Prof. Dr. Hendrik Scholz is a Professor at the Friedrich-Alexander University Erlangen-Nuremberg (FAU) , holding the Chair of Business Administration with a focus on Finance and Banking. His research spans portfolio management, performance analysis of investment funds, ESG (Environmental, Social, Governance) metrics, and capital market-oriented financial strategies. Education: University of Göttingen, Colorado College Academic Career: Habilitation at KU Eichstätt-Ingolstadt (2007), Senior Academic Councilor (2008–2009) Key research trends include ESG integration, sustainable indices, currency-hedged funds, and corporate credit spread analysis. His work combines empirical methods with machine learning, addressing market anomalies and risk management. Recent publications focus on diversity in corporate boards, fund flow dynamics, and ESG rating impacts. Collaborations with researchers like Greger, Hübel, and Webersinke highlight interdisciplinary approaches.
Samuel A. Bryan serves as a Lab Fellow and Chemist at Pacific Northwest National Laboratory (PNNL), where he pioneers spectroelectrochemical sensor development for measuring chemical species in highly complex nuclear systems. His innovations have resolved critical Department of Energy safety issues, particularly regarding ferrocyanide concentration determination in nuclear waste and hydrogen flammability in Hanford waste tanks. Dr. Bryan earned his B.S. in Chemistry from Boise State University (1979), followed by M.S. and Ph.D. degrees in Inorganic Chemistry from Washington State University (1983, 1985). His educational background established the foundation for his expertise in complex chemical systems analysis. His research focuses on real-time spectroscopic monitoring methodologies for nuclear applications. Key contributions include developing the first-ever luminescence detection from technetium complexes, creating sensors for nuclear waste analysis, and establishing predictive models for hydrogen gas generation that continue to inform Hanford Waste Treatment Plant safety designs 25 years later. His work bridges fundamental chemistry with practical nuclear engineering solutions. Analysis of his recent publications reveals strong emphasis on multi-modal spectroscopy (Raman, UV-Visible, NIR) combined with chemometric analysis for nuclear applications. His research spans from fundamental sensor development to practical implementation in nuclear fuel recycling, waste treatment, and safeguards verification. Fellow of the American Chemical Society Chair of Richland Section of the ACS (1998 and 2004) Fitzner-Eberhardt Award for Outstanding Contributions to Science and Engineering Education PNNL Laboratory Director's award (2005) ACS ChemLuminary Award for Outstanding Performance by Richland Section (2004) Dr. Bryan's technical leadership extends to mentoring junior scientists and contributing to national initiatives in nuclear safeguards. His current research focuses on microfluidic sensor systems, multi-modal spectroscopy approaches, and advanced data analysis techniques for nuclear applications, continuing to address critical challenges in nuclear waste management and national security.
Jake Kraft is an Assistant Professor within the clinical program of the Department of Psychology at the University of South Dakota. He holds a PhD in Clinical Psychology from Oklahoma State University (2022) and is a Licensed Psychologist with the South Dakota Board of Examiners of Psychologists. Ph D, Clinical Psychology, Oklahoma State University, 2022 MS, Clinical Psychology, Oklahoma State University, 2019 BA, Psychology, Augsburg University, 2016 Dr. Kraft's research program focuses on documenting cognitive and physiological processes within anxiety and related disorders to better inform treatment. At the PAWS Lab (Psychophysiology of Anxiety, Worry, and Stress Lab), he employs techniques including event-related potentials, time-frequency analyses, skin conductance, electrocardiography, and heart-rate variability to capture cognitive impairments such as executive function and attention deficits. His long-term goal involves using noninvasive brain stimulation techniques like tACS to target disease-specific and transdiagnostic physiological and cognitive processes. His publication record shows a strong emphasis on anxiety disorders, particularly weather anxiety and social anxiety, with recent work examining attentional biases, emotional processing, and the influence of self-focused attention. His research integrates clinical psychology with affective neuroscience, creating a bridge between basic science and clinical applications. Dr. Kraft teaches undergraduate courses including General Psychology, Psychopathology, Research Methods, and Biological Psychology, and graduate courses such as Cognitive and Personality Assessment and Psychopathology. He also serves as a clinical supervisor for the Psychological Service Center. As director of the PAWS Lab, Dr. Kraft leads research examining the cognitive and physiological underpinnings of anxiety and stress disorders, with particular focus on how these mechanisms maintain symptoms and how they might be targeted for treatment improvement.
