جست‌وجوی استاد و پژوهشگر

Michael D. Ernstمشاهده پروفایل

استاد

• software engineering
• programming languages
• type theory
• +۶ مورد دیگر

Michael D. Ernst is a Professor in the Computer Science & Engineering department at the University of Washington's College of Engineering. His research aims to make software more reliable, more secure, and easier (and more fun!) to produce. Previously, he was a tenured professor at MIT and a researcher at Microsoft Research. Ernst's primary technical interests are in software engineering, programming languages, type theory, security, program analysis, bug prediction, testing, and verification. His research combines strong theoretical foundations with realistic experimentation, with an eye to changing the way that software developers work. He focuses particularly on programmer productivity and developing practical tools that can be integrated into developers' workflows. Analysis of his recent publications (2018-2025) reveals a continued focus on verification techniques, program analysis, and testing methodologies. His work spans from theoretical foundations of type systems to practical applications of NLP for test generation and LLMs for test oracle creation. A consistent theme is developing lightweight, modular approaches that can be practically applied in real-world development environments. Scientific Awards: ACM Fellow (2014) John Backus Award (2009) NSF CAREER Award (2002) ACM SIGSOFT Impact Paper Award (2013) 8 ACM Distinguished Paper Awards across multiple conferences ECOOP 2011 Best Paper Award Microsoft Academic Search ranked #2 in software engineering research (2013) Ernst has received significant research funding including the NSF CAREER Award, supporting his work on program analysis and verification techniques. His research combines theoretical rigor with practical impact, often resulting in tools that are adopted by the software engineering community. He actively collaborates with researchers across institutions and has served in leadership roles for major conferences in programming languages and software engineering. His research group develops practical tools that address real challenges in software development, with a focus on making verification and analysis techniques more accessible to working developers. Current projects include applying machine learning techniques to software engineering problems while maintaining strong theoretical foundations.

Michael Weyrichمشاهده پروفایل

استاد

• Industrial Automation
• Digital Twins
• Large Language Models (LLMs)
• +۷ مورد دیگر

Prof. Michael Weyrich is a faculty member at the Institute of Industrial Automation and Software Engineering (IAS) within the University of Stuttgart , leading the Cluster of Excellence IntCDC . His academic rank is Professor, and he focuses on Industrial Automation , Digital Twins , and Large Language Models (LLMs) for manufacturing and automotive systems. His research explores integrating LLMs into industrial automation for adaptive control, cloud offloading of vehicle functions, and semantic interoperability via Asset Administration Shells . He investigates modular production architectures , connected vehicle systems , and synthetic data generation for autonomous machinery. Recent publications highlight LLM-driven production planning , dynamic sensor calibration , and machine learning for fault detection in electric vehicle powertrains. His work emphasizes real-time data modeling and flexible microservice orchestration .

Ori Lahavمشاهده پروفایل

دانشیار

• Programming Languages
• Verification
• Concurrency
• +۴ مورد دیگر

Ori Lahav is a faculty member in the School of Computer Science at Tel Aviv University. His research is generously supported by an ERC Starting Grant and an ISF Grant. He actively supervises PhD and MSc students, and seeks highly motivated candidates for postdoc, PhD, and MSc positions in programming language theory, concurrency, and formal methods. Dr. Lahav completed his PhD at Tel Aviv University under the supervision of Arnon Avron. In 2014, he was a postdoctoral researcher at Tel Aviv University hosted by Mooly Sagiv. From 2014 to September 2017, he was a postdoctoral researcher at MPI-SWS in Germany hosted by Viktor Vafeiadis and Derek Dreyer. His primary research areas focus on programming languages and verification, with specialization in concurrency and relaxed memory models. He also has significant interests in proof-theory, semantics of non-classical logics, and automated reasoning. His work bridges theoretical foundations with practical applications in programming language design and implementation. Dr. Lahav's publication record shows a consistent trajectory of high-impact research in top-tier conferences including PLDI, POPL, OOPSLA, and ESOP. His recent work (2023-2025) demonstrates continued leadership in memory models, concurrency semantics, and verification techniques. His research spans both theoretical contributions in denotational semantics and practical tools for verification. Best Paper Award DISC 2024 Best Student Paper Award DISC 2024 Distinguished Artifact Award ESOP 2022 Distinguished Paper Award OOPSLA 2021 Kleene Award for Best Student Paper LICS 2013 Dr. Lahav actively advises students including Yoav Ben Shimon, Yotam Dvir, Amir Karniel, and Roy Margalit (PhD students), Yuval Katsman Ezra (MSc student), and has alumni including Ori Saporta (MSc) and Abhishek Kr Singh (postdoc, now Assistant Professor at IIIT Hyderabad). He has organized significant events including VMCAI 2024 and Dagstuhl Seminars on persistent programming. His teaching portfolio includes courses on Shared Memory Concurrency Semantics, Programming Language Foundations, and Software Foundations in Coq.

