جست‌وجوی استاد و پژوهشگر

Bernd Brauneckerمشاهده پروفایل

مدرس

• Quantum Physics
• Nanomaterials
• Energy Control
• +۳ مورد دیگر

Bernd Braunecker serves as a Lecturer in Theoretical Physics at the University of St Andrews' School of Physics and Astronomy since 2013, following a PhD from Ecole Polytechnique Federale de Lausanne and postdoctoral fellowships at Massachusetts Institute of Technology, Brown University, University of Basel, and Universidad Autonoma de Madrid. His academic trajectory includes: PhD in Physics (docteur es sciences) from Ecole Polytechnique Federale de Lausanne Postdoctoral research at MIT, Brown University, University of Basel, and Universidad Autonoma de Madrid Research centers on quantum control in nanoscale systems , specifically understanding, designing, and manipulating quantum and energy effects in hybrid nanomaterials. His work bridges theoretical condensed matter physics and quantum thermodynamics , focusing on nanometric interacting systems where quantum coherence and energy transport phenomena dominate. Key investigations include spin-bath interactions, quantum rectification, and metastable charge states in low-dimensional structures. Publication trends (2013-2022) reveal consistent exploration of quantum transport in nanodevices, with emphasis on many-body effects in quantum wires, double quantum dots, and carbon nanotubes. His work demonstrates strong theoretical rigor in modeling non-equilibrium quantum dynamics, particularly regarding entanglement detection, Fermi-edge singularities, and thermoelectric phenomena at the nanoscale.

Roland Ketzmerickمشاهده پروفایل

استاد

• Quantum Chaos
• Hamiltonian Systems
• Floquet Systems
• +۳ مورد دیگر

Roland Ketzmerick is a Professor of Computational Physics at Technische Universität Dresden since 2002, with a Max Planck Fellow position at the Max Planck Institute for the Physics of Complex Systems (2010–2020). He was spokesperson for the DFG Forschergruppe FOR760 on Scattering Systems with Complex Dynamics (2010–2013). His research focuses on quantum chaos in mixed systems, power-law trapping in Hamiltonian systems, Floquet systems , Hamiltonian ratchets , mesoscopic physics , fractal spectra , and Bloch electrons in magnetic fields . His work bridges classical and quantum dynamics, exploring tunneling, wavefunction statistics, and nonequilibrium phenomena. His publications demonstrate a strong emphasis on chaotic resonance states , dynamical tunneling , multifractal analysis , and quantum transport in complex systems. Recent articles (2022–2025) address dielectric cavities, ultracold atom entanglement, and 4D Hamiltonian structures. Scientific Awards : Otto-Klung-Prize (1999)

Gregory J. Wagnerمشاهده پروفایل

دانشیار

• Additive Manufacturing
• Multi-scale Simulations
• Multi-physics Modeling
• +۴ مورد دیگر

Gregory J. Wagner is an Associate Professor of Mechanical Engineering and Director of Graduate Studies at Northwestern University's McCormick School of Engineering. His research focuses on developing computational methods for multi-scale and multi-physics problems in additive manufacturing, fluid dynamics, and heat transfer. He leads the Wagner Research Group, which specializes in high-performance computing tools for complex engineering simulations. Education includes a Ph.D., M.S., and B.S. in Mechanical Engineering from Northwestern University and Boston University. His work integrates machine learning with traditional computational methods to model material behavior, microstructure evolution, and process-structure-property relationships in advanced manufacturing. Notable contributions include the GO-MELT framework for thermal simulations and the C-HiDeNN neural network approach for large-scale systems. Research interests span additive manufacturing process modeling, multiphysics coupling, and data-driven approaches for material design. Awards include the Bette and Neison Harris Chair in Teaching Excellence. Publications emphasize thermal modeling, phase change phenomena, and computational fluid dynamics innovations. His lab's work bridges mesoscopic and multiscale modeling, with applications in energy systems, biomedical devices, and environmental engineering. Collaborations focus on experimental validation and industrial-scale simulation challenges.

