جستجوی استاد راهنمای دانشگاهی

• Human Factors
• Ergonomics
• Automated Driving
• +۳ مورد دیگر

André Dietrich serves as a Researcher at the Department of Ergonomics, Technical University of Munich, since March 2015. His work centers on pedestrian-vehicle interactions within automated driving contexts, utilizing advanced simulation methodologies and field studies to enhance urban traffic safety. Education: Diploma in Aerospace Engineering from Technical University of Munich specializing in aircraft propulsion and aerospace engineering Completed diploma thesis "Feasibility Analysis of a Pedestrian Simulator" in December 2014 Research Interests: Dietrich investigates pedestrian crossing behavior in automated urban environments through human factors and ergonomics frameworks. His work pioneers external human-machine interfaces (eHMIs) for vehicle-pedestrian communication, examining kinematic effects, cultural influences, and age-related perception differences. Key methodologies include augmented reality simulations, LiDAR-based field observations, and motion-platform pedestrian simulators to capture behavioral nuances in traffic scenarios. His research directly addresses safety challenges posed by increasing vehicle automation levels in complex urban settings. Publication Trends: Analysis of Dietrich's 12 publications (2016-2022) reveals consistent focus on pedestrian-AV interaction mechanisms. His work demonstrates evolving methodologies from controlled simulator studies toward real-world field validations, with growing emphasis on inclusive eHMI design for diverse user groups. Cross-cultural comparisons and technical innovations in projection-based interfaces represent significant thematic threads across his publication history. Advising and Grants: No student supervision or grant funding details are documented in the provided materials. Labs and Infrastructure: Dietrich operates within TUM's Ergonomics Chair facilities including the Dynamical Mock-Up, Modular Ergonomic Mockup, Static Driving Simulator, and robotics labs. These resources support his research on cabin design, automated driving systems, and human-robot interaction within traffic contexts.

Jose Paolo Talusanمشاهده پروفایل

پژوهشگر

• Smart Transportation Systems
• Cyber-Physical Systems
• Middleware
• +۴ مورد دیگر

Dr. Jose Paolo Talusan is a Research Scientist at the Department of Computer Science and Computer Engineering , Vanderbilt University, specializing in smart transportation systems , distributed computing , and cyber-physical systems . He is affiliated with ScopeLab , a research group focused on smart cyber-physical systems. Education: PhD from Nara Institute of Science and Technology, Japan (2020) Research Interests: His work addresses challenges in urban mobility through middleware architectures, optimization algorithms, and machine learning. Key areas include incident detection in transportation systems, privacy-preserving route planning, and vehicle-to-building charging optimization. Publication Trends: Recent publications focus on real-time transit optimization (2024-2025), leveraging reinforcement learning for heterogeneous agents in vehicle-to-building systems, and privacy-aware route planning in smart cities. His work integrates IoT , edge computing , and graph neural networks to tackle imbalanced data and sparsity issues in transit analytics. Labs & Teams: Actively contributes to ScopeLab at Vanderbilt University, collaborating on interdisciplinary projects with researchers in computer science, electrical engineering, and urban planning.

James Shucksmithمشاهده پروفایل

مدرس ارشد

• Urban Flooding Hydrodynamics
• Water Quality Modeling
• Sustainable Drainage Systems (SuDS)
• +۳ مورد دیگر

Dr James Shucksmith is a Senior Lecturer in Water Engineering at the School of Mechanical, Aerospace and Civil Engineering, University of Sheffield. After completing his undergraduate degree and PhD at the same department, he joined the academic staff in 2010 following a KTP associate role with Yorkshire Water. His research focuses on urban flooding hydrodynamics, water quality modeling, and sustainable drainage systems. Co-director of EPSRC Centre for Doctoral Training in Water Infrastructure and Resilience Current projects: Real Time Abstraction Management (with Severn Trent Water), Centaur FloodInteract Research interests include: Urban flood hydrodynamics and drainage-surface flow interactions Water quality forecasting tools for surface water abstraction Development of local real-time control systems for urban drainage Experimental validation of flood models using PIV measurements His publications (2010-2025) cover topics like contaminant transport in flooded sewer systems, longitudinal dispersion modeling, and real-time control optimization. Recent work focuses on data-driven approaches for Cryptosporidium prediction and E. coli forecasting.

