جست‌وجوی استاد و پژوهشگر

Sujie Parkمشاهده پروفایل

پژوهشگر

• Computational Design
• 3D Printing
• Sustainable Architecture
• +۳ مورد دیگر

Sujie Park is a computational designer from South Korea with a background in architecture and art. She is currently a doctoral researcher at the Institute for Computational Design and Construction (ICD) at the University of Stuttgart, Germany, where she collaborates with the Material Programming Research Group. Her work focuses on the ArchiBioFoam project, exploring multifunctional material systems using bio-based materials and robotic additive manufacturing for architectural applications. Bachelor of Fine Arts (BFA) from Ewha Womans University Master of Architecture (MArch) from Harvard Graduate School of Design (recipient of the Peter Rice Prize) Her research investigates the creative potential of 3D printing in architecture, aiming to redefine its role beyond prototyping to enable sustainable, full-scale construction. She studies how 3D printing can adapt visual, structural, and spatial qualities across architectural scales through material innovation and digital fabrication techniques. Notable projects include the ArchiBioFoam initiative and the thesis work Material Alchemy , which examines the intersection of 3D printing and architectural form. She has worked in architectural offices across New York, Boston, Amsterdam, Copenhagen, and Seoul. Peter Rice Prize (Harvard Graduate School of Design)

Georg Garnweitnerمشاهده پروفایل

استاد

• Nanomaterials Synthesis
• Non-aqueous Nanoparticle Formation
• Solid-State Battery Materials
• +۵ مورد دیگر

Prof. Dr. Georg Garnweitner is a full Professor of Nanomaterials at the Institute for Particle Technology , Faculty of Mechanical Engineering, Technische Universität Braunschweig. He has served as Dean of Studies since 2023, DFG Liaison Lecturer since 2021, and head of the Laboratory for Emerging Nanometrology (LENA) board since 2013. University Professorship in Nanomaterials (2013–present) Junior Professorship in Nanoparticles/Nanocomposites (2007–2013) Research at Max Planck Institute (2005–2006) His research focuses on nanomaterial synthesis , non-aqueous nanoparticle formation , and energy storage materials , particularly for lithium-sulfur batteries. He also explores drug delivery systems using silica aerogels and optofluidic particle analysis . His work combines materials science , surface chemistry , and advanced characterization techniques . Recent publications highlight breakthroughs in solid-state electrolyte design (2023), solvent-free drug loading (2022), and nanoparticle migration dynamics (2020). He contributes to crystal engineering (2021) and population balance modeling (2017) for nanoparticle formation.

• Network Security
• Data Security
• Cryptography
• +۵ مورد دیگر

Prof. Dr. Jörg Schwenk is a Professor and Chair of Network and Data Security at Ruhr-University Bochum's Faculty of Computer Science. He has held this position since 2003 and serves as Deputy Managing Director of the university's Computer Center. From 2007 to 2010, he was Managing Director of the Horst Görtz Institute for IT Security. His office is located at Universitätsstr. 150, 44801 Bochum (Room MC 4/110), with contact via email at joerg.schwenk@rub.de. His research focuses extensively on practical aspects of information security, particularly in: Cryptographic protocol analysis (TLS, SSH, Noise Protocol) Web and browser security vulnerabilities (XS-Leaks, DOM security) Document security flaws in PDF, OOXML, and OpenDocument formats Email encryption weaknesses and authentication mechanisms Network security implementations and powerline communications Recent publications demonstrate a strong emphasis on discovering and mitigating critical vulnerabilities in widely used protocols and file formats. His work frequently involves developing automated analysis tools (e.g., TLS-Anvil, XSinator) and reveals systemic security issues in standards implementations. Research outputs consistently target top-tier security venues (USENIX Security, CCS, NDSS) with findings that directly impact real-world systems. Schwenk leads a research group at the Horst Görtz Institute focusing on network and data security. The group maintains an active publication record in applied cryptography and systems security, frequently collaborating with industry partners to address emergent threats. His team's work on TLS vulnerabilities (ALPACA, Raccoon attacks) and document security (PDF/OOXML signature flaws) has significantly influenced protocol designs and standardization efforts.

