جست‌وجوی استاد و پژوهشگر

Cecilia Sahlgrenمشاهده پروفایل

استاد

• Notch Signaling Pathway
• Cancer Biology
• Cell Biology
• +۵ مورد دیگر

Cecilia Sahlgren is a Professor at the Faculty of Science and Engineering , Department of Biochemistry and Cell Biology at Åbo Akademi University, affiliated with the InFLAMES Flagship (Innovation Ecosystem based on the Immune System) Solutions for Health. Her research focuses on cellular signaling mechanisms, particularly the Notch signaling pathway, and their roles in cancer biology, vascular homeostasis, and mechanobiology. She leads multiple high-impact projects funded by the European Commission, Finnish research councils, and foundations. Research Interests: Notch signaling pathway, cancer cell biology, vascular biology, mechanotransduction, and biomimetic modeling. Her work bridges basic science and translational research, addressing topics like blood-brain barrier delivery systems and tumor microenvironment modeling. Grants & Projects: NAP4DIVE (EU): Non-animal nanoparticle delivery platform for blood-brain barrier studies (2025–2028). Tumor-LN-oC (EU): Tumor lymph node-on-a-chip (2021–2025). SignalSheets: Multilayer mechanosignaling in vascular systems (2020–2024). Awards: 2018: Knight, First Class, of the Order of the White Rose of Finland. 2018: Member of The Finnish Society of Sciences and Letters. 2017: Member of the Swedish Academy of Engineering Sciences in Finland. 2013: ÅAU Chancellor’s Prize for best publication. Labs/Teams: Leads interdisciplinary teams in vascular biology, cancer research, and biomaterials, collaborating internationally on projects like OptoNotch (light-activated signaling) and computational arterial modeling.

Sven Ahrendمشاهده پروفایل

استاد

• Fluid Dynamics
• Computational Fluid Dynamics
• Magnetic Resonance Velocimetry
• +۳ مورد دیگر

Sven Ahrend is a Professor at the Institute for Mathematics within the Faculty of Mathematics and Natural Sciences at the University of Rostock, Germany. His office is located at Ulmenstraße 69, Haus 3, Room 230 in Rostock (18051), with contact number +49 (0)381 498 6605. His research spans Fluid Dynamics , Computational Fluid Dynamics , and Magnetic Resonance Velocimetry , with significant applications in biomedical engineering, nuclear reactor design, and environmental fluid mechanics. Key interests include turbulence modeling in placental hemodynamics, cerebral aneurysm analysis, nuclear fuel assembly hydrodynamics, and submarine groundwater discharge systems. His work consistently bridges experimental MRV techniques with CFD validation, emphasizing industrial and medical applications. Analysis of his 15 most recent publications (2024-2025) reveals a dominant focus on MRI-based flow quantification for complex biological and engineering systems. Over 60% of articles address biomedical applications (placental/cerebral flows), while 30% target nuclear reactor safety, and 10% explore environmental fluid dynamics. Methodologically, all studies integrate advanced MRV measurements with CFD validation, highlighting his expertise in turbulence measurement and error quantification. His experimental work is anchored in the MRI Flow Lab at University of Rostock, which develops cutting-edge techniques for 3D velocity mapping in porous media and technical flows. Current projects include patient-specific lattice-Boltzmann simulations for aneurysm analysis and 3D-printed placental models for reproductive health research.

• Computational Biology
• Fluid Dynamics
• Scientific Computing
• +۴ مورد دیگر

Thomas Fai is an Associate Professor of Mathematics at Brandeis University, affiliated with the Department of Mathematics, the Benjamin and Mae Volen National Center for Complex Systems, and the Interdepartmental Program in Neuroscience. His research focuses on mathematical biology, data-driven modeling, multiscale numerical methods, and applied probability, with applications in fluid dynamics, cellular processes, and biophysical systems. Fai holds a Ph.D. from New York University and a B.S. from the University of Michigan-Ann Arbor. His research integrates experimental data with computational models to address questions in biology, such as nucleocytoplasmic transport, red blood cell dynamics, and protocell behavior. He emphasizes the use of large datasets from microscopy and employs advanced numerical methods like the Lubricated Immersed Boundary Method. Fai has been recognized with the 2022 GSAS Mentorship Award for his teaching and mentorship efforts, which incorporate inquiry-based learning approaches. His work spans interdisciplinary collaborations, addressing topics like osmotic regulation of nuclear size, microfluidic clogging phenomena, and synaptic architecture. Fai’s affiliations reflect his engagement with complex systems research, neuroscience, and mathematical applications across biological scales.

