جستجوی استاد راهنمای دانشگاهی

David Andres Figueroa Salvadorمشاهده پروفایل

پژوهشگر

• Human-Robot Interaction
• Machine Learning
• Artificial Intelligence
• +۳ مورد دیگر

David Andres Figueroa Salvador is a Postdoctoral Researcher at the Department of Materials and Production, Faculty of Engineering and Science, Aalborg University, Denmark. His work centers on human-robot interaction and machine learning applications in real-world contexts, especially for elderly care and healthcare technology. He earned his PhD from Osaka University, specializing in human-robot interaction. His educational background provides a strong foundation for his current research in socially assistive robotics. Dr. Figueroa's research interests span Human-Robot Interaction, Machine Learning, Artificial Intelligence, Social Robotics, Healthcare Robotics, and Elderly Care Technology. He investigates how technology can seamlessly integrate into daily life, with a focus on older adults facing cognitive decline, social isolation, and loneliness. His goal is to develop robotic systems that offer emotional support and combat cognitive deterioration through sustained, meaningful interactions. His recent publications (2021-2025) demonstrate a consistent focus on social robotics for elderly care, particularly targeting mild cognitive impairment and social isolation. His work ranges from fundamental machine learning algorithms to practical healthcare applications, including hand hygiene monitoring and conversational AI with character-inspired voices. This interdisciplinary research bridges computer science, psychology, and gerontology. No scientific awards were listed in the available information. Dr. Figueroa serves as a project participant in the Villum Foundation-funded 'Time-Traveling Conversations' project (2024-2026), which explores robots imitating historical figures' speaking styles. While no formal advisees are mentioned, his collaborative publications indicate active teamwork with researchers in Japan and Denmark. He conducts research within Aalborg University's Production Robotics and Automation group, collaborating with an international network of researchers as seen in his publications with institutions in Japan.

Arris Tijsselingمشاهده پروفایل

دانشیار

• Fluid Dynamics
• Computational Fluid Dynamics
• Pipeline Systems
• +۳ مورد دیگر

Arris Tijsseling is an Associate Professor at Eindhoven University of Technology (TU/e), affiliated with the Department of Mathematics and Computer Science. His research focuses on fluid transients, computational fluid dynamics, and multiphase flow modeling with applications in pipeline systems. He has contributed to advanced numerical methods like smoothed particle hydrodynamics (SPH) and fluid-structure interaction (FSI) analysis. Notable work includes Lagrangian particle models for transient pipe flows and studies on manhole cover dynamics. His teaching responsibilities include courses on computational science and calculus. Key research themes involve transient flow analysis in pipelines with moving boundaries, cavitation effects in pumps, and structural responses under fluid-induced loads. His work bridges theoretical fluid dynamics with experimental validation, as seen in large-scale pipeline filling/emptying experiments. Collaborative efforts span international teams, addressing challenges in pipeline safety and computational efficiency. Publications highlight innovations in SPH for multiphase flows, hybrid numerical schemes for transient flows, and historical contributions to fluid mechanics. His research often emphasizes practical engineering applications, such as improving pump models and understanding wavefront behavior in fluid systems.

• Computational Fluid Dynamics
• Numerical Methods
• Multiphase Flow
• +۳ مورد دیگر

Katarina Gustavsson is an Associate Professor at KTH Royal Institute of Technology, affiliated with the Department of Numerical Analysis, Optimization and Systems. She serves as the Head of Studies (Huvudstudierektor) for the Department of Mathematics and teaches courses such as the Basic Course in Numerical Methods (SF1525) and Numerical Methods, Basic Course (SF1547). Her research focuses on computational fluid dynamics, multiphase flow, and boundary treatment techniques in numerical simulations. Her work includes developing numerical methods for rigid fiber suspensions, sedimentation analysis, and contact line dynamics. Key contributions involve high-accuracy boundary treatments for Stokes flow and conservative level set methods for interface dynamics. She has authored over 20 peer-reviewed articles and conference papers since 2000. Dr. Gustavsson’s research interests span fluid-structure interaction, fiber orientation dynamics, and the numerical modeling of complex multiphase systems. Her publications address challenges in Stokes flow simulations, sedimentation processes, and the consolidation of concentrated suspensions.