• Propulsor-Hull Interaction
• Waterjet Propulsion
• Ship Hydrodynamics
• +۲ مورد دیگر

Arash Eslamdoost is an Associate Professor at Chalmers University of Technology within the Department of Marine Technology, part of the Mechanics and Maritime Sciences school. His academic career has focused on applied hydrodynamics with particular emphasis on computational fluid dynamics (CFD) to understand flow physics around marine vessels. Dr. Eslamdoost's research interests primarily center on improving marine vessel performance through reducing hull drag and understanding propulsor-hull interactions to minimize energy losses. His work spans five key areas: Propulsor-Hull Interaction , Waterjet Propulsion , Ship Hydrodynamics , Hydrofoil Technology , and Computational Fluid Dynamics . His research approach combines numerical simulations with experimental validation to develop practical engineering solutions for the maritime industry. Analysis of his recent publications reveals a strong focus on energy efficiency in marine propulsion systems, with particular attention to waterjet technology, propeller-hull interactions in various flow conditions, and the effects of waves on ship performance. His work increasingly addresses sustainable marine technologies, including hydrogen-powered vessels and wind-assisted shipping solutions. The research demonstrates progression from fundamental fluid dynamics to applied engineering solutions with practical industry relevance. Dr. Eslamdoost actively collaborates with numerous researchers across Chalmers University and with external partners including the Swedish Transport Administration, Swedish Energy Agency, and European Commission. His projects often involve interdisciplinary teams combining expertise in fluid dynamics, marine engineering, and sustainable energy systems. He leads and participates in multiple research initiatives focused on underwater propulsion systems, efficient rudder design for wind-assisted ships, hydrofoil performance measurement, and electric propulsion systems for foiling craft. His work on the RESHIP project specifically addresses energy-efficient solutions for hydrogen-powered vessels, reflecting the industry's shift toward sustainable maritime transport.

Pierre Nyquistمشاهده پروفایل

دانشیار

• Probability Theory
• Mathematical Statistics
• Applied Mathematics
• +۸ مورد دیگر

Pierre Nyquist is an Associate Professor and docent in the Department of Mathematical Sciences at Chalmers University of Technology and Gothenburg University. His research is sponsored by the Swedish Research Council, the Swedish e-science Research Center (SeRC), and the Wallenberg Artificial Intelligence, Autonomous Systems and Software Program (WASP). He is also an elected member of the Young Academy of Sweden for the period 2024-2029 and has served as a scientific ambassador for EURANDOM since November 2021. Dr. Nyquist's research interests lie at the intersection of probability theory, mathematical statistics, and applied mathematics. His main expertise is in probability theory, with a focus on large deviations theory and stochastic numerical methods. He has a general interest in all aspects of probability theory and much of what is categorized as applied mathematics, particularly questions related to partial differential equations, optimization, and stochastic optimal control. Recently, he has become increasingly interested in the mathematical foundations of complex data analysis and modeling, and the interplay with ideas from physics. His current research interests include large deviations, gradient flows and their generalizations, stochastic numerical methods, statistical learning theory, stochastic processes, and random dynamical systems. Pierre Nyquist has received research funding from several prestigious sources including the Swedish Research Council, the Swedish e-science Research Center (SeRC), and the Wallenberg Artificial Intelligence, Autonomous Systems and Software Program (WASP). His publications demonstrate a consistent focus on theoretical aspects of probability with applications to computational methods and data analysis, showing increasing integration with machine learning techniques in recent years. elected member of the Young Academy of Sweden (2024-2029) scientific ambassador for EURANDOM (since November 2021) Dr. Nyquist is actively involved in mentoring the next generation of researchers. He currently supervises several PhD students including Cinja Arndt (starting Aug. 2025), Niki Wilhemlson (started Aug. 2024), and Viktor Nilsson (started Aug. 2020). He has previously supervised successful PhD students such as Federica Milinanni (Aug. 2020-May 2025) and Carl Ringqvist (Aug 2015-June 2021). He regularly teaches graduate-level courses including "Modern methods of statistical learning" and has supervised numerous MSc theses on topics ranging from deep learning for time-series radar signals to neural network embedding in insurance pricing. His research group is active in both theoretical developments and practical applications, with current projects spanning from mathematical foundations of probability to applications in machine learning and data science. Dr. Nyquist maintains strong international collaborations, as evidenced by his frequent travel for conferences and research visits to institutions such as Brown University and TU Delft.

