester Business School. Publications: His recent work explores topics like energy-efficient robotic systems, dynamic preference adaptation in algorithms, and congested facility location problems. Over 30 peer-reviewed publications demonstrate his contributions to optimization theory and practical applications. Grants and Advising: No specific grants or advising roles are detailed in the provided text. Affiliations: - Member, International Society on Multiple Criteria Decision Making - Affiliated Researcher, Decision and Cognitive Science Research Center

Tamara KucherenkoView profile

Professor

• Thermodynamic Formalism
• Smooth Ergodic Theory
• Rotation Theory
• +5 more

Tamara Kucherenko is a Professor in the Department of Mathematics at City College of New York and the CUNY Graduate Center. Her research focuses on thermodynamic formalism, smooth ergodic theory, rotation theory, and symbolic dynamics. She co-organizes the Learning Seminar on Ergodic Theory and Dynamical Systems and the Ergodic Theory and Dynamical Systems seminar at CUNY. Ph.D. in Mathematics, University of Missouri (2005) Studied at Kharkov National University, Ukraine Her work explores phase transitions, pressure functions, and entropy in symbolic and smooth dynamical systems. She has investigated Anosov diffeomorphisms on the torus, flexibility of pressure functions, and localized equilibrium states. Recent projects include analyzing rotation sets and their geometric properties, with collaborations at institutions like CIRM, BIRS, and CUNY. Co-organized the 2025 New Directions in Thermodynamic Formalism conference in France Organized the 2025 Mina Rees NY Women and Math Conference at CUNY Co-organized workshops on computability of Markov partitions and pressure functions

Shekhar GardeView profile

Professor

• Hydrophobic Interactions
• Biophysics
• Nanotechnology
• +3 more

Shekhar Garde serves as the Thomas R. Farino Jr. ’67 and Patricia E. Farino Dean of the School of Engineering and the Elaine S. and Jack S. Parker Chaired Professor of Chemical and Biological Engineering at Rensselaer Polytechnic Institute. He holds a B.Sc. from the University of Bombay (1992) and a Ph.D. in Chemical Engineering from the University of Delaware (1997), followed by a director’s fellowship at Los Alamos National Labs (1997–1999). As department head (2007–2014) and dean since 2014, he has transformed the Chemical and Biological Engineering department through faculty recruitment, curriculum expansion, and student body growth. His research focuses on molecular-level phenomena, particularly the role of water in biological systems and hydrophobic interactions. Garde has published over 100 papers (12,500+ citations) and delivered 150 invited talks. Honors include the NSF CAREER Award, AAAS Fellowship, and leadership in the award-winning Molecularium Project educating children through digital media. He co-founded the NanoSpace website and the IMAX film Molecules to the MAX! , recognized with a 'Best of the Web' award. His academic leadership includes establishing the Howard P. Isermann Department’s teaching awards and fellowships targeting underrepresented groups. Garde’s work spans interfacial science, nanotechnology, and educational outreach, emphasizing interdisciplinary collaboration and societal impact.

Yuri V LvovView profile

Professor

• Mathematical Physics
• Nonlinear Phenomena
• Wave Turbulence Theory
• +7 more

Yuri V Lvov serves as a Professor in the Department of Mathematical Sciences within Rensselaer Polytechnic Institute's School of Science. His academic appointments include a primary affiliation with RPI where he maintains an active research program and teaches advanced mathematics courses including Numerical Computing, Multivariable Calculus, and Geophysical Fluid Dynamics. Lvov's research centers on mathematical physics and nonlinear phenomena, with particular focus on semiconductor laser theory, nonlinear and fiber optics, surface water waves, acoustic waves, and gas lasers. His work develops and applies weak turbulence theory to complex wave systems across diverse physical domains. Key research themes include energy transfer mechanisms in wave turbulence, thermalization processes in nonlinear lattices, and oceanic internal wave dynamics. His publication record reveals strong emphasis on ocean mixing mechanisms (2022-2025), with multiple papers explaining how interacting internal waves drive global ocean circulation patterns. Earlier work (2015-2020) established foundational connections between Fermi-Pasta-Ulam systems and wave turbulence theory. Current research integrates scale-separated modeling approaches with field data validation for climate prediction applications. NSF CAREER award in applied mathematics (2001) NSF Collaboration in Mathematical Sciences (2004) Lvov maintains active collaborations with oceanographers and physicists worldwide, particularly with Kurt Polzin on internal wave dynamics. His research combines theoretical development with numerical simulations and observational data analysis. Current projects focus on quantifying energy fluxes in oceanic internal waves and developing predictive models for climate systems. He leads computational efforts using wave turbulence frameworks to explain anomalous mixing patterns observed in global ocean datasets.