• Inorganic Chemistry
• DNA Microarray Synthesis
• Surface Chemistry
• +۳ مورد دیگر

Etkin Parlar is a researcher in the Department of Inorganic Chemistry within the Faculty of Chemistry at an unspecified university. Holding a BSc and MSc, Parlar actively contributes to interdisciplinary research at the interface of inorganic chemistry, materials science, and molecular biology. Education: Bachelor of Science (BSc) Master of Science (MSc) Research Interests: Parlar's work centers on Inorganic Chemistry, with a focus on DNA microarray synthesis, surface chemistry, oxidation reactions, nanomaterials, and biosensors. Key investigations involve the use of indium tin oxide and gold substrates for DNA synthesis, aiming to improve oligonucleotide quality and develop novel data storage solutions through two-dimensional barcodes. The research also extends to biological systems, such as the role of bitter taste receptors in gastric acid secretion and zinc homeostasis. Publication Trends: The 2024-2025 publications reveal a trajectory toward innovative applications of DNA technology, including nonaqueous oxidation methods for microarray synthesis and parallel DNA synthesis for data storage. These works bridge chemistry, materials science, and biotechnology, with emphasis on substrate integrity (indium tin oxide/gold) and cross-disciplinary biological implications. Awards: No scientific awards were mentioned in the available information. Collaborations: Parlar engages in extensive cross-disciplinary teamwork, evidenced by co-authorship with experts in molecular biology, nutrition science, and analytical chemistry. The research likely operates within specialized laboratory facilities for surface modification and DNA analysis, though specific team structures remain unspecified.

Logan Wadeمشاهده پروفایل

پژوهشگر ارشد

• Biomechanics
• Human Movement Coordination
• Muscle Physiology
• +۷ مورد دیگر

Logan Wade is a Research Fellow in the Department for Health at the University of Bath, actively contributing to research in biomechanics and human movement science. He holds a PhD in Biomechanics from the University of Queensland and is currently accepting doctoral students. Institution: University of Bath Department: Department for Health Academic Rank: Research Fellow Education: Doctor of Philosophy (PhD) in Biomechanics, University of Queensland, awarded on 29 March 2019. Thesis: 'The influence of intrinsic and structural muscle properties on movement coordination during altered task constraints'. Research Interests: Logan's research centers on human movement coordination, focusing on how intrinsic and structural muscle properties affect movement in both healthy and clinical populations. His current work investigates movement in individuals with ankylosing spondylitis, osteoarthritis, and amputees. He is also involved in interdisciplinary collaborations with computer science to develop marker-less motion capture systems for clinical and sports applications. These systems integrate video, motion capture, and force plate data to improve biomechanical analysis. Publication Trends: His recent publications (2024–2025) reflect a strong focus on clinical biomechanics, sports performance, and technological innovation in movement analysis. Key themes include knee osteoarthritis, pose estimation, exoskeletons, and validation of marker-less systems. His work frequently appears in journals such as Clinical Biomechanics , Scandinavian Journal of Medicine and Science in Sports , and Royal Society Open Science , demonstrating interdisciplinary impact. Scientific Contributions: Contributor to the BioCV Motion Capture Dataset (2024), a synchronized dataset for validating markerless human movement analysis. Researcher on the EPSRC-funded project 'Exploring Immersive Support for People Affected by Phantom Limb Pain' (2020–2021). Supervision and Collaboration: Logan supervises doctoral students and collaborates extensively with researchers in biomechanics, computer science, and clinical rehabilitation. His network includes experts in motion analysis, neuromuscular control, and assistive technologies. He is actively engaged in interdisciplinary research that bridges engineering, health sciences, and computer vision to advance human movement understanding and rehabilitation.