Maurizio Martinoمشاهده پروفایل

استاد

• Laser-Matter Interaction
• Optoelectronics
• Nanotechnologies
• +۳ مورد دیگر

Maurizio Martino is Full Professor of Physics of Matter at the University of Salento's Department of Mathematics and Physics 'Ennio De Giorgi'. His expertise includes laser-matter interaction, optoelectronics, nanotechnologies, sensors, optics, nuclear detectors, and contact lens research. He serves as a Third Degree Radiation Protection Expert and founded the Lecce Laser Laboratory (L3 group). Martino directs the Center for Advanced Contactology Research (CERCA), investigating novel contact lenses and tear substitutes through industry collaborations. His extensive publication record spans nanostructured films, nuclear detectors, and optoelectronic materials. Recent research focuses on laser-induced diamond graphitization for particle detectors in next-generation accelerators (PADME experiment). Administratively, Martino coordinates internationalization efforts and serves on several committees including the Environment and Health Commission of the Medical Association. He teaches Laboratory Physics and Nanotechnology courses and supervises doctoral candidates in Physics and Nanoscience.

Mads Peter Sørensenمشاهده پروفایل

استاد

• Nonlinear Dynamics
• Applied Mathematics
• Superconductivity
• +۵ مورد دیگر

Mads Peter Sørensen is a Professor in the Department of Applied Mathematics and Computer Science at the Technical University of Denmark (DTU). His research focuses on nonlinear dynamics, superconductivity, and fluid dynamics, with contributions to mathematical modeling in fields such as disease dynamics, traffic flow, and acoustics. He is actively involved in interdisciplinary projects, including studies on methane cracking for carbon production and bacterial biofilm growth in microfluidic systems. His work aligns with UN Sustainable Development Goals related to sustainable energy and health. Key projects include investigations into superconducting elements, nonlinear stochastic models of molecular crystals, and ultra-short optical pulse generation. Sørensen has collaborated internationally, contributing to over 147 publications. Notable recent work includes studies on memory effects in disease modeling and nonlinear oscillations in acoustic systems. He has advised multiple research projects, including those on high-temperature superconductivity and flux dynamics. His research often integrates analytical and numerical methods, addressing both fundamental and applied challenges in nonlinear systems.

Tony Gengمشاهده پروفایل

استادیار

• Computer Architecture
• Machine Learning
• Generative AI
• +۶ مورد دیگر

Tony Geng is an Assistant Professor at the University of Rochester, jointly appointed in the Departments of Electrical and Computer Engineering and Computer Science. He directs the IntelliArch Lab and holds secondary affiliations with the Goergen Institute for Data Science. His research spans computer architecture, generative AI, graph intelligence, and high-performance computing, focusing on sustainable and efficient artificial general intelligence. His work integrates hardware-software co-design for accelerating machine learning workloads, with applications in scientific discovery, fintech, and social media. Recent projects explore dynamical systems for graph learning and diffusion models for scientific simulations. Notable recognitions include multiple DOE and NSF research awards, the Excellence in Graduate Teaching Award, and substantial GPU allocations from NERSC for generative AI research. He actively mentors PhD students and postdocs in sustainable AI development.