• Transport Engineering
• Sustainable Transportation
• Traffic Management
• +۶ مورد دیگر

Dr. Ioannis Kaparias is an Associate Professor in Transport Engineering at the University of Southampton, affiliated with the Transportation Research Group (TRG). He holds a Master of Engineering from Imperial College London and a PhD from the same institution. His academic career includes roles at City, University of London, and postdoctoral research at Imperial College. He is a Fellow of Advance HE, a member of the Chartered Institute of Highways and Transportation (CIHT), and serves as Deputy Editor-in-Chief of the IET Intelligent Transport Systems journal. Education: MEng in Civil Engineering, Imperial College London (2004) PhD in Transport Engineering, Imperial College London (2008) Postdoctoral Researcher, Imperial College London (2008–2012) Research Interests: Efficient, safe, and sustainable land transport systems Highway and traffic management, including real-time routing and network reliability Active travel modes (cycling/pedestrian infrastructure) Public transport operations and optimization New transport technologies (CAVs, MaaS, EVs) Land use-transport interaction models Teaching: Highway & Traffic Engineering modules at Southampton Doctoral Programme Director (Training) in the School of Engineering Past roles include teaching at Imperial College London, City University London, and the University of East London External Roles: Member of US Transportation Research Board committees (Pedestrians/ACH10 and Human Factors/ACH40) Independent expert for the European Commission Speaker at international conferences (e.g., 'To share or not to share space? A very British tale', 2023)

Tim Murphyمشاهده پروفایل

استاد

• Neuroscience
• Neuroplasticity
• Stroke Recovery
• +۴ مورد دیگر

Tim Murphy is a Professor in the Department of Psychiatry at the University of British Columbia's Faculty of Medicine. He holds a B.Sc. from Saint Mary's College (1984), Ph.D. from Johns Hopkins University (1989), and completed postdoctoral training at Johns Hopkins (1994). He is a Full Member of the Djavad Mowafaghian Centre for Brain Health and leads UBC's Dynamic Brain Circuits in Health and Disease research cluster. His research focuses on understanding brain circuit reorganization after stroke using advanced neuroimaging techniques. Key areas include: In vivo imaging of synaptic interactions and sensorimotor processing Optogenetic brain mapping and neuroplasticity mechanisms Development of automated imaging/stimulation tools for neurological disorders Mouse models of stroke, depression, and autism Synthetic data approaches for behavioral analysis Dr. Murphy's recent publications demonstrate strong focus on developing novel neurotechnologies, including mesoscale imaging systems, 3D calibration tools, and synthetic biomarkers. His work integrates neuroscience with biomedical engineering and computational approaches. He leads an active laboratory developing open-source neuroscience hardware and software. The lab participates in the Canadian Neurophotonics Platform and has created innovative tools like the Diesel2P mesoscope and automated home-cage imaging systems.

• Concrete Materials Science
• Structural Engineering
• Computational Modeling
• +۴ مورد دیگر

Dr. Tathagata Bhaduri is a Lecturer in the Department of Civil and Environmental Engineering at Rensselaer Polytechnic Institute (RPI). He holds a Ph.D. in Civil Engineering from RPI (2021), an M.Tech. from the Indian Institute of Technology, Kanpur (2016), and a B.E. from the Indian Institute of Engineering, Science and Technology, Shibpur (2014). His research focuses on computational modeling of ultra-high-performance concrete (UHPC), particularly multi-scale techniques, fiber orientation effects, and failure modes in UHPC structures. He also explores smart systems for structural vibration control using bracing and fluid dampers. Dr. Bhaduri teaches core courses including Strength of Materials and Engineering Economics, and served as the course coordinator for Strength of Materials in Fall 2023. His professional involvement includes contributions to the American Concrete Institute (ACI) 239C committee, aiding in UHPC design guide development. His publications emphasize UHPC's mechanical properties, multi-scale modeling, and fiber-reinforced material behavior. Research trends highlight interdisciplinary approaches combining experimental and computational methods to address structural challenges in advanced materials.

