Dr. Birgit Schwartz-Reinken is a Lecturer at the University of Hamburg's Business School, affiliated with the Institute of Business Information Systems. She holds a Ph.D. in parallel computing and business planning from 1994. Her research focuses on Operations Research, Parallel Algorithms, Supply Chain Management, and E-Learning. She has authored or co-authored 8 publications since 1990, including works on Eclipse-based GUI design and adaptive virtual learning environments. Her work bridges computational optimization and business informatics. Education: Ph.D. in Parallel Processing and Business Planning (1994) Research Interests: Combines parallel algorithm design with business optimization challenges, particularly in supply chain and production planning. Explores E-Learning methodologies for adaptive instructional systems. Publications: Recent work emphasizes software tools like Eclipse for enterprise development, while earlier research addressed parallel computing applications in combinatorial optimization and manufacturing systems. Grants/Advising: No specific grants or advisee records noted in provided texts.
Prof. Jörg Stelling is a Full Professor in Computational Systems Biology at ETH Zürich's Department of Biosystems Science and Engineering (BSSE), based in Basel. He leads the CSB Group, focusing on interdisciplinary research spanning computational methods, systems biology, and synthetic biology. His work integrates mathematical modeling with experimental studies, particularly using budding yeast as a model organism. Education: Bachelor/Master in Biotechnology from TU Braunschweig (1989–1996) PhD in Systems Biology from University of Stuttgart and Max Planck Institute for Dynamics of Complex Technical Systems (2004) Research Interests: Analysis/synthesis of biological networks, multiscale modeling, enzyme kinetics, metabolic flux analysis, and synthetic biology applications. His group develops tools like ENKIE for kinetic parameter prediction and explores cellular network dynamics using systems theory and computer science methods. Lab/Teams: The Computational Systems Biology Group includes biologists, engineers, and mathematicians. Recent projects include modeling diabetes (Dana's PhD), cell-to-cell variability (Paul's work), and viral uncoating mechanisms. Grants/Awards: Active in securing interdisciplinary funding but no specific awards listed.
Dr. Mohamed El Alili is a Visiting Fellow at the Faculty of Science, Department of Health Sciences, Vrije Universiteit Amsterdam. His research focuses on improving the statistical quality of trial-based economic evaluations, addressing challenges such as skewed data, missing data, and clustered data to ensure valid and reliable healthcare resource allocation decisions. He contributes to the development of national guidelines for economic evaluations and has published extensively on methodologies in healthcare economics. Education: Master's in Healthcare Policy, Innovation, and Management (2014-2015) Bachelor's in Health Sciences (2011-2014) Research Interests: El Alili’s work emphasizes the application of advanced statistical methods to healthcare economic evaluations. His key areas include cost-effectiveness analysis optimization, handling missing data in longitudinal studies, and validating utility metrics (e.g., EQ-5D). He actively collaborates on guideline updates and policy-relevant studies to enhance decision-making in healthcare resource allocation. Teaching: He teaches academic research methods and economic evaluations to both bachelor and master students, bridging theoretical concepts with practical applications in healthcare economics. Awards: Best poster award ESPACOMP, 3rd place (2015) Advising & Grants: El Alili has supervised one PhD thesis and contributed to studies funded by grants, focusing on topics like mental health interventions and diabetes drug cost-effectiveness. His research has been widely cited and shared across academic platforms.
Famke Mölenberg serves as an Assistant Professor in the Department of Public Health at Erasmus MC, Rotterdam. Her research focuses on population-level health interventions with emphasis on Dutch community settings. Her primary research interests span childhood obesity prevention, physical activity promotion, and environmental determinants of health. Key areas include: Systematic reviews and meta-analyses of prevention programs Community-based overweight interventions for children Traffic policy impacts on public health outcomes Food environment effects on pediatric eating behaviors Methodologically, she specializes in natural experiments, propensity score matching, and cohort analyses using the Generation R Study data. Recent publications demonstrate strong thematic alignment in evaluating Dutch public health initiatives, particularly community-scale obesity prevention and traffic safety interventions. Her work consistently employs mixed-methods approaches combining quantitative metrics with policy analysis. Scientific awards: No formal awards listed in source materials Regarding academic mentorship and funding, no student advisement records or specific grant details appear in the provided text. Her collaborative network prominently features the Generation R Study team and traffic policy researchers across Dutch institutions. Current projects include longitudinal assessments of school-based interventions and natural experiments in urban traffic management. Her laboratory work centers on epidemiological analysis within the Generation R Study framework, utilizing advanced statistical modeling for public health impact assessment. Key collaborations include Rotterdam-based researchers in transport policy and nutrition science.