Yoichiro Moriمشاهده پروفایل

استاد

• Mathematical Biology
• Physiology
• Biophysics
• +۴ مورد دیگر

Yoichiro Mori is the Calabi-Simons Professor in Mathematics and Biology at the University of Pennsylvania, affiliated with the School of Arts and Sciences. His positions span the Department of Mathematics and the Department of Biology, reflecting his interdisciplinary research focus. He holds an office in both DRL 4N20 (Math) and Levin 352 (Biology). His research interests encompass Mathematical Biology, Physiology, Biophysics, and Applied and Numerical Analysis. Key areas include electrodiffusion theory, cell volume regulation, fluid dynamics of elastic structures, and computational models of physiological processes like cortical spreading depression and cardiac electrophysiology. Mori’s recent work emphasizes theoretical and numerical analysis of slender body theory, ion transport phenomena, and the interplay between cellular mechanics and biochemical signaling. Notable contributions include studies on the Peskin problem, osmotic water flow, and the dynamics of deformable membranes in viscous fluids. His publications frequently address topics such as cell migration energetics, multidomain electrodiffusion models, and mathematical frameworks for biological systems. Collaborations span applied mathematics, bioengineering, and experimental biology, with a focus on bridging theoretical models and real-world biological phenomena.

Sergey Churakovمشاهده پروفایل

استاد

• Geochemical Modeling
• Atomistic Simulations
• Thermodynamics
• +۲ مورد دیگر

Prof. Sergey Churakov is a Full Professor of Mineralogy at the University of Bern and Head of the Laboratory for Waste Management at the Paul Scherrer Institute (PSI) in Switzerland. His research integrates computational and experimental approaches to address geochemical processes, nuclear waste safety, and material science challenges. Education: PhD in Physical-Chemical Properties of Complex Natural Fluids (TU Berlin, 2001) M.S. in Applied Mathematics (Moscow State University, 1997) M.S. in Geochemistry (Moscow State University, 1996) Research Focus: Churakov's work spans multi-scale geochemical modeling, atomistic simulations of fluid-solid interfaces, thermodynamic equilibrium in high-pressure systems, and machine learning applications in geochemistry. His lab investigates mineral reactivity, radionuclide transport, and sustainable material design for environmental and industrial applications. Publication Trends: Recent articles (2024-2025) emphasize machine learning-enhanced material discovery, nuclear waste containment mechanisms, and atomistic studies of mineral surfaces. His interdisciplinary output bridges geochemistry, materials science, and computational physics. Awards: No specific scientific awards are listed in the provided text. Labs & Teams: Leads the Laboratory for Waste Management at PSI, focusing on geochemical barriers for nuclear waste, reactive transport modeling, and collaborative projects like EURAD on nuclear safety digitalization.

Georgios Anagnostopoulosمشاهده پروفایل

دانشیار

• Machine Learning
• Artificial Intelligence
• Optimization
• +۴ مورد دیگر

Georgios C. Anagnostopoulos is a tenured Associate Professor at Florida Institute of Technology's College of Engineering and Science, Department of Electrical Engineering and Computer Science. He leads the Machine Learning Research Group and co-directs the Center for Advanced Data Analytics & Systems (CADAS). Ph.D. in Electrical Engineering (University of Central Florida, 2001) M.S. in Electrical Engineering (University of Central Florida, 1997) Eng. Dipl. in Electrical Engineering (University of Patras, Greece, 1994) His research spans foundational AI/ML with applications in social network dynamics, environmental monitoring, and cybersecurity. Key contributions include: Information diffusion modeling via self-exciting processes Deep learning for nuclear explosion detection and flood hazard assessment Transformer-based edge computing for environmental sound classification Multi-task learning with Rademacher complexity analysis Multi-domain cyber-physical systems analysis Recent publications focus on optimization algorithms for social network analysis, flood prediction in ungauged basins, and acoustic gunshot detection systems. He has secured over $3 million in federal funding, including grants from DARPA and the Defense Threat Reduction Agency. Scientific awards held by his mentees include: Barry Goldwater Scholarship (Joey Velez-Ginorio) NSF Graduate Research Fellowship (multiple recipients) Frost Scholarship (Oxford University) UCF Distinguished Undergraduate Researcher Award He has advised over 8 graduate students, including Ph.D. researchers in machine learning and software engineering now employed at Google, Twitter, Expedia Group, and pursuing doctoral studies at University of Pennsylvania. His group maintains active collaborations with Air Force Research Laboratory and University of Central Florida.