Aryan Pasikhaniمشاهده پروفایل

مدرس

• Intrusion Detection and Prevention Systems
• Reinforcement Learning
• Machine Learning
• +۹ مورد دیگر

Dr. Aryan Pasikhani is a Lecturer in Cybersecurity at the University of Sheffield , affiliated with the Security of Advanced Systems research group . Holding a PhD from the same institution, his research focuses on Intrusion Detection Systems , Reinforcement Learning , and Quantum Computing applications in security. Specializes in securing Embedded Systems and Internet of Things architectures Active in Adversarial Machine Learning and Privacy-Preserving Technologies Peer-reviewer for IEEE Internet of Things Journal and IEEE Transactions on Industrial Informatics His recent work explores 6LoWPAN security through reinforcement learning and Federated Learning frameworks for privacy-preserving data analysis. Awards include Fellow of the Higher Education Academy . Current grants involve real-time ransomware detection (CipherGrit) and automated threat modeling for AI systems. He supervises four PhD students and teaches Security of Control and Embedded Systems .

Ingmar Glaucheمشاهده پروفایل

استاد

• Hematopoietic Stem Cell Biology
• Clonal Competition Dynamics
• Stem Cell Aging
• +۵ مورد دیگر

Prof. Dr. Ingmar Glauche serves as Deputy Institute Director at the Institute for Medical Informatics and Biometrics within TU Dresden's Medical Faculty . He leads the Theoretical Stem Cell Biology research group and coordinates the institute's teaching activities. As an elected member of TU Dresden's extended senate, he contributes to institutional governance. Academic focus on hematopoietic stem cell biology Expertise in computational modeling Key roles in leukemia research and stem cell transplantation Research interests span clonal competition , stem cell aging , and proliferation-differentiation control , with applications in chronic/acute myeloid leukemia and inherited bone marrow failure . His work combines differential equation models and agent-based simulations to study clonal dynamics , spatial organization , and feedback mechanisms in stem cell systems. Recent publications analyze clonal dominance mechanisms (2025), pediatric CML therapy monitoring (2023), and stem cell aging (2022). Collaborations include DFG , BMBF , and Wilhelm Sander-Stiftung projects like TKI-Stop and MinimaL . Current students include Andrea Gottschalk and Thomas Zerjatke , while former advisees include Christoph Baldow and Helene Hoffmann . 2025: Blood - Myeloid bias mechanisms 2024: BMC Medical Education - Competence analysis 2024: Leukemia - Clonal hematopoiesis 2023: PLOS Digital Health - Data integration 2022: Nature Communications - Clonal reconstruction

Melrose Brownمشاهده پروفایل

دانشیار

• Space Situational Awareness
• Hypersonic Aerodynamics
• Satellite Drag Modeling
• +۶ مورد دیگر

Associate Professor Melrose Brown is a faculty member at UNSW Canberra, School of Engineering and Technology, where he leads numerical space situational awareness research and coordinates the Space Masters program. He holds advanced degrees in Aerospace Engineering and specializes in applying high-fidelity simulations to satellite-environment interactions in Low Earth Orbit (LEO). Research Focus: DSMC/PIC simulations for LEO satellites Orbit propagation and determination Ionospheric drag modeling Atmospheric physics Hypersonic CFD His recent publications analyze thermospheric responses to geomagnetic storms using GITM-OVATION models, ionospheric drag effects, and numerical tools like pdFOAM. Key keywords include Space Weather, Satellite Formation Control, and Computational Fluid Dynamics. He supervises Ph.D. projects related to aerospace engineering and offers scholarships for research in LEO dynamics. His work involves collaborations on CubeSat missions (e.g., M2) and space traffic management systems.