• Information Science
• Human-Computer Interaction
• Gamification
• +۷ مورد دیگر

Dion Hoe-Lian Goh is a researcher at Nanyang Technological University, Singapore , with a focus on information science, human-computer interaction, and digital literacy. His work explores emerging technologies like deepfakes and conversational AI , gamification in education, and information behavior in social media platforms. Research trends in his recent publications include deepfake detection strategies , AI-driven educational frameworks , and social dynamics in misinformation . His studies span diverse populations such as Generation Z and senior citizens , emphasizing the role of technology in public perception and information verification. Key subfields of his work include computational thinking education , crowdsourcing , digital nudges , and user experience in gamified systems . While no formal awards are listed, his contributions to journals like J. Assoc. Inf. Sci. Technol. and conferences such as HCI and ICADL highlight his impact in academic circles.

Tobias Neckelمشاهده پروفایل

دانشیار

• Uncertainty Quantification
• Random Differential Equations
• Numerical Algorithms
• +۴ مورد دیگر

Tobias Neckel is an Associate Professor at the Institute for Informatics at the Technical University of Munich (TUM), where he leads research projects and coordinates academic programs. He has been the project team leader of the IGGSE Project ExaNIML since 2018, main coordinator of the Ferienakademie since 2014, and Program Coordinator of the Bavarian Graduate School of Computational Engineering (BGCE) since 2009. Diploma in Technomathematik from TU München (2005) Dr. rer. nat. in Informatics from TU München (2009) Neckel's research focuses on Uncertainty Quantification, Random Differential Equations, and High Performance Computing. His work develops efficient numerical algorithms using hierarchic and adaptive methods such as octrees/spacetrees and sparse grids, with applications in fluid-structure interactions and incompressible fluid flow simulation. His research bridges theoretical mathematics with practical computational science, emphasizing robust and efficient implementations. His recent publications demonstrate a strong trajectory in multi-fidelity modeling, uncertainty quantification, and high-performance computing. Neckel has made significant contributions to scalable hierarchical approximation methods, dynamic resource management in HPC, and the application of machine learning techniques to computational science problems. His work spans diverse application domains including plasma physics, hydrology, and computational engineering. Lehrfonds prize of the TUM (2014) Ernst Otto Fischer prize of the TUM (2011) Promotionspreis des Bunds der Freunde der TU München (2009) Neckel has supervised numerous graduate students and has been actively involved in curriculum development and teaching innovation. His book "Bits and Bugs: A Scientific and Historical Review of Software Failures in Computational Science" (2019) represents a significant contribution to understanding software reliability in scientific computing. He has organized minisymposia at major conferences including SIAM CSE and SIAM UQ, and serves on program committees for various computational science conferences. As coordinator of the Ferienakademie and the BGCE, Neckel plays a central role in advanced computational engineering education in Bavaria. His research group develops software for exascale computing and contributes to the Transregional Collaborative Research Centre 89 on Invasive Computing. Neckel also maintains international collaborations, with research stays at institutions including the Australian National University and Tokyo Institute of Technology.

• Machine Learning
• Optimization
• Federated Learning
• +۸ مورد دیگر

Peter Richtarik is a Professor at the King Abdullah University of Science and Technology (KAUST), specializing in Machine Learning, Optimization, and Federated Learning. He actively teaches courses such as Stochastic Gradient Descent Methods and mentors PhD and MS students like Konstantin Burlachenko, Kai Yi, and Lukang Sun. His research spans distributed optimization, parameter-efficient fine-tuning, and theoretical frameworks for non-convex and non-smooth problems. Recent work includes 2025 contributions to Bernoulli-LoRA (theoretical PEFT) and Gluon (LMO-based optimizers). He co-developed Thanos (block-wise pruning) and BurTorch (CPU-optimized training framework). His publications focus on communication efficiency ( ATA , LoCoDL ), differential privacy ( DP-RBCD ), and stochastic proximal methods. Richtarik received the Charles Broyden Prize for his work on quasi-Newton methods. He frequently presents at workshops like MLSS in Senegal and FLOW seminars.