• Artificial Intelligence
• Cognitive Robotics
• Discrete Optimization
• +۵ مورد دیگر

Florian Herzog is a Lecturer at the Lucerne School of Computer Science and Information Technology (HSLU). He holds a PhD in Bioinformatics from ETH Zurich, a Master of Science in Bioengineering and Biotechnology from EPFL (with a research stay at Columbia University), and a Bachelor in Life Sciences and Technologies from EPFL. His professional roles include Senior Researcher at HSLU and Co-Leader of the CAS Artificial Intelligence program. Herzog's research focuses on Cognitive Robotics, Artificial Intelligence, Discrete Optimization, and Data Science, with projects addressing AI-driven process optimization in tourism and technical customer service. He co-leads the Cognitive Robotics Lab and has contributed to research on hybrid teaching formats and AI applications in design and production processes. His academic contributions span computational biology, bioinformatics, and applied AI. Education: PhD in Bioinformatics, ETH Zurich Master of Science in Bioengineering and Biotechnology, EPFL (with research at Columbia University) Bachelor in Life Sciences and Technologies, EPFL Research Interests: Cognitive Robotics and AI applications in real-world systems Discrete optimization for scheduling and precedence constraint problems Data science methodologies for process automation AI-driven solutions in tourism and customer service Notable Projects: "Intelligente Auskunftssysteme im Tourismus" (AI-based tourism information systems) "Kognitive Services im Technischen Kundendienst" (cognitive services in technical customer service) Optimizing design/production processes via AI Lab Affiliation: Cognitive Robotics Lab at HSLU.

• Computer Vision
• Machine Learning
• Deep Learning
• +۲ مورد دیگر

Thomas Koller is a Professor and Head of the Master's Program in Engineering at Lucerne University of Applied Sciences and Arts, affiliated with the School of Computer Science and Information Technology. His research focuses on computer vision, machine learning, and medical image analysis applications. His primary research domains include: Computer Vision and Image Processing Deep Learning and Reinforcement Learning Medical Imaging and Diagnostic Applications His publications demonstrate strong focus on applying computer vision and deep learning techniques to medical challenges, particularly in dermatology and vascular imaging. Recent work shows increasing emphasis on real-world healthcare applications and interactive systems. Scientific Awards: Best Poster Video Award (2022) aha! Award des Allergiezentrums Schweiz (2017)

Montserrat Casas Ametllerمشاهده پروفایل

استاد

• Quantum Information
• Semiclassical Methods
• Nuclear Structure
• +۲ مورد دیگر

Montserrat Casas Ametller is a Full Professor at the University of the Balearic Islands, where she has held her position since February 1994. She earned her PhD in Physics from the Autonomous University of Barcelona in 1981, following her undergraduate degree from the same institution in 1977. Her research spans: Quantum information and entangled states Semiclassical methods in physics Nuclear structure analysis Alpha spectrometry applications Cosmic radiation composition Professor Casas Ametller's publications focus on foundational aspects of quantum mechanics, including entanglement dynamics, quantum information metrics, and semiclassical entropy formulations. Her work bridges theoretical physics with practical applications in nuclear science and materials research. She has presented her research internationally at institutions including the Autonomous University of Barcelona, University of Córdoba (Argentina), and Bariloche Atomic Center (Argentina).

Mark Ainslieمشاهده پروفایل

مدرس

• Applied Superconductivity
• High-Field Magnets
• Superconducting Electric Machines
• +۴ مورد دیگر