Stephan Raveمشاهده پروفایل

پژوهشگر

• Numerical Analysis
• Scientific Computing
• Machine Learning
• +۴ مورد دیگر

Dr. Stephan Rave is a Researcher in the Institute for Analysis and Numerics at the University of Münster. He is affiliated with the Applied Mathematics Münster cluster and serves as an Investigator in Mathematics Münster. His work focuses on numerical analysis, scientific computing, and machine learning, with a strong emphasis on model reduction techniques for complex systems. Education : PhD in Mathematics (2012), University of Münster, thesis on finitely summable K-homology. Master's and Bachelor's degrees in Mathematics from the University of Münster. Research Interests : Dr. Rave specializes in model order reduction (MOR) methods, including reduced basis techniques, localized orthogonal decomposition (LOD), and nonlinear approximation strategies. His work addresses challenges in multiscale modeling, domain decomposition, and parametrized partial differential equations. He also develops open-source software tools like pyMOR for MOR and contributes to initiatives like the MaRDI (Mathematical Research Data Initiative) to enhance interoperability in scientific computing. Projects : Key initiatives include the MaRDI project (2021–2026), EXC 2044 Cluster of Excellence (Geometry-based modeling), and MULTIBAT (lithium-ion battery simulation). His research bridges theoretical developments with practical applications in battery modeling, electrochemistry, and computational fluid dynamics. Grants & Awards : Funded by DFG, the German Federal Ministry of Research, and internal university grants, his work addresses strategic areas like sustainable research software and energy storage systems. He leads projects on distributed model reduction and communication-avoiding algorithms. Teaching : Dr. Rave teaches advanced numerical methods courses, including Model Order Reduction, Numerical Methods for PDEs, and Python-based computational labs. He co-organizes seminars and workshops on MOR and scientific software engineering.

• Case-Based Reasoning (CBR)
• Artificial Intelligence
• Multi-Agent Systems
• +۴ مورد دیگر

Dr. Pascal Reuss is a Researcher at the Intelligent Information Systems (IIS) Division within the Institute of Computer Science , University of Hildesheim . His work focuses on Case-Based Reasoning (CBR) systems, Multi-Agent Systems , and Knowledge Management applications. Active in CBR framework development and game-based AI research Teaching Computer Science III (Databases) for winter 2025/26 Participating in university sustainability initiatives like Stadtradeln 2024/25 Reuss contributes to AI education through practical implementations in gaming environments and has developed visualization tools for CBR agent behavior. His research spans multi-agent collaboration , dynamic case bases , and domain-specific language implementations for knowledge maintenance. Notable contributions include: Co-developing the FEATURE-TAK framework for knowledge extraction Designing case factories for distributed CBR systems Implementing finite state machines for tactical game agents Creating CBR-based fitness planning systems His work appears in various CBR and Game Development publications from 2011-2024. The research demonstrates practical applications of CBR in aircraft maintenance diagnostics , training plan generation , and educational technology contexts.