Di Zhuمشاهده پروفایل

استادیار

• Geographic Information Science
• Geospatial Artificial Intelligence (GeoAI)
• Spatial Networks
• +۶ مورد دیگر

Di Zhu is an Assistant Professor of Geographic Information Science at the University of Minnesota's Department of Geography, Environment and Society. He directs the Geospatial Data Intelligence (GeoDI) Lab, focusing on GeoAI and social sensing to analyze human-environment interactions in urban systems, public health, and socioeconomic dynamics. His educational background includes a PhD in Cartology and GIScience from Peking University, complemented by a BSc in GIS and a BA in Economics from the same institution. Key research interests include spatial regression models, human mobility patterns, and GeoAI applications. He has collaborated on projects funded by NIH, NSF, and other agencies, exploring topics like spatiotemporal data imputation, urban flow analysis, and pandemic spatial dynamics. His work bridges traditional GIScience with modern machine learning techniques, emphasizing actionable insights from big geospatial data. Teaching focuses on advanced GIS, numerical spatial analysis, and urban sensing. He actively mentors students through the University of Minnesota's Master of GIS program and serves on academic boards including CPGIS. Current projects include analyzing Twin Cities mobility networks and developing intelligent spatial prediction frameworks.

Hakan Türeciمشاهده پروفایل

استاد

• Quantum optics
• Quantum information
• Superconducting circuits
• +۳ مورد دیگر

Hakan Türeci is Professor of Electrical and Computer Engineering at Princeton University, with joint affiliation at the Princeton Materials Institute. A theoretical physicist by training, his research explores quantum optics, quantum information science, and superconducting circuits for quantum computing applications. Education: Ph.D. from Yale University (2003) M.S. in Physics from Bilkent University, Turkey (1996) B.S. in Physics from Bilkent University, Turkey (1994) Research Interests: Focuses on non-equilibrium quantum phenomena in optical and microwave platforms, quantum simulation, quantum error correction, and the development of near-term quantum devices for computation and machine learning. Publication Trends: Recent work emphasizes quantum system modeling, quantum measurement techniques, Josephson junction physics, and applications of reservoir computing in quantum information processing. Academic Leadership: Advises a large group of graduate students and researchers in quantum engineering projects, collaborating across physics and engineering disciplines to advance quantum technologies.

• Superconductivity
• Mesoscopic Phenomena
• Quantum Electronics
• +۳ مورد دیگر

Prof. Vladimir Krasnov is a leading researcher in Experimental Condensed Matter Physics at Stockholm University , focusing on mesoscopic superconductivity, Josephson junctions, and nanoscale quantum phenomena. He heads the Experimental Condensed Matter Physics Group since 2005. Department: Department of Physics Lab: EKMF Lab (SU-KTH collaboration) Key Methodologies: Pulsed laser deposition, FIB nanofabrication, cryogenic measurements (0.25-300 K), THz spectroscopy Research Themes: His work bridges fundamental superconductivity studies (high-Tc cuprates, iron-pnictides) with applied quantum electronics. Notable contributions include Developing vortex-based cryogenic memory Controllable spin-triplet supercurrents in magnetic junctions THz emission from intrinsic Josephson stacks Quantum phase transitions via electrical doping Magnetic field effects on mesoscopic systems Scientific Trends: Analysis of 15 recent publications reveals strong emphasis on Josephson vortex dynamics, superconducting/ferromagnetic hybrid systems, THz applications, and non-equilibrium phenomena in quantum circuits. Facilities: Utilizes Nano-Fab clean-room for sample engineering and Low-T lab for high-field (17T), cryogenic experiments.