Beate Paulusمشاهده پروفایل

استاد

• Quantum Chemistry
• Theoretical Chemistry
• Computational Chemistry
• +۸ مورد دیگر

Beate Paulus is a Professor for Theoretical Chemistry at the Freie Universität Berlin , affiliated with the Chemistry and Biochemistry college and the Chemistry department. Her research focuses on advanced quantum chemical methodologies and applications to 2D materials, spintronics, and catalysis. Current affiliation: Freie Universität Berlin Key research areas: Quantum Chemistry, Density Functional Theory, 2D Materials, Spintronics, Electrocatalysis Her work spans computational modeling of electronic structures, magnetic properties, and chemical reactions using Density Functional Theory (DFT) with specialized corrections. She investigates systems like MoS2 , graphene heterostructures , and transition metal complexes , aiming to understand and optimize properties for energy applications, biosensors, and nanoelectronics. Recent publications highlight her contributions to quantum mechanical fluorine tunnelling , spin-selective transport in doped nanoribbons , and surface functionalization strategies for 2D materials. Her group also explores mechanically interlocked molecules and redox-responsive polymers with potential biomedical applications. Beate Paulus leads the Paulus Group , which actively publishes in high-impact journals and collaborates on interdisciplinary projects involving experimental and theoretical approaches.

• Traffic Data Acquisition
• Traffic Data Analysis
• Video-Based Microscopic Traffic Flow Simulation
• +۲ مورد دیگر

Dr. Adrian Fazekas is a Lecturer at the Institute of Highway Engineering, RWTH Aachen University, and collaborates with the Federal Highway Research Institute (BASt). He holds a Dr.-Ing. in Computer Science from RWTH Aachen (2005–2011), specializing in Media Engineering. His professional trajectory includes roles as a Research Assistant at RWTH Aachen and industry experience as a Software Developer at Continental AG. Research interests focus on traffic data acquisition , microscopic traffic flow simulation , and intelligent transportation systems . Key projects include: DROVA: Drone-based traffic analysis for infrastructure optimization ESIMAS: Real-time tunnel safety management Digital Twin Road: Physical-informational mapping of future highways AUTUKAR: Automated tunnel monitoring systems His publications emphasize real-time traffic detection , safety analytics , and data-driven modeling , with recent work exploring thermal-camera nudging systems and weigh-in-motion accuracy. He actively contributes to the Research Association for Roads, Earth and Tunneling (SETAC). No awards or student advising roles are documented.

• Embedded Machine Learning
• Neural Network Hardware Acceleration
• Quantized Neural Networks
• +۳ مورد دیگر

Lukas Einhaus is a Researcher and PhD student in the Embedded Systems department at the University of Duisburg-Essen since April 2020, affiliated with the Intelligent Embedded Systems (IES) research group and contributing to initiatives including Elastic AI and the IoT Garage. His academic background includes: Bachelor of Science from University of Duisburg-Essen, thesis focused on programming abstractions for concurrent embedded systems Master of Science from University of Duisburg-Essen, specializing in distributed and reliable systems with thesis research on quantizing neural networks Einhaus's research centers on designing neural networks for efficient hardware implementation on FPGAs, with primary expertise in quantized or low-precision neural networks that reduce bit depth (typically 1-3 bits) for computations and information flow. This work enables energy-efficient AI solutions for embedded and IoT devices where resource constraints are critical. His publication record from 2021-2025 reveals consistent innovation in FPGA-based neural network optimization, with applications spanning fluid flow estimation, time-series analysis, and real-time stream processing. Core themes include Elastic AI for adaptive systems, precomputation techniques for convolutional layers, and hardware-aware neural architecture design. He previously contributed to the BMBF-funded project "KI-Sprung: LUTNet" (until March 2022), developing energy-efficient AI networks using elementary lookup tables for FPGA deployment. Einhaus actively mentors students through the IoT Garage initiative, supervising practical projects including drink-mixing machines, exoskeletons, and ball-challenge systems.

Jochen Garckeمشاهده پروفایل

استاد

• Numerical Methods in Science and Technology
• Machine Learning
• Sparse Grids
• +۵ مورد دیگر

Prof. Dr. Jochen Garcke is a faculty member at the Institute for Numerical Simulation, University of Bonn, with a dual affiliation at Fraunhofer SCAI's Department of Numerical Data-Based Prediction. His work bridges numerical simulation and machine learning, focusing on high-dimensional problems, sparse grids, and optimal control. Key research themes: Sparse grids, machine learning for simulations, reinforcement learning, uncertainty quantification Teaching includes courses on Numerical Methods in Science and Technology and Scientific Computing , emphasizing practical machine learning applications. Recent publications explore hybrid models combining data-driven and physics-based approaches in automotive engineering, wind turbines, and geoscientific modeling. His group employs adaptive sparse grids, graph algorithms, and spectral methods to tackle challenges in crash simulations, fluctuating renewable energy systems, and turbulent flow analysis. Collaborations span Fraunhofer SCAI and industry 4.0 initiatives.