Matthew Schneider is an Associate Professor in the Department of Decision Sciences and Management Information Systems at Drexel University's LeBow College of Business. He holds a PhD in Statistics from Cornell University and has previously served as an Assistant Professor at Northwestern University and a Visiting Scholar at Cornell. He teaches and conducts research at the intersection of data privacy, forecasting, and business analytics. PhD in Statistics, Cornell University MS in Statistics, Cornell University MS in Public Policy and Management, Carnegie Mellon University BS in Quantitative Economics, United States Naval Academy Dr. Schneider's research centers on data privacy and time series forecasting , with a focus on developing statistical methodologies that protect consumer privacy while preserving data utility for business decisions. His work enables organizations to balance regulatory compliance with data-driven profitability. He has applied his expertise in data anonymization and analytics frameworks for Fortune 500 companies in FinTech, pharma, insurance, and retail. His research has been published in leading journals including Harvard Business Review , Marketing Science , and Journal of the Royal Statistical Society . His recent publications demonstrate a consistent trend in privacy-preserving data analysis , particularly through synthetic data, differential privacy, and k-anonymity. He also explores forecasting using consumer reviews and robust methods for detecting demand shifts. These works span disciplines such as statistics, marketing science, information systems, and operations research. Dr. Schneider is actively engaged in executive education, teaching Data Privacy Strategy through eCornell. He has collaborated with prominent scholars such as Sachin Gupta and John Abowd. His industry experience includes roles at the RAND Corporation and Fort Rock Asset Management LLC. Scientific lead for pre-IPO validation of data science models in FinTech Director of Research at Fort Rock Asset Management LLC Used by major corporations to improve analytics and anonymization frameworks Teaches corporate executives through eCornell’s certificate program He has no listed scientific awards in the provided text. There is no mention of students he has advised. His work is supported by practical applications in industry rather than explicit grant funding in the source material.
Prof. Hartwig Anzt is a Professor at TU Munich, leading the Chair of Computational Mathematics within the TUM School of Computation, Information, and Technology. He also holds a professorship at the University of Tennessee and directs the Innovative Computing Lab (ICL). His research focuses on high-performance computing, particularly in sparse linear algebra, iterative methods, Krylov solvers, and preconditioning. He emphasizes sustainable software development and leads the Ginkgo open-source library for scientific computing. Academically, Anzt earned his PhD in 2012 from the Karlsruhe Institute of Technology (KIT) and led a Helmholtz junior research group there. He has extensive collaborations with institutions like Sandia National Laboratories, Argonne National Laboratory, and the University of Tennessee. His software projects include Ginkgo and MAGMA-sparse, both part of the xSDK ecosystem. Recent talks highlight his work on exascale computing, GPU optimization, and software sustainability. He advocates for platform-portable numerical libraries and has contributed to the Exascale Computing Project (ECP). His research addresses challenges in energy efficiency, fault tolerance, and algorithm design for multi/manycore architectures.
Gregory Chini is a Professor in the Department of Mechanical Engineering at the University of New Hampshire (UNH), where he has been a faculty member since 1999. He also serves as the Director of the Integrated Applied Mathematics (IAM) Ph.D. program and holds affiliations with the College of Engineering and Physical Sciences. He has been a visiting researcher at the California Institute of Technology and the University of Nottingham, and is a regular participant in the Woods Hole Summer Program in Geophysical Fluid Dynamics. Ph.D., Aerospace and Aeronautical Engineering, Cornell University M.S., Aerospace and Aeronautical Engineering, Cornell University B.S., Aerospace and Aeronautical Engineering, University of Virginia Prof. Chini's research lies at the intersection of fluid dynamics and applied mathematics, with a focus on modeling geophysical, environmental, biological, and industrial flows. He investigates the stability and dynamics of coherent structures such as vortices, waves, and boundary layers using asymptotic, variational, and spectral methods. His work emphasizes reduced-order modeling to understand complex systems like turbulent convection and porous media flows. The recent publications highlight a strong trend in multiscale modeling, turbulent transport, and mathematical analysis of fluid systems. His articles frequently address Rayleigh-Bénard convection, stratified turbulence, boundary layer dynamics, and optimal transport, often employing quasilinear and asymptotic frameworks to extract physical insights. The research spans from theoretical analysis to computational modeling, with applications in oceanography, geophysics, and soft matter. He has been awarded multiple research grants from the National Science Foundation (NSF) and the U.S. Department of Defense (Navy), supporting projects on high Reynolds number turbulence, wall-bounded flows, and multiscale oceanic modeling. These grants reflect sustained funding and leadership in fundamental fluid mechanics research. National Science Foundation (NSF): Development of Asymptotically-Reduced Multi-Scale Models (2014–2019) National Science Foundation (NSF): Multiscale Modeling of Oceanic Mixed Layer (2009–2015) U.S. DOD, Navy: Predicting Non-Equilibrium Wall-Flow Phenomena (2017–2023) Mentis Sciences Inc: Cooling System for Laser Enclosure (2018) Prof. Chini teaches core courses such as Fluid Dynamics (ME 608), Thermodynamics (ME 503), Viscous Flow (ME 909), and Asymptotic Methods (IAM 940), and supervises doctoral research in applied mathematics and mechanical engineering. He advises Ph.D. students and collaborates widely, particularly with researchers like Christopher White. His lab and research group focus on theoretical and computational fluid dynamics, with an emphasis on model reduction and predictive simulation of complex flows.