Graham CoxView profile

Assistant Professor

• Spectral Theory
• Geometric Analysis
• Topological Methods
• +2 more

Graham Cox is an Assistant Professor in the Department of Mathematics and Statistics at Memorial University of Newfoundland. His research applies geometric and topological methods to spectral theory stability problems, with particular focus on fluid flows and reaction-diffusion systems. He holds a Ph.D. from Duke University where he studied under Hubert Bray, and previously held positions at Pennsylvania State University and University of North Carolina. Cox is actively seeking graduate students at both MSc and PhD levels to work on problems involving spectral theory, geometric analysis, and partial differential equations.

Jay A. CampbellView profile

Visiting Assistant Professor

• Exercise Physiology
• Biostatistics
• Human Performance
• +3 more

Jay A. Campbell, PhD , is a Visiting Assistant Professor in the Department of Health and Exercise Science at Wake Forest University . He teaches courses such as Statistics in the Health Sciences , Human Physiology , and Exercise Physiology , focusing on practical applications in health and performance contexts. BS in Human Performance/Kinesiology from University of Alabama MS in Exercise Physiology from University of Alabama PhD in Exercise Physiology with a minor in Biostatistics from Springfield College and University of Alabama His research explores human performance strategies , recovery practices , and assessment technologies in sport and tactical environments. Recent publications emphasize recovery mechanisms , muscle fatigue , bone health , and military training optimization , using methodologies like collagen supplementation , neuromuscular testing , and vascular reactivity analysis .

Abhimanyu GuptaView profile

Professor

• Econometrics
• Economic History
• Spatial Econometrics
• +3 more

Professor Abhimanyu Gupta is an academic at the University of Essex specializing in econometrics and economic history. His research spans theoretical and applied econometrics, with a focus on spatial econometrics and statistical theory. PhD (London School of Economics, 2013) MSc (London School of Economics, 2008) BA (University of Delhi, 2006) His key research areas include: Spatial Autoregressive Models High-Dimensional Parameter Estimation Credit Market Network Analysis Robust Time Series Inference Recent publications analyze spatial interaction functions, financial networks, and nonparametric prediction methods. Awards include grants from the Leverhulme Trust and British Academy . He supervises PhD students in economics and teaches econometric methods courses.

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.

Ian F. PutnamView profile

Professor

• Operator Algebras
• C*-Algebras
• Topological Dynamics
• +3 more

Ian F. Putnam is a Professor in the Department of Mathematics and Statistics at the University of Victoria. He holds a Ph.D. from the University of California, Berkeley. His research focuses on operator algebras, particularly C*-algebras and their connections to topological and symbolic dynamics, K-theory, and noncommutative geometry. He is a Fellow of the Royal Society of Canada and the American Mathematical Society. Education: - Ph.D., Mathematics, University of California, Berkeley Research Interests: - Dynamical systems (topological, symbolic, hyperbolic) - Operator algebras (C*-algebras, groupoid C*-algebras) - K-theory and noncommutative geometry - Smale spaces and homology theories Recent Work: Recent publications explore topics like spectral triples for subshifts, K-theoretic duality for hyperbolic systems, and minimal homeomorphisms in dynamical systems. His work bridges abstract algebraic structures with geometric and topological insights. Awards: - Fellow, Royal Society of Canada - Fellow, American Mathematical Society

