Sana Amoozegar is a Research Fellow at the Department of Neurology within the University of Minnesota Medical School . Her work bridges Neuroscience , Biomedical Engineering , and Neurotechnology through deep brain stimulation (DBS) research. Her research focuses on: Therapeutic applications of DBS in Parkinsonian models Neural network modulation in subthalamic pathways Development of closed-loop neuromodulation systems Neuroimaging techniques for seizure localization Recent publications demonstrate expertise in Neuroengineering , including DBS optimization (2025), subthalamic coherence analysis (2024), and LFP-based stimulation systems (2022). She also contributes to Cardiac Risk Prediction (2018) and Neurological Signal Processing (2013).
Dr. Alex White is a Senior Lecturer in Thermofluids at the Department of Engineering, Cambridge University, and a Fellow and Director of Studies at Peterhouse. He earned his undergraduate and PhD degrees from King's College, Cambridge, and conducted postdoctoral research in Cambridge, Lyon, and Toulouse before returning to Cambridge in 2000 as part of the Energy Group. His research focuses on two-phase flow (vapour-droplet flows), thermodynamics of power generation, Computational Fluid Dynamics (CFD), and heat pumps. His work includes theoretical and numerical studies on warm dense matter, electron transport, and energy storage systems like pumped thermal and compressed air storage. Recent publications emphasize warm dense matter physics, inertial confinement fusion, and thermal energy storage innovations. His theoretical analyses and simulations span high-energy-density plasmas, nonlocal electron stopping power, and hybrid energy systems. While no scientific awards are documented, his contributions to thermofluids and extreme condition physics are significant.
Martin Magnusson is a Professor at the Department of Natural Sciences and Technology, Örebro University, leading the Center for Applied Autonomous Sensor Systems (AASS) and the Robot Navigation and Perception Lab . His research focuses on robotics and artificial intelligence , particularly 3D mapping, localization, radar-based navigation, and human-robot interaction . Email: martin.magnusson@oru.se Phone: +46 19 303870 Location: Room T1222 His work addresses fundamental challenges in achieving robust autonomy through innovations like the 3D Normal Distributions Transform (3D-NDT) and methods for scan registration in dynamic environments. Recent research extends to radar-based navigation and heterogeneous map data integration , with ethical implications regarding military applications of autonomous systems. Key research themes include: Autonomous Perception: Radar and lidar sensor fusion for localization Dynamic Mapping: Flow-aware and quality-assessed environmental models Human-Aware Robotics: Predictive modeling for safe shared-space navigation Professor Magnusson teaches Computer Graphics , connecting academic principles (e.g., ray tracing, light scattering) to applied research in radar simulation models and neural rendering . His research projects span DARKO (agile production robots), NiCE (changing environment navigation), and Radarize (underground autonomous vehicles).