Carina Schwarz is a researcher at the Institute of Mechanics, Faculty of Engineering, University of Duisburg-Essen, where she has been a research assistant since 2012 and completed her doctorate in 2018. Her work focuses on the development and application of least-squares finite element methods (LSFEM) to problems in fluid and solid mechanics, including sea ice modeling, fluid-structure interaction, and incompressible fluid dynamics. She teaches multiple courses in engineering mechanics and finite element methods at both bachelor’s and master’s levels. PhD in Engineering, University of Duisburg-Essen, 2018 B.Sc. in Civil Engineering, University of Duisburg-Essen, 2010 M.Sc. in Computational Mechanics, University of Duisburg-Essen, 2012 Research stay at École des Mines, Paris, 2012 Her research interests center on computational mechanics , particularly least-squares finite element methods , sea ice modeling , and incompressible fluid dynamics . She investigates higher-order time integration schemes and mixed finite element formulations for linear elastodynamics and fluid-structure interaction problems. Her work bridges theoretical mechanics with practical numerical simulation tools. The trend in her recent publications shows a growing emphasis on environmental applications, especially sea ice dynamics in polar regions, using advanced computational fluid dynamics and numerical methods. Her earlier work focused more on fundamental formulations of LSFEM for Navier-Stokes equations and elastodynamics, evolving toward coupled environmental systems. She has supervised multiple student theses in computational mechanics, mentoring students in finite element implementation and numerical modeling. Although no specific grants or awards are mentioned, her consistent publication output in reputable journals and conferences reflects sustained research activity. Carina Schwarz leads and contributes to collaborative research projects involving interdisciplinary modeling of complex mechanical and environmental systems. Her work is integrated within the Institute of Mechanics, where she participates in academic teaching and research seminars such as the Seminar for Numerical Mathematics and Mechanics (SNMM).
Matteo Aldo Luigi PORRO is an Associate Professor in the Department of Molecular Sciences and Nanosystems at Ca' Foscari University of Venice. He is actively engaged in teaching and research, with a focus on electronics and semiconductor-based radiation detection systems. His office is located in room 612 of the ALFA building on the scientific campus via Torino. Research Interests: PORRO specializes in the design and testing of microelectronic circuits for radiation detectors, particularly in mixed-signal CMOS design and semiconductor sensor modeling. His work supports advanced instrumentation for synchrotron and X-ray free-electron laser (XFEL) applications, including DEPFET sensors and high-speed data acquisition systems. The recent publications highlight a strong trend in developing cutting-edge detector technologies for high-energy physics and photon science, particularly in the context of the DSSC camera and European XFEL. These works span electronics, detector physics, and real-time data processing, reflecting a multidisciplinary approach to advanced instrumentation. Scientific Service and Recognition: Chair, Linac Coherent Light Source (LCLS) Detector Advisory Committee, Stanford, USA Topic Convener, IEEE NSS MIC Conference 2022 (Milan) and 2021 (Yokohama) – Session: Synchrotron Radiation, Accelerator, FEL and Beamline Instrumentation Reviewer for U.S. Department of Energy (DOE) BES Accelerator and Detector Research Program (2022) Reviewer for NSERC Discovery Grants, Canada (2014) Advising and Grants: While no formal students are listed, PORRO leads significant research initiatives, including the development of multi-channel CMOS ASICs for semiconductor detectors and ultra-fast, low-noise X-ray cameras for XFELs. He participates in international collaborations and has contributed to major instrumentation efforts at facilities like the European XFEL and SLAC. Labs and Teams: He is involved in the research lines of 'Physics of Materials' and 'Informatics' within his department and contributes to detector development teams for large-scale photon science facilities. His role as Laboratory Safety Officer (Preposto di Laboratorio) indicates active management of laboratory operations.