Dr. Chris Montgomery is a Senior Lecturer in Dialectology at the School of English, University of Sheffield, where he has held roles since 2012. Prior to this, he was a Lecturer at Sheffield Hallam University and completed an ESRC Postdoctoral Fellowship at the University of Edinburgh. His research focuses on non-linguists' perceptions of language variation, particularly in northern England and southern Scotland, integrating GIS technologies and sociolinguistic methods. He explores how real-time reactions to regional speech are influenced by salience and stereotypes, emphasizing methodologies like starburst charts and geospatial analysis. His research interests span perceptual dialectology, folk linguistics, computational sociolinguistics, and the role of borders in linguistic perception. He contributes to interdisciplinary collaborations, applying geographical science techniques to linguistic studies. Dr. Montgomery teaches modules on language variation, regional identity, and language attitudes at both undergraduate and postgraduate levels. His work has been published in journals such as Journal of Sociolinguistics and Frontiers in Artificial Intelligence , and he co-edited volumes like Language and a Sense of Place (2017) and Cityscapes and Perceptual Dialectology (2016). Dr. Montgomery’s methodologies include innovative approaches to mapping perceptual dialect landscapes, with a focus on urban and border regions. His recent projects examine insular dialects (e.g., Isles of Scilly) and utilize Twitter data for lexical variation studies. He actively supervises students in perceptual dialectology, computational methods, and sociolinguistic theory.
Vincent J. Ervin is a Professor of Mathematical Sciences at Clemson University's College of Science, located in Martin Hall. His academic journey includes a PhD from Georgia Institute of Technology in 1984. He specializes in numerical analysis, computational mathematics, and partial differential equations with focuses on fluid dynamics, fractional calculus, and viscoelastic systems. University: Clemson University College/School: College of Science Department: Mathematical and Statistical Sciences His research emphasizes fractional diffusion equations , viscoelastic fluid flow , and coupled Stokes-Darcy systems . Notable contributions include: Numerical methods for axisymmetric elasticity equations Stability analysis of fractional advection-diffusion systems Modeling fluid-structure interactions in biomedical applications (e.g., ocular pressure) Publications span topics from spectral approximations for fractional PDEs to error estimation in viscoelastic flows. His work bridges theoretical analysis with computational implementations, often employing finite element methods and stabilized formulations.
Jae Patterson, PhD, is an Associate Professor in the Department of Kinesiology at Brock University. His primary research focuses on motor skill acquisition across the lifespan, emphasizing practice variables such as augmented feedback, learner-controlled practice, and error detection. His work has implications for sport, rehabilitation, and vocational training. He is affiliated with the Motor Skills Acquisition Laboratory and the Centre for Neuroscience at Brock University. Research interests include augmented feedback mechanisms, repetition scheduling, observational learning, and cognitive effort during skill acquisition. His studies explore how practice conditions influence learning outcomes in diverse populations, including athletes and individuals with movement disorders. Publications span peer-reviewed journals and book chapters, addressing topics like self-controlled learning protocols, focus of attention in sports, and the impact of concussion on athletic performance. His work emphasizes practical applications in rehabilitation and sports training. Professional affiliations include the Canadian Society for Psychomotor Learning and Sport Psychology, and the North American Society for the Psychology of Sport and Physical Activity. The Motor Skills Acquisition Lab actively seeks graduate and undergraduate students for research projects.