Dr. Mark Ainslie is a Lecturer in Engineering and Head of the Superconducting Technology + Cryogenics research group at King's College London's Department of Engineering, Faculty of Natural, Mathematical & Engineering Sciences. His expertise spans applied superconductivity, high-field magnet design, and superconducting electric machines. He holds a B.E. and B.A. from the University of Adelaide, an M.Eng. from the University of Tokyo, and a PhD from the University of Cambridge. Education: B.E. (Electrical & Electronic) & B.A. (Japanese), University of Adelaide (2004) M.Eng. (Superconducting Fault Current Limiter Design), University of Tokyo (2008) PhD (Transport AC Loss in High-Temperature Superconducting Coils), University of Cambridge (2012) Research focuses on applied superconductivity for sustainable electric transportation, medical/industrial magnets, and numerical modeling. His work bridges materials science, numerical simulations, and engineering applications. Awards include the 2011 ESAS Young Researcher Award, IOP Brian Pippard Prize (2021), and Guinness World Record for strongest trapped magnetic field (2014). His research addresses challenges in high-field magnet systems and superconducting materials. Labs/Teams: Leads the Superconducting Technology + Cryogenics group. Collaborates internationally on projects like bulk superconductor magnetization and HTS dynamos.

• Accelerator Physics
• Medical Physics
• Proton Therapy
• +۶ مورد دیگر

Prof. Sytze Brandenburg is a Professor of Accelerator Physics at the University of Groningen's Faculty of Medical Sciences, affiliated with the Kernfysisch Versneller Instituut (KVI). He leads groups in Medical Physics and Accelerator Physics. His work focuses on particle accelerators, proton therapy, nuclear physics, and radiation detection. Brandenburg holds a PhD in Nuclear Physics and has over 30 years of experience in accelerator development, including roles at the AGOR cyclotron facility. Education: PhD (cum laude) in Mathematics and Natural Science, University of Groningen (1985) MSc in Experimental Physics, University of Groningen (1980) Research Interests: Accelerator technology, proton therapy, ionizing radiation production/detection, nuclear power, and radioisotope production. Recent work includes developing proton dose engines, improving proton radiography systems, and studying radiation effects on biological systems. He has been awarded the Knighthood Order Netherlands Lion (2017) and contributed to major facilities like the AGOR cyclotron and the Particle Therapy Research Center (PARTREC). Collaborations span institutions globally, focusing on medical applications and accelerator advancements.

Farzad Rahnemaمشاهده پروفایل

استاد

• Nuclear Engineering
• Radiation Transport
• Reactor Physics
• +۴ مورد دیگر

Dr. Farzad Rahnema is the Georgia Power Company Distinguished Professor of Nuclear Engineering and Director of the Computational Reactor and Medical Physics (CRMP) Laboratory at Georgia Institute of Technology. He holds a Ph.D. from the University of California, Los Angeles (1981), an M.S. from Louisiana State University (1977), and a B.S. from Illinois Institute of Technology (1975). Prior to Georgia Tech, he spent 11 years at General Electric Nuclear Energy, leading development of the PANACEA 3-D Core Simulator for reactor design and MONICORE systems for Boiling Water Reactor monitoring. His research focuses on theoretical and computational radiation transport, reactor physics, and high-fidelity modeling of nuclear systems. Key areas include COMET (Coarse Mesh Radiation Transport) methods, nuclear security, and medical physics applications like radiotherapy calculations. He has published over 240 peer-reviewed articles and holds a U.S. patent (7,676,015B2) for Boundary Condition Adjustment Methods. Dr. Rahnema is an American Nuclear Society (ANS) Fellow (2003) and recipient of the 2019 ANS Gerald C. Pomraning Memorial Award for contributions to mathematics and computation in nuclear fields. He has served as Chair of Georgia Tech’s Nuclear & Radiological Engineering and Medical Physics Programs (2002–2016), ANS Mathematics and Computation Division (twice), and the Reactor Physics Division (2007–2008). His leadership extends to editorial roles: Editor-Designate of *Nuclear Science and Engineering*, and advisory board member for *Annals of Nuclear Energy* and *Nuclear Technology*. He founded the Southeastern Universities Nuclear Research Institute for Science and Education (SUNRISE) and chaired the 16th International Conference on Transport Theory (1999). Research contributions include benchmark problems for advanced reactor designs (e.g., AHTR, SmAHTR), neutronics challenges in fluoride-salt-cooled reactors, and cross-section generation methods. His work bridges computational efficiency and nuclear safety, with applications in reactor core analysis, medical physics, and multiphysics coupling.