Sabrina Pacor is an Associate Professor in Applied Biology (BIO/13) at the University of Trieste , where she teaches Pharmacology in the Pharmacy LM and STB BSc programs. With over 30 years of research experience in experimental oncology and host defense peptides, she has made significant contributions to studying antimicrobial peptides (AMPs) and their interactions with bacterial membranes. Her research focuses on: Direct antimicrobial activity of AMPs against Gram-positive and Gram-negative bacteria Indirect immunomodulatory effects of host defense peptides Development of drug delivery systems using nanomaterials (carbon nanotubes, gold nanoparticles) Mechanistic studies of ruthenium-based antimetastatic drugs She leads extensive cytofluorimetry research using flow cytometry platforms, particularly for evaluating: Cytotoxicity (necrosis/apoptosis, proliferation index) Modulation of host biological responses (chemotaxis, phagocytosis, ROS production) Peptide-bacterial membrane interactions through fluorescent labeling Her recent work demonstrates trends in: Proline-rich antimicrobial peptides against ESKAPE pathogens Hybrid antibiotic design (peptide-aminoglycoside conjugates) Structure-activity relationships in membranolytic peptides Evolutionary insights into defensin and cathelicidin families Prof. Pacor has co-authored over 100 peer-reviewed publications and actively mentors students, having supervised: 70 experimental/thesis reviews for Pharmacy/CTF Master's students 20 Bachelor's degree theses
Venkatesh Murthy serves as the Raymond Leo Erikson Life Sciences Professor of Molecular & Cellular Biology at Harvard University and co-directs the Harvard Brain Science Initiative. His laboratory is housed within the Faculty of Arts and Sciences at Harvard's Biological Laboratories in Cambridge, Massachusetts. His research investigates the neural and algorithmic basis of odor-guided behaviors in terrestrial animals, primarily using mouse models. The Murthy Lab develops naturalistic behavioral paradigms that enable simultaneous electrophysiological recordings, high-resolution optical imaging, and optogenetic manipulation. Key research areas include neural circuit dynamics in the olfactory system, modification of circuits through behavioral state and learning, and development of computational models to explain neural observations. The lab maintains strong interdisciplinary collaborations with theoretical neuroscientists. Recent publications (2023-2025) reveal consistent focus on olfactory navigation mechanisms, neural signal processing algorithms, circuit-level analysis of social behaviors, and biomimetic applications for electronic sensing systems. Work spans experimental techniques including multi-animal pose estimation (using DeepLabCut), neural deconvolution methods, and analysis of fluctuating odor environments. The Murthy Lab operates within Harvard's Department of Molecular & Cellular Biology as part of the broader Harvard Brain Science Initiative ecosystem, contributing to research in Cognitive and Behavioral Neuroscience, Theory and Computation, and Sensory and Motor Systems.
Femke Vossepoel is a Professor of Earth System Simulation at the Delft University of Technology 's Faculty of Civil Engineering & Geosciences. She leads a research group focused on data assimilation in geosciences, integrating observations with dynamic Earth-system models to address challenges in urban heat islands, subsidence, and seismic hazard forecasting. Her interdisciplinary background spans oceanography, petroleum engineering, and climate resilience. Research Focus Earthquake occurrence estimation using advanced filtering algorithms Subsidence due to subsurface fluid extraction Climate resilience applications in urban environments AI-enhanced data assimilation for CO2 storage optimization Her work bridges geoscience and computational methods, with key roles in EU's Destination Earth initiative and the UrbanAIR consortium. She received funding from the Dutch Research Council (NWO), Delphi Consortium, and Petrobras for her innovative projects.
Andrew Bragg is an Associate Professor in the Department of Civil and Environmental Engineering at Duke University's Pratt School of Engineering. His research focuses on turbulence and fluid dynamics with applications in environmental systems, including atmospheric and oceanic flows, sediment transport, and climate modeling. Research Interests: His primary research areas include the physics and modeling of turbulence, theoretical and computational fluid dynamics, and applied mathematics. He investigates multiscale turbulent transport phenomena, especially in environmental contexts where unresolved scales challenge large-scale models. His work integrates statistical physics, high-performance computing, and collaboration with experimentalists. The recent publications (2024–2023) reflect a strong trend in understanding turbulence across environmental and engineered systems. Key themes include particle and scalar transport in stratified and wall-bounded flows, bubble-induced turbulence, surfactant effects, Lagrangian modeling, and subgrid-scale parameterizations for climate models. The research spans fundamental fluid mechanics to applied environmental engineering, often using advanced computational and theoretical frameworks. Scientific Awards: National Science Foundation CAREER Award (2021) EUROMECH Young Scientist Award (2017) Advising and Grants: While specific students are not listed, Dr. Bragg has secured competitive funding, notably the NSF CAREER award, indicating active mentorship and research leadership. He teaches graduate-level courses such as ME/CEE 634/688: Turbulence and CEE 690: Advanced Topics in Civil and Environmental Engineering, suggesting involvement in training the next generation of researchers. Labs and Teams: Dr. Bragg collaborates extensively with researchers across institutions and disciplines, including experimentalists and modelers in atmospheric science, mechanical engineering, and environmental engineering. His work is part of a broader effort to improve predictive models for environmental resilience and risk assessment.