Danh Le Phuocمشاهده پروفایل

پژوهشگر

• Autonomous Information Systems
• RDF Stream Processing
• Semantic Web
• +۴ مورد دیگر

Danh Le Phuoc is a Principal Computer Scientist at Technical University of Berlin, leading research at the PICOM.AI lab where his team develops autonomous information systems for robotics, autonomous vehicles, and IoT systems through pervasive intelligence in complex networks. With over 70 publications and significant academic impact (6811 citations, H-index 31), he has established himself as a notable researcher in semantic technologies. His educational background isn't explicitly detailed in the provided text, but his research expertise spans multiple domains requiring advanced technical knowledge. Le Phuoc's research focuses on bridging theoretical concepts with practical system implementation, particularly in RDF Stream Processing, Semantic Web technologies, and IoT middleware. His work emphasizes building real-world systems that process linked streams and data in real-time, enabling applications in intelligent transportation systems and connected vehicles. His research trajectory shows consistent innovation from foundational work on semantic mashups (2009) through to advanced stream processing frameworks (2017). His publications reveal strong trends toward processing real-time semantic data streams, with increasing focus on scalability, performance optimization, and integration of IoT systems with knowledge graphs. The progression shows movement from basic semantic web pipes to complex, elastic cloud-based stream processing systems. 22 Awards, Honours, Fellowships and Grants 10+ awards for innovative Semantic Web applications Multiple honors for IoT applications As an obsessive builder, Le Phuoc has developed numerous influential systems including The Graph of Things, CQELS (Continuous Query Evaluation over Linked Streams), Semantic Web Pipes, and Linked Sensor/Stream Middleware. His current focus is on ASAP (Autonomous Semantic Stream Processing), a platform for connected vehicles and intelligent transportation systems. His lab appears to maintain active GitHub repositories for several of these systems, suggesting ongoing development and community engagement.

Michael Vogelمشاهده پروفایل

استاد

• Molecular Dynamics
• Condensed Matter Physics
• Glass Transition
• +۶ مورد دیگر

Prof. Michael Vogel is a Professor at the Institute for Condensed Matter Physics at Darmstadt University of Technology (Technische Universität Darmstadt), where he leads the Molecular Dynamics in Condensed Matter research group. His work focuses on understanding the microscopic structure and dynamics of condensed matter systems and relating these to macroscopic properties. Research Interests Prof. Vogel's research spans several key areas in condensed matter physics and physical chemistry. His group investigates the structure and dynamics of condensed matter—from simple liquids and soft matter to crystalline and amorphous solids. Specific research focuses include: Water Anomalies: Exploring the fundamental understanding of water's anomalies, particularly testing the hypothesis of a transition between two liquid phases in supercooled water. Ion Transport: Studying microscopic mechanisms of ion movement in energy materials, with applications to lithium-ion batteries and fuel cells. Glass Transition: Investigating cooperative and heterogeneous motion processes during the glass transition to contribute to fundamental understanding. Protein Dynamics: Examining the interplay between protein and solvent dynamics, particularly in biological function. Ionic Liquids: Analyzing structural and dynamic heterogeneities in ionic liquids and their relationship to macroscopic properties. Liquids at Interfaces: Understanding how interfaces alter the properties of liquids, especially water, when confined in nanoscopic geometries. Research Methodology Prof. Vogel's group combines modern experimental techniques, particularly nuclear magnetic resonance (NMR) spectroscopy, with computational approaches like molecular dynamics simulations. This dual approach allows for comprehensive characterization of both local molecular motions and long-range transport properties. Their work often involves analyzing systems under confinement, at interfaces, or in supercooled states to reveal fundamental mechanisms that govern material behavior. Scientific Contributions Prof. Vogel has made significant contributions to understanding: The role of dynamic heterogeneities in glass-forming systems Mechanisms of ion transport in solid-state electrolytes The behavior of water in confined geometries and at interfaces The coupling between protein and solvent dynamics Structural and dynamic properties of ionic liquids Research Team and Facilities Prof. Vogel leads an active research group at TU Darmstadt with access to advanced NMR facilities and computational resources. His team regularly publishes in high-impact journals across physics, chemistry, and materials science. The group collaborates with other research institutions and participates in interdisciplinary projects such as the DFG Research Group 1583 on "Hydrogen-bonding liquids in the presence of internal interfaces of different hydroaffinity."