• Quantum Information
• Ultracold Atoms
• Quantum Many-Body Systems
• +۳ مورد دیگر

Dr. Philipp Preiss is the Group Leader of the Atomic Quantum Matter research group at the Max Planck Institute of Quantum Optics. His work focuses on experimental quantum information science applied to ultracold atomic systems, leveraging quantum gas microscopy and optical lattice technologies to study many-body quantum systems with single-particle control. He leads the UniRand project, funded by an ERC Starting Grant, which aims to develop a novel optical lattice system for studying quantum phase transitions and entanglement dynamics at the intersection of condensed matter physics and quantum information science. Research Interests: Quantum simulation using ultracold atoms Entanglement dynamics in many-body systems Quantum phase transitions and criticality Optical lattice engineering and single-atom control Random unitary protocols and basis-independent measurements Key Contributions: His recent work explores emergent hydrodynamic behavior in fermionic systems, Cooper pairing in two-dimensional Fermi gases, and novel cooling techniques like quantum virtual cooling. The group also investigates skyrmion ground states and Pauli crystals in rotating ultracold gases. Awards: ERC Starting Grant (2020): UniRand – Random Unitaries in a Rapid Optical Lattice Simulator Advising & Infrastructure: His labs include the FermiQP Lab and Lithium Lab , equipped for advanced quantum gas microscopy and optical tweezer experiments. The group collaborates on interdisciplinary projects, such as the HDvent Emergency Ventilator System , demonstrating applications of quantum engineering principles in medical technology.

Sergei Fedotovمشاهده پروفایل

استاد

• Random Walk Theory
• Reaction-Diffusion Systems
• Non-Markovian Processes
• +۳ مورد دیگر

Professor Sergei Fedotov is a Professor of Applied Mathematics in the Department of Mathematics at the University of Manchester. He holds a PhD from Ural Federal University (1986) and has held academic positions in London, Aachen, Wuppertal, and Berlin before joining Manchester in 1998. His research focuses on random walk theory, reaction-transport systems, and anomalous transport phenomena with applications to biophysics, nanotechnology, and cancer biology. His expertise includes non-Markovian models, fractional calculus, and interdisciplinary collaborations in areas such as intracellular transport, nanoparticle dynamics, and DNA repair. Fedotov has led major grants, including EPSRC-funded projects on nanoparticle transport in radiotherapy and FAPESP-UoM collaborations on correlated memory in biological systems. He has supervised PhD students including Anna Gavrilova, Daniel Han, and Helena Stage, and collaborates with institutions globally, such as Universitat Autònoma de Barcelona and The Christie Hospital. Key research themes include stochastic models of subdiffusion/superdiffusion, fractional partial differential equations, and the application of statistical mechanics to biological systems. His work contributes to sustainable development goals through advancements in medical physics and environmental modeling. Recent publications explore heterogeneous transport in C. elegans, stochastic water flow dynamics, and the modeling of radiation-induced DNA damage. Fedotov’s team develops novel frameworks to bridge theoretical mathematics with experimental biology, emphasizing the role of memory effects and non-equilibrium processes. Grants managed include the EPSRC £702k project on improving radiotherapy via nanoparticle transport modeling (2021–2025) and the FAPESP-UoM study on correlated memory in biological systems (2018–2022). His work integrates mathematical rigor with experimental validation, addressing challenges in cellular logistics and disease mechanisms.