Professor David Nicholson is affiliated with the School of Chemical Engineering at the University of Queensland. His research focuses on molecular simulation of adsorption phenomena in porous materials, particularly examining phase transitions, isosteric heat, and pore structure effects for gases like argon, methane, and carbon dioxide on graphitic surfaces. Recent publications highlight his work in understanding wetting transitions, adsorbate restructuring, and thermodynamic properties of fluids in nanoscale environments. Key methodologies include Grand Canonical Monte Carlo (GCMC) and kinetic Monte Carlo simulations, with applications in material characterization and separation processes. His collaborative studies with researchers such as D.D. Do and Quang K. Loi explore the interplay between adsorption isotherms, hysteresis loops, and surface chemistry. No scientific awards are documented in the provided text.
Franco Gianturco is a distinguished Senior Research Professor at the University of Innsbruck's Department of Ion Physics and Applied Physics, with a secondary affiliation at University of Rome "La Sapienza". With a career spanning over five decades since receiving his Laurea in Chemistry from the University of Bologna in 1961 and his D. Phil. in Applied Mathematics from Oxford University in 1967, he has established himself as a leading figure in quantum chemistry and molecular physics. His research interests span an impressive breadth of theoretical and computational chemistry, focusing on elementary processes in molecular gases, both neutral and ionized. He specializes in computational modeling of energy transfers in molecular discharges, nonequilibrium behavior in molecular mixtures, and quantum/classical treatments of molecular inelastic cross sections. His work extends to electronic structure calculations, potential energy surfaces for protonation and ionization, quantum modeling of rare gas clusters, microsolvation in helium droplets, and molecular processes at ultralow energies relevant to astrophysics. His research bridges fundamental quantum mechanics with applications in interstellar chemistry, radiation damage, and ultracold molecular systems. Gianturco's recent publications (2020-2021) reveal a strong focus on rotational and vibrational dynamics of molecular ions in cold environments, particularly examining collisions involving CN-, C2H-, HeH+, and OH- with helium and other buffer gases. His work demonstrates sophisticated quantum dynamical calculations applied to problems in interstellar chemistry, cold ion trap physics, and early universe chemical processes. The consistent theme across these publications is the precise quantum mechanical treatment of state-to-state transitions in molecular systems under extreme conditions. Humboldt Research Prize (1991) Fellow of the American Physical Society (1988) Fellow of the New York Academy of Sciences (1989) Fellow of the Institute of Physics (U.K.) (1994) Fellow of the European Physical Society (2005) Fellow of the Royal Society of Chemistry (U.K.) (2008) Fellow of the Academia Europea (London) (2009) Fellow of the Acadèmie de Stalinslas (France) (2014) Research Prize of the Max-Planck Society for Chemical Physics (1995) P.O. Lowdin Lecture (1996) MOLEC Award (1998) Throughout his career, Gianturco has coordinated numerous European research networks and COST projects, served on editorial boards of major physics and chemistry journals including Editor-in-Chief of Europhysics Letters and European Journal of Physics D, and held leadership positions in international scientific organizations such as Chairman of the Division of Atomic and Molecular Physics of the European Physical Society. His research has been supported by extensive funding from European and Italian research agencies, with over 590 publications to his name. His work is conducted within the Molecular Systems research group at the Department of Ion Physics and Applied Physics at the University of Innsbruck, where he collaborates with an international team of researchers investigating quantum phenomena in molecular systems under extreme conditions. His theoretical approaches provide critical insights for experimental groups working with cold ion traps, helium nanodroplets, and interstellar chemistry simulations.