Gerhard Naegeleمشاهده پروفایل

پژوهشگر

• Biological Soft Matter
• Colloidal Systems
• Protein Dynamics
• +۳ مورد دیگر

Prof. Dr. Gerhard Naegele is a senior researcher at the Institute for Biological Information Processes (IBI) within the Research Center Jülich GmbH . His primary role is in the Biomacromolecular Systems and Processes (IBI-4) department, focusing on theoretical and computational studies of biological soft matter. His research emphasizes colloidal systems, protein dynamics, and phase behavior in quasi-two-dimensional environments. Key research areas include: Structure and dynamics of charged colloids, microgels, and protein solutions Competitive interactions in dispersions and their impact on clustering and phase transitions Modeling ultrafiltration processes and membrane technologies Computational methods such as mode-coupling theory and multiparticle collision dynamics His work bridges theoretical physics, chemistry, and biophysics, with applications in biomaterials, drug delivery, and industrial filtration. Recent studies explore stimuli-responsive microgels and the rheological properties of soft matter systems. Notable contributions include: Development of advanced simulation frameworks for complex fluids Analysis of cross-flow filtration efficiency under varying conditions Experimental-theoretical collaborations on protein aggregation and colloidal stability His laboratory is part of the broader Helmholtz Association, emphasizing interdisciplinary research in energy, health, and materials science.

Edwin Flikkemaمشاهده پروفایل

مدرس

• Theoretical Chemistry
• Computational Modelling
• Oxide Systems
• +۵ مورد دیگر

Dr Edwin Flikkema is a Lecturer in the Department of Physics at Aberystwyth University. His research focuses on theoretical chemistry and computational modeling of oxide systems, particularly silica clusters and hydroxylated structures. He employs methods like global optimization, molecular dynamics, and Monte Carlo simulations. His work includes determining optimal geometrical configurations of nanoscale silica clusters using Density Functional Theory, with recent interests in two-dimensional foams. Education: BSc and PhD in Theoretical Physics and Polymer Simulation from the University of Groningen (Netherlands). Postdoctoral research includes Delft University of Technology (silica clusters), Cambridge University (Marie Curie Fellowship on energy landscapes with Prof. David Wales), and a brief stint at the University of Barcelona. Joined Aberystwyth as an RCUK fellow in 2008, becoming a lecturer in 2012. Research Interests: Energy landscapes, computational materials science, nanocluster structures, hydroxylation effects, and foam modeling. His work bridges theoretical physics and applied chemistry, with contributions to understanding atomic configurations in confined systems. Key Achievements: Over 30 peer-reviewed publications, including studies on silicate oligomer interconversion and minimal perimeter partitioning. Active in interdisciplinary collaborations, combining computational methods with visualization techniques for material behavior analysis.

Dijana Petrovskaمشاهده پروفایل

مدرس

• Biometrics
• Speech Processing
• Computer Vision
• +۳ مورد دیگر

Dijana Petrovska is a Lecturer at Telecom SudParis, part of the Université Paris-Saclay. Her work focuses on biometric systems, medical diagnostics, and privacy-preserving technologies. She has contributed to projects like the EMPATHIC Virtual Coach, aimed at improving elderly health through AI-driven virtual assistants. Her research interests include facial recognition, speech processing, and cryptographic key regeneration using biometrics. Notably, she has pioneered methodologies for early-stage Parkinson's disease detection via facial action units and voice analysis. She also explores secure authentication systems combining biometrics with cryptography, emphasizing privacy preservation. Publications span over two decades, with recent work emphasizing cross-disciplinary applications of AI in healthcare and security. While no specific academic awards are listed, her impactful contributions to the field of biometric and medical AI are evident through her prolific publication record and active project leadership. Her involvement in collaborative projects like SpeechXRays and EMPATHIC demonstrates a commitment to bridging technical innovation with real-world societal needs. Though no student advisees are listed, her work likely impacts both academic and industry research ecosystems.