Jari Vepsäläinenمشاهده پروفایل

استادیار

• Mechatronics Design
• Energy Efficient Systems
• Generative Design
• +۷ مورد دیگر

Jari Vepsäläinen is an Assistant Professor at Aalto University's Department of Energy and Mechanical Engineering under the College of Engineering. He serves as Director of the Fluid Power group and specializes in mechatronics design, energy efficiency, and generative design methodologies. Research focuses on physics-based modeling for energy recovery AI/ML applications in electromechanical system design Applications in robotics, heavy machinery, and sustainable transportation His recent publications demonstrate expertise in hybrid systems, fluid power optimization, and AI-driven engineering, with a strong emphasis on electrification and efficiency across automotive, maritime, and industrial domains. Key areas: Mechatronics, Energy Systems, Generative Design Technologies: Digital Twins, IoT, Machine Learning Current projects involve thermal energy systems, electric motor optimization, and advanced control algorithms for mobile machinery.

• Photonics
• Wave Propagation
• Anderson Localization
• +۵ مورد دیگر

Dr. Ara Asatryan is a Lecturer at the University of Technology Sydney (UTS) within the School of Mathematical and Physical Sciences . With an international reputation in theoretical and computational photonics, he focuses on wave propagation in complex photonic structures, including Anderson localization and photonic crystals. His h-index of 28 and over 137 refereed publications underscore his academic impact. Research Interests : Photonics, Anderson localization, wave propagation in disordered media, photonic crystals, and solar energy applications. Teaching : Coordinates and lectures Mathematics and Physics subjects, including Linear Algebra, Differential Equations, and Physical Modeling. Scientific Contributions : He developed semi-analytic tools for wave propagation modeling in photonic clusters and constructed Green’s functions for photonic structures. His funded research includes the grant titled Photon Conductance in Photonic Crystal Devices (2004-2005). Awards : Senior Member of the Optica Society (since 2010). Publications : 137 refereed publications (including 93 journal articles) and 64 conference abstracts.

• Shape Optimization
• Numerical Analysis
• Integro-Partial Differential Equations
• +۳ مورد دیگر

Peter Philip is a Senior Lecturer at the Department of Mathematics, Faculty of Mathematics, Computer Science, and Statistics of Ludwig-Maximilians University Munich. His career since 2008 at LMU includes research in shape optimization and numerical analysis of integro-partial differential equations, with prior roles at the Weierstrass Institute for Applied Analysis and Stochastics (WIAS) and the Institute for Mathematics and its Applications (IMA). He has taught extensively across mathematics disciplines and led software development for crystal growth simulations. Positions: Academic Senior Counselor (2013–present), Academic Counselor (2008–2013), Industrial Postdoctoral Fellow (2004–2006), Research Associate (1997–2004) Education: Habilitation (2012) and Ph.D. (2003) in Mathematics from LMU Munich and Humboldt University Berlin, respectively; Diplom in Mathematics (1997, with excellence) from Free University Berlin Research Interests: His work focuses on Shape optimization via control of integro-partial differential equations Conductive-radiative heat transfer analysis and control Crack propagation modeling using energy functional minimization Numerical simulation of semiconductor crystal growth processes Finite volume methods for anisotropic and complex geometries Optimal control of electromagnetic heating systems Publications: He has published extensively in applied mathematics journals, with key contributions to conductive-radiative heat transfer, sublimation growth of SiC crystals, and crack propagation models. His work bridges theoretical analysis, numerical implementation, and industrial applications. Teaching: Since 2008, he has taught courses such as Numerical Mathematics, Analysis, Linear Algebra, and Axiomatic Set Theory, with a teaching load of 13 hours per week. His lectures include both foundational and advanced topics, supported by freely downloadable lecture notes.