Luis Ibarra is an Associate Professor in the Department of Civil & Environmental Engineering at the University of Utah, where he has been employed since 2010. He was promoted to Associate Professor in July 2016 after serving as an Assistant Professor from 2010 to 2016. He earned his PhD in Civil and Environmental Engineering from Stanford University in 2004. Research Interests Dr. Ibarra's research spans multiple domains of civil engineering with particular emphasis on seismic performance of structures, nuclear safety, and material behavior. His work integrates computational mechanics, experimental testing, and probabilistic risk assessment to address challenges in structural resilience under extreme loading conditions. Primary research themes include: Seismic modeling of nuclear containment structures and fuel rod behavior Development of advanced hysteretic models for structural components Earthquake engineering applications for bridges and buildings Probabilistic risk assessment of structural systems Publications Overview Recent publications (2018-2025) demonstrate Dr. Ibarra's focus on computational mechanics applied to nuclear and structural safety, featuring advanced finite element modeling, probabilistic methods, and experimental validation. Recurring themes include seismic vulnerability of nuclear facilities, deterioration modeling of structural components, and innovative retrofitting techniques for earthquake resilience. The research consistently integrates material science fundamentals with structural engineering applications. Awards and Recognition Ben Jacobsen Kingfisher Bend Ranch Award for exceptional teaching effectiveness (2015) Teacher of the Year Award, CvEEN Department (2014) Teacher of the Year Award in the CvEEN Department (2013) Milek Fellowship Award, American Institute of Steel Construction (2013) Academic Activities Dr. Ibarra maintains an active research program supported by multiple grants including seismic modeling of nuclear structures, machine learning applications for collapse prediction, and performance of retrofitted bridges. He regularly advises graduate students in thesis research and teaches courses in structural dynamics, steel design, and structural analysis. His professional service includes editorial board membership for the Tall and Special Buildings Journal and community outreach through earthquake education programs for high school students.
Harry Joe is a Professor in the Department of Statistics at the University of British Columbia (Vancouver Campus). His primary research focuses on dependence modeling, copula theory, multivariate analysis, and applications in biostatistics, finance, and psychometrics. He has advised students including Xiaoting Li, Xinyao Fan, and Pavel Krupskiy. Research Interests: - Advanced copula constructions (e.g., vine copulas) - Extreme value theory and tail dependence - Applications in financial risk, biomedical research, and educational measurement - Multivariate time series analysis and non-Gaussian models Publications highlight contributions to copula-based classification methods (2024), factor copula models (2015), and dynamic dependence modeling (2020). His work bridges theoretical developments with practical applications across disciplines. Teaching and advising emphasize methodological innovation. Current research explores high-dimensional dependence structures and computational methods for complex data. No lab/team affiliations explicitly noted in provided materials.
Kevin Flores is an Associate Professor in the Department of Mathematics at North Carolina State University (NC State), and Director of the Biomathematics Graduate Program. He leads the Flores Lab, focusing on developing mathematical and statistical methods for parameter estimation, uncertainty quantification, and forecasting in Precision Medicine, Environmental Toxicology, and Synthetic Biology. His work bridges computational approaches with biological systems analysis. Dr. Flores earned his PhD in 2009 from Arizona State University. His research groups include the Mathematical Biology cluster within the Department of Mathematics. His affiliations include Cox Hall 406D and the College of Sciences at NC State. Research interests emphasize interdisciplinary applications: (1) Mathematical Biology involving tumor heterogeneity, viral dynamics, and angiogenesis modeling; (2) Biostatistics focusing on parameter estimation in complex systems; and (3) Computational Tools for biomedical image analysis and machine learning in healthcare. His lab pioneered methods like biologically-informed neural networks and topological data analysis for biological systems. Recent work highlights include: (1) tumor spheroid modeling predicting clinical variability; (2) BK virus infection dynamics in transplant patients; (3) EEG-based brain-computer interface improvements using GANs; and (4) few-shot learning for plant phenotyping. His methodologies address challenges in sparse data scenarios and integrate mechanistic understanding with data-driven approaches. Awards and recognition : None explicitly listed in provided texts. Advising and grants: No specific advisees or grant details provided in texts. His lab's software tools support image segmentation and population modeling. Labs/teams: Directs the Flores Lab for Mathematical Biology at NC State, specializing in hybrid computational-experimental approaches. Collaborates across departments in biomathematics and engineering.