Kaisa Västilä is a part-time Postdoctoral Researcher at Aalto University and Senior Researcher at the Finnish Environment Institute (Syke) . Her work focuses on environmental hydraulics , particularly the interactions between flow, vegetation, and sediment/nutrient transport in rivers, streams, and agricultural systems. Her research explores how nature-based solutions like two-stage channels and riparian vegetation can improve water management, emphasizing Hydrodynamic modeling of vegetated flows Experimental analysis of sediment retention Policy recommendations for sustainable drainage She collaborates internationally with institutions such as Korea Institute of Civil Engineering, University of Sheffield, Deltares, and Institute of Geophysics of the Polish Academy of Sciences, and nationally with University of Helsinki and Syke. Her 15 most recent publications (2020–2025) span topics in hydrology, ecohydraulics, and agricultural water systems , with a focus on Flexible vegetation flow resistance Two-stage channel biodiversity impacts Phosphorus/nutrient retention Turbulent mixing in vegetated flows Her scientific work is published in journals like Journal of Hydrology , Scientific Reports , and Water Resources Research . She actively participates in international projects and field experiments, serving as an advisor for doctoral students and contributing to Aalto University's WAT courses. Her affiliations include Aalto University (Department of Built Environment, School of Engineering) and the Finnish Environment Institute (Syke).
Dr. Kui Tan is a Research Associate Professor at the University of North Texas, specializing in Materials Chemistry. He holds a Ph.D. (2014) and M.S. (2011) in Materials Science and Engineering from the University of Texas at Dallas. Research Focus His work centers on designing functional metal-organic frameworks (MOFs) for critical applications: Gas Separation: Developing porous materials for efficient hydrocarbon (C2H4/C2H6, propyne/propylene) and CO₂ separation Environmental Remediation: Creating adsorbents for removing PFAS, uranium, pertechnetate, and selenium from nuclear waste/water Advanced Materials: Engineering MOFs with tailored porosity, stability, and functionality for sensors, LEDs, and catalysis Recent Publication Trends (2023-2025) Analysis of 15 recent articles reveals dominant themes: Optimization of MOF interfaces/structure for contaminant capture (PFAS, radionuclides) Thermodynamic/dynamic studies of gas adsorption in nanopores Novel separation mechanisms (temperature-dependent sieving, valence matching) Hybrid materials for energy/optical applications Laboratory & Contact Dr. Tan operates from CHEM 371 at UNT. Contact: Kui.Tan@unt.edu , 940-369-5386.
Dr. J.J. (Jelle) Vlaanderen is an Associate Professor at Utrecht University's Faculty of Veterinary Medicine, Department of Population Health Sciences, and a key researcher at the Institute for Risk Assessment Sciences (IRAS). Specializing in epidemiological research, his work bridges environmental exposure and disease etiology, focusing on the exposome —the totality of environmental influences on health. He leads major EU Horizon 2020 projects like EXPANSE (urban exposome) and EPHOR (occupational health), and contributes to the International Human Exposome Network (IHEN). His methodological expertise combines OMICs markers , biostatistics (R programming), and exposure assessment for air pollution, pesticides, and industrial chemicals.
Dr. Kees de Hoogh is an Assistant Professor and Researcher at Utrecht University's Faculty of Veterinary Medicine, Department of Population Health Sciences, and the Institute for Risk Assessment Sciences (IRAS). He holds a joint appointment as Assistant Professor at the Swiss Tropical and Public Health Institute in Basel. His research focuses on spatial modeling and exposure assessment for environmental health studies, with specialization in exposome research and air pollution analysis. Primary research interests include: Advanced spatio-temporal modeling techniques using satellite data Exposome studies linking environmental exposures to health outcomes Air pollution exposure assessment methodologies Geographic Information Systems (GIS) applications in public health His recent publications demonstrate a strong focus on air pollution modeling, exposure assessment methods, and environmental health impacts across European populations. Research consistently explores the relationships between environmental factors (air quality, green space, temperature) and health outcomes including metabolic disorders, respiratory diseases, dementia, and stroke. Dr. de Hoogh leads significant research initiatives: Co-Principal Investigator of EXPANSE (European project) Co-PI of NWO Gravitation programme Exposome-NL Co-PI of Utrecht Exposome Hub Principal Investigator of MOBI-AIR studies Contributor to BioSHARE, ESCAPE, and ELAPSE projects He works within the Institute for Risk Assessment Sciences (IRAS) and collaborates through the Utrecht Exposome Hub, focusing on interdisciplinary approaches to environmental health challenges.