• Neural Network Dynamics
• Computational Neuroscience
• Theoretical Physics
• +۳ مورد دیگر

Prof. Raoul-Martin Memmesheimer is a Professor at the University of Bonn's Institute of Genetics , contributing to the Transdisciplinary Research Area (TRA) - Life and Health . His research focuses on understanding neural network dynamics across microscopic, mesoscopic, and large-scale phenomena, integrating mathematical approaches with neurophysiological insights. Key interests include the dynamics of precise spiking activity, collective network behavior, and computational principles underlying neural systems. Education & Background : While specific educational details are not listed, his position as a Professor indicates advanced academic qualifications in theoretical neuroscience or related fields. Research Interests : Memmesheimer's work bridges theoretical physics and computational neuroscience, addressing topics like spiking neuron models, learning in neural networks, and the emergence of complex behaviors. His group employs methods from computer science and applied mathematics to study how neural systems perform computations through their dynamic properties. Publications : Recent work explores topics such as gradient descent learning in spiking networks, STDP-based assembly dynamics, and oscillatory phenomena in hippocampal regions. These publications highlight his focus on both foundational theory and applications to biological systems. Awards & Collaborations : While no specific awards are listed, his participation in TRA Life and Health underscores collaborative efforts in transdisciplinary health-related research. His work is supported by the University of Bonn's strong focus on transdisciplinary innovation. Labs & Teams : His research group operates within the Institute of Genetics, leveraging interdisciplinary resources at the University of Bonn to advance theoretical neuroscience and computational biology.

Anirban Chakrabortiمشاهده پروفایل

استاد

• Econophysics
• Sociophysics
• Complex Systems
• +۱۴ مورد دیگر

Anirban Chakraborti is a Professor at the School of Computational and Integrative Sciences, Jawaharlal Nehru University (JNU), New Delhi, India, where he has been a faculty member since 2014. He previously held academic positions at École Centrale Paris (France) as Chercheur Senior (Associate Professor) and Chargé de Recherche (Assistant Professor), and earlier roles at Banaras Hindu University, Brookhaven National Laboratory (USA), and Helsinki University of Technology (Finland). He is a leading figure in the interdisciplinary field of econophysics and complex systems. Education: Diplôme d’Habilitation à Diriger des Recherches (2013), Université Pierre et Marie Curie – Paris VI, France (Physics) Ph.D. in Physics (2003), Saha Institute of Nuclear Physics, Jadavpur University, India Post-M.Sc. in Physics (1999), Saha Institute of Nuclear Physics, Jadavpur University, India (Ranked First) M.Sc. in Physics (1998), University of Calcutta, India (Ranked First) B.Sc. in Physics (1996), Scottish Church College, University of Calcutta, India His research interests lie at the intersection of physics, economics, and data science. He is particularly known for pioneering work in econophysics , including the statistical mechanics of money, wealth distribution, agent-based market models, and network-based analysis of financial and social systems. He also works on complex systems , computational finance , statistical physics , and nanosciences , with applications in sensing and imaging. His work often involves modeling socio-economic phenomena using tools from statistical physics. His recent publications span topics such as financial fluctuations, wealth inequality, network analysis of conflicts, order book dynamics, and nanomaterial characterization. These works reflect a strong trend toward interdisciplinary research combining physics, economics, and data analytics, with a focus on real-world applications in finance, inequality, and social systems. Scientific Awards: Indian National Science Academy Young Scientist Medal (2009) He has advised Ph.D. students such as Kiran Sharma and leads the ETC (Experimental-Theoretical-Computational) Lab at JNU, which brings together physicists, computer scientists, and mathematicians. The lab has been involved in international collaborations, including projects funded by the Estonian Ministry of Education and Research and consultancies with TCS Innovation Labs and DONO Consulting. His research has been supported through grants and collaborative projects, reflecting strong industry and global academic engagement.