Andreas KarageorghisView profile

Professor

• Numerical Analysis
• Scientific Calculations
• Boundary Element Methods
• +3 more

Andreas Karageorghis is a Professor in the Department of Mathematics and Statistics at the University of Cyprus, affiliated with the School of Natural and Applied Sciences. His research focuses on numerical analysis, scientific computations, and boundary element methods, particularly employing the Method of Fundamental Solutions (MFS). He holds a DPhil from Oxford University, preceded by a BA and MA. His work emphasizes solving complex elliptic boundary value problems, inverse scattering, and geometric reconstruction. Notable contributions include advancements in MFS algorithms for biharmonic equations, axisymmetric systems, and polyharmonic problems. He has also explored hybrid meshless methods and RBF neural networks for nonlinear problems. Key applications span fluid mechanics (e.g., Brinkman equations), elasticity, and acoustic scattering. His research addresses challenges like void detection, shape identification, and steady-state heat conduction. Karageorghis has published extensively in top journals like SIAM and IMA Numerical Analysis, with over 40 years of continuous academic contribution. His methodological innovations include matrix decomposition algorithms, efficient Kansa-type MFS formulations, and non-iterative approaches for inverse problems. Ongoing work includes optimal parameter selection for RBF methods and extending MFS to higher-order PDE systems.

Edoardo S. BiagioniView profile

Associate Professor

• Networking
• Wireless Networking
• Network Security
• +9 more

Edoardo S. Biagioni is an Associate Professor at the University of Hawaii in the Department of Information and Computer Sciences , where he has been since 1997. His primary research focuses on decentralized networking , wireless security , and systems programming , with long-term projects including the Allnet project (since 2011) and earlier PODS micro-sensor networks (2000-2003). Current research since 2024 includes formal verification of file systems and correctness properties in systems programming Technical interests span protocol decomposition , language-based OS design , and congestion control Teaching emphasizes Java fluency , data structures , and algorithm complexity in courses like ICS 211 Prior roles included directing the Advanced Network Computing Laboratory (1997-2005) and contributions to the Fedora Core project. Students under his supervision have worked on projects ranging from network measurement to ATM transport protocols . His work bridges theoretical concerns like IP fragmentation theory with practical implementations in SML database systems and IPv6 transitions .

Konstantin WackerView profile

Associate Professor

• Macroeconomics
• Economic Development
• International Economics
• +3 more

Konstantin Wacker is an **Associate Professor** at the **University of Groningen**, affiliated with the **Faculty of Economics and Business** and the **Department of Global Economics & Management**. He holds a PhD in Economics and Applied Statistics from the University of Göttingen (2013) and has studied at institutions in Vienna, Alicante, and Beijing. Previously, he worked at the World Bank (2013–2015) and as an Assistant Professor at the University of Mainz (2015–2018). His research focuses on **macroeconomic development**, **economic growth**, **foreign direct investment (FDI)**, and **globalization**, employing advanced econometric methods, particularly panel data analysis. Research Interests : Macroeconomic development and cross-country income disparities Economic growth drivers, including capital accumulation and institutional factors Globalization impacts, including trade, FDI, and export quality Panel data econometric methods and model specification Poverty and inequality dynamics Recent Articles & Themes : Recent work includes analyses on **export quality in global value chains**, **pandemic impacts on environmental performance**, and **growth accelerations in developing economies**. He emphasizes methodological rigor, leveraging panel data to address questions of FDI transmission, trade dynamics, and policy effectiveness. Awards & Fellowships : Klaus Liebscher Economic Research Scholarship (Austrian Central Bank, 2020) Kurt Rothschild Price (2020) Grants & Projects : Manages an NWO-funded project on **export quality in global value chains** Contributes to the Horizon Europe **Twin Seeds** initiative Collaborations & Roles : Visiting researcher at Statistics Netherlands (CBS) Research fellow at the Vienna Institute for International Economic Studies (wiiw) Global Labor Organization fellow Media & Outreach : Contributions to public discourse include analyses on **robotization impacts**, **corporate tax avoidance**, and **global pandemic preparedness**, featured in popular and academic outlets.