• Additive Manufacturing
• Structural Health Monitoring
• Laser Directed Energy Deposition
• +۴ مورد دیگر

Zoé Jardon is an Applied Mechanics postdoctoral researcher at Vrije Universiteit Brussel (VUB), working within the Applied Mechanics Acoustics & Vibration Research Group. Her research focuses on additive manufacturing processes, particularly laser-based directed energy deposition techniques, with expertise spanning structural health monitoring, residual stress analysis, and crack mitigation in additively manufactured components. Dr. Jardon completed her PhD at VUB, for which she received the prestigious Belgian National Committee for Theoretical and Applied Mechanics (NCTAM) Best PhD Thesis Award in 2022 (awarded March 2023) and VUB's Doctoral Derby in 2023. Her doctoral work centered on structural health monitoring systems, building upon two Master's theses she completed at VUB in 2018: one on crack localization verification and another on turbulent noise production in duct systems. Her research program demonstrates exceptional depth in advanced manufacturing technologies, with particular emphasis on thermal management and structural integrity of additively manufactured components. Dr. Jardon's work bridges theoretical mechanics with practical industrial applications, addressing critical challenges in laser-based directed energy deposition processes including powder-gas flow dynamics, residual stress control, and real-time monitoring systems. Her fingerprint analysis reveals strong expertise in Structural Health Monitoring (100%), 3D Printing (55%), Powder Processing (48%), and Laser Materials Processing (47%). Dr. Jardon's publication record shows consistent growth and increasing impact, with 31 research outputs spanning from 2017 to 2025. Her recent work demonstrates a clear trajectory toward developing intelligent manufacturing systems that incorporate in-process monitoring and real-time control to enhance component quality and reliability, moving beyond traditional post-process inspection methods. Her notable achievements include: Belgian National Committee for Theoretical and Applied Mechanics (NCTAM) Best PhD Thesis Award 2022 (awarded March 2023) VUB's Doctoral Derby 2023 Physical understanding of propagating waves through eSHM - system for crack localization (October 10, 2019) As principal investigator for the FWOTM1172 project "Thermal history and Residual Stress Control and Mitigation for Hybrid Additive Manufacturing Techniques" (2023-2026), Dr. Jardon leads fundamental research addressing residual stresses in manufacturing processes. She actively contributes to the academic community through conference presentations and workshop organization, recently chairing the VUB Additive Manufacturing Workshop in September 2024. Her collaborative research network includes strong partnerships with colleagues at VUB and beyond, focusing on advancing additive manufacturing technologies for industrial applications. Working within VUB's Applied Mechanics Acoustics & Vibration Research Group, Dr. Jardon contributes to the group's mission of developing innovative solutions for structural analysis and advanced manufacturing challenges. Her leadership in organizing research events and presenting at international conferences demonstrates her growing influence in the additive manufacturing research community.

Sonja Barkhofenمشاهده پروفایل

استاد پژوهش

• Quantum Optics
• Quantum Information
• Quantum Computing
• +۵ مورد دیگر

PD Dr. Sonja Barkhofen is a Research Professor at the University of Paderborn’s Institute for Photonic Quantum Systems (PhoQS). She holds a Privatdozentin title, reflecting her advanced academic standing. Her primary affiliation is the Institute for Photonic Quantum Systems , where she leads research in quantum photonics and related fields. Her research focuses on topological quantum systems , quantum walks , entanglement generation , and photonic quantum technologies . Her work bridges theoretical concepts like zeta function analysis in hyperbolic systems with experimental realizations in quantum optics. Recent breakthroughs include scalable multiphoton entanglement generation and experimental observation of topological quantum criticality. Teaching activities include the course Quantenelektronik (Quantum Electronics), emphasizing practical applications of quantum principles in photonics. Collaborators such as C. Silberhorn, J. Sperling, and A. Altland frequently appear in her publications, reflecting strong interdisciplinary partnerships. Her publications (2021–2024) span Physical Review Research , Communications in Mathematical Physics , and Physik in unserer Zeit . While no awards are explicitly listed, her prolific output and high-impact journals suggest recognition in her field. Active labs/groups include the Hybrid Quantum Photonic Devices group and involvement in academic governance as an Academic Councillor.