• Human-Computer Interaction
• Privacy Studies
• Social Media
• +۳ مورد دیگر

Andrea Forte is a Professor affiliated with the University of Michigan, with a former position at Drexel University. Her research focuses on Human-Computer Interaction (HCI), Privacy Studies, and Social Media, exploring topics such as privacy expertise, marginalized communities' digital experiences, and collaborative systems. She has published extensively in top venues like CHI, CSCW, and ACM Transactions on Computer-Human Interaction. Her work bridges technical, social, and ethical dimensions of technology, addressing challenges in privacy protection, online anonymity, and the impact of social media on vulnerable populations. She has contributed to understanding how technologies like Wikipedia and social platforms mediate trust, credibility, and activism. Notable projects include studies on user privacy rights in people search websites and the sociotechnical challenges faced by disability activists online. Forte collaborates with interdisciplinary teams, addressing issues such as internet-facilitated harassment of researchers and the design of privacy-enhancing technologies. Her research emphasizes equitable and inclusive approaches to technology, particularly in library and educational contexts.

• Behavioral Ecology
• Animal Behavior
• Social Systems
• +۴ مورد دیگر

Eli D. Strauss is a behavioral ecologist and Postdoctoral Researcher at the Max Planck Institute of Animal Behavior and the University of Konstanz. He will transition to an Assistant Professor position at the Department of Integrative Biology, Michigan State University in late 2025. His research focuses on the evolution of stable social systems, particularly in spotted hyenas, analyzing how individual behaviors and relationships shape group-level dynamics. Strauss employs field experiments, computational techniques, and long-term observational data to study dominance hierarchies, social inequality, and the interplay between individual experiences and collective behaviors. Research Interests : Strauss investigates how societies emerge from individual interactions, emphasizing long-term perspectives. Key themes include dominance hierarchy dynamics, social inheritance, and the ecological drivers of social behavior. His work bridges behavioral ecology with computational methods, addressing questions about social structure stability and evolutionary adaptations. Key Projects : Co-director of the Mara Hyena Project in Kenya, a long-term study on hyena behavior and ecology. Developing methodologies for longitudinal studies of dominance hierarchies, including frameworks for analyzing hierarchy dynamics across timescales. His computational tools (e.g., DynaRankR ) are widely used for dominance inference. Upcoming Initiatives : Establishing a lab at Michigan State University focusing on social behavior and collective ecology. Recruiting graduate students and postdocs to study social systems, computational ecology, and animal behavior.

Enno Mammenمشاهده پروفایل

استاد

• Nonparametric Statistics
• Bootstrap Methods
• Additive Models
• +۶ مورد دیگر

Enno Mammen is a Professor of Mathematical Statistics at Heidelberg University, leading the Institute for Applied Mathematics. His career includes roles as Chair for Mathematical Statistics at Heidelberg (2014–present), Chair for Statistics at the University of Mannheim (2003–2014), and various academic positions since 1986. He holds a PhD (1983) and habilitation (1992) from Heidelberg University. Research interests focus on nonparametric statistics, bootstrap methods, additive models, high-dimensional data, and statistical theory. Key contributions include foundational work on the wild bootstrap, penalized nonparametric estimators, and nonparametric diffusion models. He has authored over 150 papers in top journals like the Annals of Statistics and Biometrika. Current research spans Hawkes processes, neural network statistics, and non-Euclidean data analysis. He has supervised 12 PhD students since 2010, with many progressing to academic roles. Awards include the Heinz Maier Leibnitz Prize (1989) and IMS Fellowship (1998). Active in editorial roles for journals like the Annals of Statistics and Bernoulli. Major funding includes leadership of the DFG-funded Research Training Group 'Statistical Modeling of Complex Systems' (2013–2022) and collaborations with Russian institutions on stochastic differential equations.