Lei Tianمشاهده پروفایل

دانشیار

• Computational imaging and sensing
• Computational microscopy
• Imaging in scattering media
• +۵ مورد دیگر

Lei Tian is an Associate Professor in the Department of Electrical and Computer Engineering and the Department of Biomedical Engineering at Boston University's College of Engineering. He leads the Computational Imaging Systems Lab and maintains affiliations with the Neurophotonics Center, Photonics Center, Center for Information & System Engineering, Rafik B. Hariri Institute for Computing, and Nanotechnology Innovation Center. His educational background includes: PhD, Massachusetts Institute of Technology, 2013 MS, Massachusetts Institute of Technology, 2010 Professor Tian's research integrates optics and computation to overcome physical limitations in imaging systems. His work spans computational imaging and sensing, computational microscopy, imaging in scattering media, phase retrieval, and neurophotonics. He develops next-generation imaging systems with applications in biomedical microscopy, neuroscience, semiconductor metrology, and advanced vision applications, emphasizing the joint design of optical components and computational algorithms. His publication record shows a strong progression from fundamental computational imaging techniques to practical applications, with increasing integration of deep learning approaches to solve challenging imaging problems in scattering media and neural environments. His work consistently bridges theoretical advances with real-world applications. Professor Tian has received numerous prestigious awards: Boston University Provost's Scholar-Teacher of the Year Award (2025) Optica Fellow (2025) Early Career Excellence in Research, BU College of Engineering (2021) NSF CAREER Award (2019) Dean's Catalyst Award (2018) The Fumio Okano Best 3D Paper Prize (2018) As an advisor, he has successfully mentored at least 10 PhD students to completion as of mid-2025, with recent graduates including Jeffrey Alido, Jiabei Zhu, Chang Liu, Hao Wang, and Joseph Greene. His research is supported by substantial funding including a $2 million NIH grant for the Computational Miniature Mesoscope (CM2), a $1.75M grant from NIBIB for cancer cell metabolism research, and funding from the Chan Zuckerberg Initiative. His Computational Imaging Systems Lab pioneers innovative imaging techniques that synergistically combine optical hardware with computational algorithms, making significant contributions to computational microscopy, intensity diffraction tomography, neural imaging systems, and deep learning applications in optical imaging for both biomedical and industrial applications.

Chase Broederszمشاهده پروفایل

استاد

• Statistical Physics
• Biological Physics
• Soft Matter Physics
• +۴ مورد دیگر

Prof. Dr. Chase Broedersz is a tenured W2 Professor of Theoretical Physics – Statistical and Biological Physics at Ludwig-Maximilians-Universität München (LMU Munich) since 2015. He also holds a secondary affiliation as Associate Professor at VU Amsterdam since 2020. He is a member of the Young College of the Bavarian Academy of Science since 2017. Education Ph.D. in Theoretical Physics , VU Amsterdam (2011) MSc. in Physics , VU Amsterdam (2007) BSc. in Physics and Astronomy , VU Amsterdam (2005) Research Interests Prof. Broedersz leads a research program at the intersection of statistical physics and biological physics , with a focus on: Soft Matter Physics : mechanics of biopolymer networks, semiflexible filaments, and composite materials Active Matter : non-equilibrium dynamics in living systems, motor-driven networks, and active gels Cell Mechanics : confined cell migration, mechanosensing, and force transmission in tissues Chromosome Organization : bacterial chromosome structure, protein-DNA interactions, and SMC condensins His work combines theoretical modeling , computational simulations , and experimental collaborations to uncover the physical principles governing complex biological systems. Publication Trends Prof. Broedersz has authored over 50 peer-reviewed publications since 2010. His recent work (2019–2025) emphasizes: Cell migration in confined and soft environments, with studies in Nature Physics and PNAS Non-equilibrium dynamics in active biological systems, including broken detailed balance and emergent contractility Machine learning approaches to infer stochastic dynamics in biological data, published in Nature Communications and Physical Review Letters Chromosomal organization in bacteria, combining polymer physics with genomic data Labs and Teams He leads the Statistical and Biological Physics Group at LMU Munich, affiliated with the Arnold Sommerfeld Center for Theoretical Physics (ASC) . The group collaborates closely with experimental teams at LMU, Princeton, and other institutions, focusing on interdisciplinary biophysics research. Teaching Prof. Broedersz has taught advanced courses including: Advanced Statistical Physics Soft Matter Physics Stochastic Processes in Physics and Biology