Joseph Webber is a Research Fellow at the Warwick Mathematics Institute, University of Warwick, where he works in Professor Tom Montenegro-Johnson's group on the Leverhulme-funded project "Shape Transforming Active Matter." Previously, he completed his PhD at the Department of Applied Mathematics and Theoretical Physics (DAMTP) at the University of Cambridge under the supervision of Professor Grae Worster. Dr. Webber is an applied mathematician specializing in the intersection of fluid mechanics and soft matter physics, with a particular focus on hydrogels. His research encompasses: Poroelasticity and the behavior of porous, deformable media Responsive hydrogels that change volume in response to environmental stimuli Theory development for hydrogel modeling, particularly the "linear-elastic-nonlinear-swelling" (LENS) approach Freezing dynamics of hydrogels and cryosuction phenomena Swelling and drying behavior of super-absorbent polymers Wrinkling instabilities in swelling hydrogels His recent publications demonstrate a strong focus on developing mathematical frameworks to understand hydrogel behavior across various conditions. The research shows progression from fundamental modeling approaches to applications in soft robotics, microfluidics, and bio-inspired devices. Key themes include the coupling between fluid flow, elastic deformation, and chemical reactions in responsive materials, with particular attention to time-dependent phenomena and pattern formation. Scientific achievements include: IMA Lighthill-Thwaites Prize finalist (2025) First prize for a 10-minute talk at DAMTP Friday Fluids (2022) Dr. Webber has supervised courses in applied mathematics as part of the Cambridge Mathematical Tripos and lectured portions of the Part IA Introduction to Mechanics course. His teaching resources include detailed notes on fluid dynamics, variational principles, and stress tensor analysis. He has also created a YouTube playlist introducing fluid mechanics and continuum mechanics basics. He is actively involved in the UK Hydrogels Network and maintains a mailing list for researchers working on hydrogels in the UK. His current research in the Montenegro-Johnson group focuses on developing theoretical models for responsive hydrogels and their applications in active matter systems.
Paolo Pescetto is a Fixed-term tenure-track Assistant Professor in the Department of Energy (DENERG) at Politecnico di Torino, where he is also a member of the Interdepartmental Center PEIC (Power Electronics Innovation Center). He serves on multiple academic boards including the College of Electrical and Energy Engineering, College of Computer, Film and Mechatronics Engineering, and College of Mechanical, Aerospace, and Automotive Engineering. His research focuses on power electronics, electrical machines, and motor drives with particular emphasis on electric vehicle applications. His work spans motor control strategies, thermal management of high-power density motors, sensorless control techniques, and integrated power systems for e-mobility. He has developed advanced methodologies for flux mapping, torque ripple compensation, and fault protection in permanent magnet and synchronous reluctance machines. Analysis of his recent publications reveals a strong trend toward solving practical challenges in electric vehicle powertrains, with significant contributions in multi-phase motor drives, thermal management, and fault-tolerant control systems. His work bridges theoretical advances with practical automotive applications, particularly in third-generation electric vehicle technologies. Dr. Pescetto holds multiple patents in motor control technologies, including methods for MTPA tracking without HF injection, spatial harmonic flux-map identification, and isolated on-board battery chargers for electric vehicles. His intellectual property demonstrates practical innovation in the field of motor drives and power electronics. He actively supervises PhD students Andrei Bojoi and Chen Chen in the Electrical, Electronics, and Communications Engineering program, focusing on electric motor drives and sustainable traction electrification. His research projects include commercial contracts on sensorless control of synchronous reluctance machines, firmware implementation for motor control, and advanced sensorless control methodologies for brushless motors. As a member of the PEEMD Research Group within DENERG, Dr. Pescetto contributes to cutting-edge research in power electronics and motor drives, with a strong industry collaboration focus that translates academic research into practical automotive solutions.