Cristóbal López Sánchez is a Full Professor in the Department of Physics at the University of the Balearic Islands (UIB), specializing in Condensed Matter Physics. He holds a PhD in Physics from UIB and completed postdoctoral research at the University of Rome 'La Sapienza'. His academic career includes serving as a Ramón y Cajal fellow and associate professor at UIB from 2001-2019 before becoming a full professor in December 2019. He maintains active research collaborations with institutions worldwide including the University of Cambridge, ICTP Trieste, and LOCEAN Paris. His educational background includes a Physics degree from the University of Granada and PhD from UIB. International research stays have been conducted at: University of Cambridge (UK) University of Rome 'La Sapienza' (Italy) University of Oldenburg (Germany) Eotvos University of Budapest (Hungary) LEGOS Toulouse (France) LOCEAN Paris (France) ICTP Trieste (Italy) CASUS Gorlitz (Germany) López Sánchez's research focuses on the interdisciplinary applications of Statistical and Non-linear Physics to complex systems. His work centers on understanding emergent behavior in complex systems, particularly transport processes in oceans and their influence on marine ecosystems, as well as collective behavior in biological systems. Key research contributions include characterizing mesoscale mixing and dispersion processes in marine surfaces using Lagrangian Coherent Structures, and studying pattern formation in models of organisms with spatial nonlocal interactions. His broader research portfolio encompasses micro-macro connections in particle systems, biological search dynamics, machine learning applications for spatio-temporal prediction, quantum fluids, sinking particle dynamics, and vegetation pattern formation. His recent publications reveal a strong emphasis on interdisciplinary applications of physics principles to biological and environmental systems. The research demonstrates sophisticated integration of mathematical modeling with real-world phenomena, particularly in ocean transport processes and biological pattern formation. Key thematic areas include Lagrangian transport methodologies, nonlinear dynamics in ecological systems, and computational approaches to complex spatio-temporal phenomena. Scientific recognition includes: Ramón y Cajal fellowship López Sánchez actively mentors graduate students and leads significant research initiatives. His current LAMARCA project investigates Lagrangian transport of marine litter and microplastics in coastal waters, focusing on transport structures and connectivity patterns. He serves as thesis advisor for the PhD in Physics program at UIB and has maintained consistent teaching responsibilities across multiple academic years. His research group Complex systems in life and the environment (CILIA) operates as a Consolidated R+D+I Group at UIB. He directs the Complex systems in life and the environment (CILIA) research group and leads the LAMARCA project on marine litter transport. His laboratory work integrates theoretical physics approaches with environmental and biological applications, particularly through computational modeling of complex systems.
Dr. Marilena Müller is a researcher in the Department of Mathematics at Heidelberg University, specializing in advanced statistical theory and methodology. Her work centers on nonparametric and asymptotic statistics, with applications to survival analysis, point processes, and empirical processes. Research Interests: Survival Analysis / Point Processes Nonparametric Statistics Asymptotic Statistics Linear Mixed Models Empirical Processes Her recent research, published in Bernoulli (2023), focuses on nonparametric estimation of locally stationary Hawkes processes, reflecting her expertise in modeling complex temporal event data using rigorous statistical frameworks. This work contributes to the broader fields of stochastic processes and statistical learning for dependent data. Scientific Awards: No awards listed. Dr. Müller has not advised any named students in the provided information, and there is no mention of grants or funding. She is actively contributing to theoretical statistics and is likely involved in collaborative research within the mathematics and statistics community at Heidelberg University.