Benjamin Hinrichsمشاهده پروفایل

پژوهشگر

• Spectral Analysis
• Quantum Field Theory
• Mathematical Physics
• +۵ مورد دیگر

Benjamin Hinrichs is a Junior Research Group Leader and Academic Councillor at the University of Paderborn's Faculty of Mathematics and Computer Science, leading the Mathematical Physics of Complex Quantum Systems group within the Institute for Photonic Quantum Systems (PhoQS). He holds a PhD in Mathematics from Friedrich Schiller University Jena (2022), where he also earned his BSc and MSc in Physics. His research focuses on mathematical aspects of quantum physics, employing methods from functional analysis (spectral theory, operator theory) and stochastic analysis. Key interests include spectral analysis of quantum field theories, effective limits of many-body systems, Feynman-Kac path integral techniques, and dynamical properties of quantum systems. Teaching responsibilities include organizing the master's program 'Mathematische Physik' at Paderborn and courses such as Functional Analysis and Mathematical Quantum Mechanics . He advises students on thesis topics in mathematical physics and contributes to outreach programs like Studieren vor dem Abi for prospective students. His recent publications explore renormalization in quantum models, Lieb-Robinson bounds for fermionic systems, and critical phenomena in spin-boson models. He actively engages in academic activities, including international conferences and seminars, and collaborates with researchers globally. Hinrichs' work bridges pure mathematics and theoretical physics, addressing foundational questions in quantum field theory and many-body systems with rigorous analytical methods.

• Analytical Chemistry
• Mass Spectrometry
• Liquid Chromatography
• +۵ مورد دیگر

Sabrina Cramer MSc is a researcher at the Institute of Analytical Chemistry, Department of Natural Sciences and Sustainable Resources, University of Natural Resources and Life Sciences, Vienna (BOKU). She is actively engaged in developing advanced analytical platforms for bioprocess monitoring, particularly in microperfusion fermentation systems. Her research focuses on analytical chemistry , with an emphasis on mass spectrometry , liquid chromatography , and high-throughput screening . Her work integrates 2D-LC-MS/MS and valve-based sample handling for real-time monitoring of biological processes, contributing to advancements in biopharmaceutical process development and industrial biotechnology. The recent publications and conference presentations demonstrate a consistent trend in developing integrated analytical platforms for online monitoring of complex fermentation systems. Her work bridges analytical instrumentation and bioprocess engineering, enabling more efficient and data-rich biomanufacturing workflows. Scientific Contributions: Active participant in research projects on high-throughput acquisition methods and informatics workflows. Presented at major international conferences including ASMS and European Summit of Industrial Biotechnology. Collaborative Research & Grants: She contributes to self-financed and scientifically driven projects at BOKU, collaborating with leading researchers such as Tim Causon and Diethard Mattanovich. While no formal grants are listed, her involvement in project execution indicates active engagement in funded research environments. Laboratory & Team Affiliation: Based at the Institute of Analytical Chemistry (Muthgasse 18, Vienna), she is part of a research team focused on cutting-edge analytical methodologies for life sciences and biotechnology applications.

• Statistical Mechanics
• Ising Model
• Probability Theory
• +۳ مورد دیگر

Sébastien Ott is a Lecturer in the Department of Mathematics at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with both the SB-SMA-SMA-ENS and SB-MATH-MATH-GE units. He contributes to teaching courses such as Probability and Statistics and Large Deviations , focusing on mathematical foundations of statistical physics. Research interests centered on Statistical Mechanics and Probability Theory , particularly in systems like the Ising and Potts models. His work investigates critical phenomena, correlation decay, interface behavior, and large deviation principles. Articles often address topics such as Ornstein-Zernike asymptotics, phase transitions, and spatial mixing properties. His publications reveal a focus on Ising/Potts model phase transitions Large deviations and fluctuation regimes Surface localization/delocalization Renormalization group applications Correlation length analyticity with connections to mathematical physics and percolation theory.