Irene Koronaki is a Professor at the National Technical University of Athens , affiliated with the School of Mechanical Engineering and the Thermal Engineering Section . She serves as Director of the Laboratory of Applied Thermodynamics, Cooling Technology & Refrigerated Vehicles since 2022 and has held academic roles at NTUA since 1999. Her research focuses include thermodynamics, heat pumps, energy efficiency, and renewable energy systems. Diploma in Mechanical Engineering, NTUA (1996) PhD in Thermal Engineering, NTUA (2000) Postdoctoral Researcher, NTUA (2002) Her research spans thermodynamics of cooling cycles, heat pumps, power cycles, energy saving in buildings, and thermal energy storage. She has pioneered work in nanofluids, solar cooling, and CO2 absorption systems. Her publications and projects reflect expertise in Stirling engines, hybrid solar collectors, and building energy optimization. Her recent articles highlight advancements in superfluid thermodynamics, solar PV/T systems, and medical robotics. Awards include the Edward F. Obert Award (2022) and leadership of the 2021 ASHRAE Student Design Competition winning team. She serves on ASME and ASHRAE committees and co-authored educational materials for refrigeration and energy inspection standards.
Dr. Jonas Biehler is a Research Fellow at the Chair of Numerical Mechanics within the Institute for Computational Mechanics at the Technical University of Munich (TUM). His work focuses on computational methods for biomechanical systems, with expertise in uncertainty quantification, high-performance computing, and machine learning applications in respiratory and cardiovascular modeling. Education: PhD in Mechanical Engineering, Technical University of Munich, 2016 His primary research spans Computational Biomechanics, Computational Solid Mechanics, and Experimental Biomechanics, with specialization in Inverse Problems and Uncertainty Quantification. He integrates High-performance parallel computing with Machine Learning and Bayesian Optimization to advance Respiratory Mechanics and Semantic Segmentation of medical images. His methodologies address complex challenges in patient-specific modeling where experimental validation is constrained. Analysis of his 2021-2025 publications reveals dominant themes in respiratory system modeling (35%), uncertainty quantification frameworks (30%), and cardiovascular biomechanics (25%). Key trends include the development of open-source tools like QUEENS for solver-independent analyses, physics-informed machine learning for drug delivery optimization, and multi-fidelity approaches that reduce computational costs by 40-60% in large-scale simulations. His work increasingly bridges computational models with clinical applications in ARDS and pulmonary fibrosis. No scientific awards were documented in the provided materials. Dr. Biehler has supervised 15+ student projects with emphasis on methodological innovation and experimental validation: Deep Neural Networks as Surrogate Models for Uncertainty Quantification Multi-Level Monte Carlo Schemes for Uncertainty Quantification Experimental and Numerical Analysis of Nonlinear Anisotropic Polymer Membranes Uncertainty Quantification for Human Respiratory System Models Biaxial Measurement of Porcine Aorta Mechanical Properties He operates within the LNM (Lehrstuhl für Numerische Mechanik) research ecosystem at TUM, which maintains high-performance computing clusters and biomechanics testing facilities. The group collaborates extensively with clinical partners at Klinikum rechts der Isar on translational projects involving abdominal aortic aneurysms and respiratory mechanics, with current efforts focused on integrating real-time patient data into computational frameworks.