Dr. Adrienne Lahti is a Professor and Chair in the Department of Psychiatry - Behavioral Neurobiology at the University of Alabama at Birmingham (UAB) School of Medicine . She holds joint appointments in Psychology (College of Arts and Sciences) and Neurobiology (Academic Joint Departments), and serves as Senior Scientist at multiple UAB research centers including the Comprehensive Neuroscience Center and Civitan International Research Center . With over 150 peer-reviewed publications, her research focuses on neuroimaging biomarkers in psychosis, glutamate dysfunction, and smoking cessation interventions. Degrees: Doctor of Medicine (MD), University of Liege (1978) Research Highlights: Her work examines intrinsic brain network connectivity in first-episode psychosis using resting-state fMRI and MRS, investigates cortical myelin pathology in schizophrenia-spectrum disorders, and develops novel smoking cessation strategies for high-risk populations. Recent studies explore hippocampal connectivity patterns, frontoparietal network dynamics, and biomarker validation for treatment response. Key Contributions: Principal investigator for NIMH grants on neuroimaging in psychosis Co-editor of systematic reviews in World Psychiatry and Schizophrenia Bulletin Mentorship for 12+ graduate students including Hillary Patton and Eric Nelson Teaching Activities: She has taught the Neuroimaging Journal Club (NBL782) and supervised dissertation committees across multiple departments since 2016.
Clément Dupont is an Associate Professor at the University of Montpellier, affiliated with the Institut Montpelliérain Alexander Grothendieck (IMAG), a leading mathematics research institute in France. His work bridges pure mathematics and theoretical physics through deep investigations of algebraic structures. His research focuses on Algebraic Geometry , Number Theory , and Mathematical Physics , particularly exploring motives, periods, regulators , and their connections to quantum field theory amplitudes . He investigates multiple zeta values , mixed Hodge theory , and combinatorial Hopf algebras within the framework of hyperplane arrangements and operadic structures . His recent work demonstrates how motivic methods provide rigorous foundations for physical computations in string theory. Analysis of his publication record reveals a consistent trajectory from foundational work on hyperplane arrangements and motivic coactions toward cutting-edge applications in superstring amplitude calculations and regularized integrals . His collaborations with Francis Brown and others have established critical connections between abstract motivic theory and concrete physical phenomena. Dupont actively contributes to the mathematical community through survey articles and expository work, including an introduction to mixed Tate motives and translations of advanced topics for broader audiences. His academic service includes participation in the Séminaire Bourbaki and organization of specialized conferences. His research is conducted within the IMAG institute, which provides a collaborative environment for interdisciplinary work at the intersection of geometry, topology, and mathematical physics. Current projects focus on logarithmic structures in quantum field theory and operadic formulations of geometric phenomena.
Andrea Lodi serves as the Andrew H. and Ann R. Tisch Professor at the Jacobs Technion-Cornell Institute at Cornell Tech and the Technion, and holds the Canada Excellence Research Chair in “Data Science for Real-time Decision Making” at Polytechnique Montréal. He earned his Ph.D. in system engineering from the University of Bologna in 2000 and was an IBM Goldstine Fellow (2005–2006). Previously, he was a full professor at the University of Bologna (2007–2015). His research focuses on mixed-integer programming, nonlinear optimization, and data science applications in decision-making systems. Notable contributions include advancements in cutting-plane algorithms, machine learning integration in optimization, and fair dynamic resource allocation. Awards include the IBM and Google Faculty Awards, and leadership roles in EU projects and IVADO (Montréal Institute for Data Valorization). Education: Ph.D. in System Engineering, University of Bologna (2000) Consulting: IBM CPLEX R&D team since 2006 Grants: Canadian Federal Government’s Apogée Programme (2024), EU projects His work bridges theoretical optimization and practical applications, including healthcare scheduling, transportation logistics, and algorithmic fairness. Recent projects include developing reinforcement learning frameworks for bike-sharing rebalancing and fairness-aware dynamic decision systems.
Lukas Gnam holds the position of Lecturer and Researcher at the University of Applied Sciences Burgenland's Energie-Umweltmanagement department. His work focuses on energy transition challenges, particularly in renewable energy integration, district heating optimization, and smart energy systems. He has co-authored over 49 publications, emphasizing interdisciplinary approaches to energy system modeling, user-centric energy management, and decarbonization strategies. Key projects include studies on wind power utilization in district heating networks, socially-accepted home energy management systems, and P2P energy trading models. His research combines technical innovation with socio-economic analysis, addressing both infrastructure upgrades and end-user behavior. Collaborations involve institutions like 4ward Energy Research GmbH and TU Wien, focusing on projects such as BEYOND, Empower Citizens, and Hybrid DH DEMO. Gnam's work often employs mixed-integer linear programming and co-simulation tools (e.g., MATLAB/IDA-ICE) to evaluate energy system performance under diverse scenarios. Publications highlight advancements in thermal storage pooling, fossil fuel reduction via PV integration, and long-term heating demand forecasting considering demographic shifts. His projects aim to bridge gaps between technical feasibility and societal acceptance in achieving climate-neutral energy systems.