• Materials Science
• Nanotechnology
• 2D Materials
• +۵ مورد دیگر

Didem Dede is a researcher at the École polytechnique fédérale de Lausanne (EPFL), affiliated with the School of Engineering and the Institute of Materials, specifically within the Laboratory of Molecular Simulation and Catalysis (LMSC). Her work focuses on the synthesis, characterization, and application of two-dimensional materials for advanced technological applications. Research Interests: Dr. Dede's research spans materials science and nanotechnology, with a strong emphasis on 2D materials such as transition metal dichalcogenides, black phosphorus, and hexagonal boron nitride. Her work integrates experimental synthesis with atomic-scale characterization and computational modeling to explore electronic, optical, and catalytic properties. Her investigations into strain engineering, defect dynamics, phase transitions, and heterostructure interfaces contribute to fundamental understanding and practical development in nanoelectronics, energy conversion, and quantum materials. Publication Trends: Her recent publications (2019–2024) reveal a consistent focus on the electronic and structural properties of 2D semiconductors. Themes include carrier mobility modulation, excitonic behavior, interfacial engineering, and scalable synthesis methods. The work is frequently published in high-impact journals such as Nano Letters and ACS Applied Nano Materials , reflecting strong contributions to the nanomaterials community. Scientific Funding: Her research has been supported by major funding bodies, including: Swiss National Science Foundation NCCR QSIT (National Centre of Competence in Research Quantum Science and Technology) CIME (Interdisciplinary Center for Electron Microscopy) EPSRC European Cooperation in Science and Technology Advising and Collaboration: While formal advisees are not listed, her co-authorship on a doctoral thesis and frequent collaboration with leading scientists such as Anna Fontcuberta i Morral and Nicholas Morgan suggests active mentorship and integration within EPFL’s research ecosystem. She contributes to collaborative projects involving advanced microscopy, quantum materials, and energy applications. Laboratories and Facilities: Dr. Dede operates within the LMSC at EPFL, leveraging state-of-the-art facilities such as CIME-GE for electron microscopy and materials characterization. Her access to cleanroom environments and computational resources enables a multidisciplinary approach combining synthesis, experimentation, and simulation.

• Machine Learning
• Optimization
• Deep Learning Theory
• +۷ مورد دیگر

Prof. Dr. Aurelien Lucchi is an Assistant Professor in the Department of Mathematics and Computer Science at the University of Basel, Faculty of Science. His research group focuses on the intersection of optimization and machine learning, particularly in advancing theoretical understanding and algorithmic design for deep learning systems. His research interests include: Stochastic and non-convex optimization Deep learning theory and generalization Kernel methods and spectral analysis Transformer architectures and training dynamics Batch Normalization and initialization effects Modeling optimization via stochastic differential equations (SDEs) The recent publications (2023–2025) highlight a strong focus on theoretical machine learning, especially in characterizing optimization landscapes, generalization in kernel methods, and the role of noise and adaptive methods in training. There is a clear trend toward using advanced mathematical tools—such as random matrix theory, SDEs, and curvature analysis—to explain phenomena in deep learning. His group actively publishes in top venues including NeurIPS, ICML, ICLR, and AISTATS. Scientific awards and recognitions include: SNF Consolidator Grant (1.7M CHF) Prof. Lucchi leads an active research group with postdoctoral fellows and ongoing projects, including work on quantum machine learning and noise-adaptive optimization. He has secured competitive research funding and mentors early-career researchers. His group has received recent paper acceptances at ICLR 2025, AISTATS 2025 (oral), and NeurIPS 2024, indicating strong momentum in theoretical and algorithmic machine learning. He previously held a scientific research position at ETH Zurich (2014–2021) and earned his PhD from EPFL. The group is currently involved in two major ongoing projects: Designing and Training Hybrid Hierarchical Quantum Neural Networks with Quantum Advantage Noise-Adaptive Optimization Methods and their Robustness Properties