Virginie Ehrlacher is a Professor at CERMICS, École des Ponts ParisTech (ENPC), France. She specializes in applied mathematics with a focus on high-dimensional problems, numerical analysis, and computational modeling. Her work bridges quantum chemistry, materials science, and machine learning through innovative mathematical frameworks. Education includes: PhD in Mathematics (2012) from ENPC: Mathematical models in quantum chemistry and uncertainty quantification Habilitation (2020) from Université Paris-Dauphine: Mathematical and numerical analysis of high-dimensional and multiscale problems in materials science Research spans multiscale modeling, tensor decompositions for high-dimensional systems, cross-diffusion equations, and scientific machine learning. Her work frequently addresses challenges in quantum mechanics, materials science, and computational physics using advanced numerical techniques. Publications emphasize: Algorithms for high-dimensional PDEs and eigenvalue problems Model reduction techniques (tensor networks, reduced basis methods) Cross-diffusion systems with biological/physical applications Neural networks for scientific computing Awards and distinctions: Irène Joliot-Curie Prize (2023) Chevalier de l’Ordre National du Mérite (2025) Leadership includes: ERC Starting Grant HighLEAP (2023–2028) ERC Synergy project EMC2 (2020–2026) ANR JCJC project COMODO (2019–2023) She co-leads the EMS Topical Activity Group on Scientific Machine Learning. Affiliated with the CERMICS laboratory, she collaborates on interdisciplinary teams tackling multiscale and data-driven modeling challenges.
Miroslav Grmela is a Researcher at the Department of Chemical Engineering in Polytechnique Montréal , and a member of the Research Center for High-Performance Polymer and Composite Systems (CREPEC) . His work spans thermodynamics, transfer processes, and multiscale modeling of complex fluids. Grmela’s research focuses on non-equilibrium thermodynamics , contact geometry in kinetic dynamics , and mesoscopic theories of polymer suspensions, superfluids, and nanocomposites. He has extensively explored the role of energy and entropy in multiscale systems, with recent publications addressing geometric formulations of thermodynamics and neural network applications to non-symplectic mechanics. Analysis of his 15 most recent articles reveals trends in multiscale thermodynamics , non-Fourier heat conduction , GENERIC formalism , and quantum hydrodynamics . His work often bridges geometric mechanics with thermodynamic consistency. Grmela has supervised 10 graduate students (7 PhD, 3 Master’s) in projects involving nanocomposite thermal conductivity , polymer rheology , and powder suspension simulations . He has no listed scientific awards. His research intersects with fluid dynamics , polymer science , and statistical mechanics , emphasizing mathematical structures like Poisson brackets and Hamiltonian formulations . The CREPEC laboratory provides institutional support for his studies on polymers and composites.
Natalia Kopteva is a Full Professor (Chair) in Applied Mathematics at the Department of Mathematics and Statistics, University of Limerick, Ireland. She holds a Ph.D. and M.Sc. in Computational and Applied Mathematics from Moscow State University. Her career includes academic positions at Moscow State University, University College Cork, and University of Strathclyde. Education: M.Sc. in Applied Mathematics, Lomonosov Moscow State University Ph.D. in Computational Mathematics, Lomonosov Moscow State University Her research focuses on numerical analysis of partial differential equations , particularly time-fractional and singularly perturbed subdiffusion equations , with emphasis on a posteriori error estimation , adaptive discretization methods , and maximum norm analysis . She has contributed to discontinuous Galerkin methods and Green's function estimates for convection-diffusion problems. Recent publications highlight trends in graded meshes for fractional calculus, pointwise error bounds , and time stepping adaptation for non-smooth data. Her work bridges applied mathematics and computational science with applications in reaction-diffusion systems and convection-diffusion equations . She serves as editor for SIAM Journal on Numerical Analysis and Advances in Computational Mathematics , and has held editorial roles for 8 international refereed journals. Additional affiliations include membership in the Centre for Research Training in Foundations of Data Science and the Mathematics Applications Consortium for Science and Industry (MACSI) .
Ilana Witten is Professor at the Princeton Neuroscience Institute, Princeton University. Her research investigates the neural mechanisms underlying reward learning, decision-making, and behavioral control using integrative approaches including optogenetics, rodent behavior, electrophysiology, and computational modeling. Research focuses on: Neural circuit mechanisms of reward seeking behaviors Striatal contributions to learning and decision-making Neurobiology of individual differences in behavior Integration of sensory information with reward outcomes Neural plasticity during learning processes Publications center on dopaminergic systems, striatal function, and neural circuit dynamics. Recent trends include work on prediction errors, neural representations of prior information, and circuit mechanisms of behavioral control. Lab: Leads the Witten Lab at Princeton Neuroscience Institute investigating neural circuits of reward and decision.