FİKRİ SERDAR GÖKHANمشاهده پروفایل

استاد

• Optics
• Photonics
• Telecommunications
• +۷ مورد دیگر

Prof. Fikri Serdar Gokhan is a faculty member at Rafet Kayış Faculty of Engineering, Department of Electrical and Electronic Engineering. His academic journey spans institutions such as Alanya Aladdin Keykubat University, Harran University, and Hasan Kalyoncu University, where he held progressive roles from Lecturer to Associate Professor before attaining his current rank as Professor. Education: Doctorate and Masters in Electronics Engineering from Uludag University (2010, 2003), Licence in Electrical and Electronics Engineering from Uludag University (1998). Prof. Gokhan's research focuses on Optics and Photonics , particularly Brillouin and Raman fiber amplifiers, quantum tunneling in plasmon sources, and thermal sensing in CMOS-MEMS technology. His work includes analytical modeling, numerical simulations, and applications in optical communication and sensing. His publications highlight expertise in Brillouin amplification, fiber optics, quantum photonics, and terahertz imaging. Notable contributions include innovative guess functions for Raman amplifiers, SBS management in Yb fibers, and electrical-driven plasmon sources on silicon. Administrative roles include Head of Department and Deputy Director of the Institute at Hasan Kalyoncu University. Students mentored include Güneş Yılmaz (PhD) and Arzu Babaev (Masters thesis).

• Microbiology
• Bioinformatics
• Molecular Microbiology
• +۵ مورد دیگر

Magnus Fagerlind is a Senior Lecturer in Bioscience at the School of Bioscience, Department of Biosciences, University of Skövde. He serves as Deputy Head of Division and coordinates advanced-level courses in biosciences. His research spans Microbiology , Bioinformatics , and Systems Biology , focusing on bacterial pathogenesis, biofilm dynamics, and molecular mechanisms. Recent work includes genotyping of Escherichia coli and Klebsiella in sepsis, alongside computational models of quorum sensing in Pseudomonas aeruginosa . Key methodologies: Computational modeling, Next-generation sequencing, Bioinformatics pipelines Applications: Clinical microbiology, Reproductive biology, Educational technology His publications reflect interdisciplinary collaborations in infectious disease research, immunology, and pedagogical innovation. While no explicit awards or advisees are listed, his contributions to research and education at the University of Skövde demonstrate sustained academic engagement.

Jonathan Wedmanمشاهده پروفایل

دانشیار

• Behavioral Science Measurements
• Educational Assessment
• Test Design
• +۳ مورد دیگر

Jonathan Wedman is an Associate Professor at the Department of Applied Educational Sciences within Umeå University , Sweden. His work centers on behavioral science measurements , focusing on test design, large-scale assessments, and legally sound examinations. He holds pedagogical qualifications as both an Excellent teacher and Distinguished university teacher . Research Interests : Educational assessment, psychometrics, validity evidence, equating methods, and AI integration in pedagogy. Scientific Awards : Distinguished university teacher Excellent teacher Recent publications highlight his expertise in test design and validity analysis , including studies on gender-related differential item functioning (2018), AI impacts in humanities education (2023), and frameworks for summative assessment. His work bridges theoretical rigor with practical applications in large-scale testing.

Martin Elsmanمشاهده پروفایل

استاد

• Programming Languages
• Theory of Computation
• Functional Programming
• +۵ مورد دیگر

Martin Elsman is a full-time Professor in the Programming Languages and Theory of Computation section at the Department of Computer Science, University of Copenhagen (DIKU). He serves as head of the PLTC section and head of studies for the BSc education in Computer Science and Economics. Elsman is also an active maintainer of several software tools including the MLKit and SMLtoJs. Joined DIKU in 2012 after 4 years at SimCorp (2008-2012) and previous Associate Professorship at IT University of Copenhagen (2003-2008). Co-developer of Futhark, TAIL APL compiler, SMLtoJs, and SMLserver. Education: M.Sc. in Engineering, Technical University of Denmark Ph.D. in Computer Science, University of Copenhagen (DIKU), supervised by Mads Tofte. Research Interests: Elsman works on programming language design and implementation, with a focus on functional programming, module systems, domain-specific languages for financial contracts, region-based memory management, compilation techniques for parallelism, program optimization, and static type systems. His work spans both theoretical and applied domains, including blockchain-based financial contract execution, web technology, and GPU programming using functional languages. Publication Trends: His recent articles focus on functional programming, array programming, parallelism, and memory management. Topics include region inference, type systems for data-parallelism, program optimization techniques, and domain-specific compilation for financial and quantum computing. He frequently collaborates with Troels Henriksen and others on tools like Futhark and MLKit.