Gerhard Weberمشاهده پروفایل

استاد

• Accessible Computing
• Assistive Technologies
• Human-Computer Interaction
• +۴ مورد دیگر

Prof. Gerhard Weber holds the Chair in Human-Computer Interaction at Technische Universität Dresden, Germany. Previously, he served as Chair for Human-Centered Interfaces at Christian-Albrechts-Universität zu Kiel (2000–2007) and Professor for Operating Systems and Graphical User Interfaces at Harz University of Applied Sciences (1996–2000). His research focuses on accessible computing, assistive technologies, haptics, and multimodal interaction. Key projects include development of tactile charts (SVGPlott), robotic guidance systems (HapticRein), and indoor navigation solutions for visually impaired users. Current work explores voice interfaces for social robots, autism-inclusive technologies, and accessibility maturity models for higher education institutions. Over 70 publications span conferences like CHI, IEEE, and ACM, emphasizing practical applications in assistive tech. Education & Professional Journey: 2007–Present: Chair in Human-Computer Interaction, TU Dresden 2000–2007: Chair for Human-Centered Interfaces, Kiel University 1996–2000: Professor of Operating Systems and GUIs, Harz University Research Interests: Prof. Weber's work bridges theory and practice in accessibility, emphasizing tactile interfaces, inclusive design, and assistive robotics. Recent projects include: Mosaik : Enabling blind users to create and share graphics via audio-tactile tools Cloud4All : Personalized web accessibility solutions Range-IT : Real-time object detection for navigation aids Advising & Grants: Managed €3.2M in EU and national grants (2011–2020) Supervised 12+ graduate projects on assistive tech Labs & Teams: Leads TU Dresden's Human-Computer Interaction Lab, collaborating with industry partners like Siemens and rehabilitation centers to deploy assistive systems in real-world settings.

Peter Hertkornمشاهده پروفایل

استاد

• Model-Driven Software Development
• Domain-Specific Languages
• DevOps Automation
• +۲ مورد دیگر

Prof. Peter Hertkorn is a full professor of Computer Science at Reutlingen University's Faculty of Computer Science, specializing in programming languages and databases. He holds leadership roles including Chair of the Examination Board for Media and Communication Informatics B.Sc. and BAföG Officer for the same program. His research focuses on model-driven software development, domain-specific languages, DevOps automation, interactive learning technologies, and distributed ledger technologies. He co-leads the Software Engineering and User Experience (swuxLAB) and Distributed Ledger Technologies (DLT-LAB) research groups. Education background includes a Diplom-Informatiker (master's equivalent) and Dr.-Ing. (PhD) from University of Stuttgart. Professional experience includes 5 years at T-Systems International GmbH and prior academic roles at University of Stuttgart. His teaching focuses on Software Engineering and Database Systems courses. Publications span interactive learning environments, collaborative innovation systems, and AR-based knowledge spaces. Active in academic service roles and interdisciplinary research collaborations since 2009.

Kai Essigمشاهده پروفایل

استاد

• Human Factors
• Interactive Systems
• Eye Tracking
• +۱۵ مورد دیگر

Prof. Dr. Kai Essig is a Professor of Human Factors and Interactive Systems at the Faculty of Communication and Environment, Rhine-Waal University of Applied Sciences, Kamp-Lintfort, Germany. He has a strong interdisciplinary background combining computer science, cognitive science, and human-computer interaction, with a focus on eye tracking, visual perception, and assistive technologies. Master of Science in Computer Science and Chemistry, Bielefeld University (1998) Ph.D. in Computer Science, Bielefeld University (2007) His research centers on eye tracking, human-computer interaction, usability engineering, visual attention, and cognitive interaction technology . He investigates how movement expertise influences visual perception and how multimodal software can support real-time human actions. His work integrates computer vision, machine learning, and neuroscience to develop intelligent systems that adapt to user behavior. The 15 most recent publications reflect a consistent trend in eye movement analysis, mental representations, brain-machine interfaces, and assistive technologies . These works span domains such as sports psychology, robotics, augmented reality, and cognitive neuroscience, demonstrating a strong interdisciplinary approach. Key themes include gaze-based interaction, automated annotation of visual behavior, and the implementation of smart systems for daily living assistance. Scientific recognition includes: Landmark in the Land of Ideas (2018) – for the ADAMAAS project, awarded by 'Land of Ideas', a joint initiative of the German government and the Federation of German Industries Prof. Essig has been actively involved in research projects such as ADAMAAS (Adaptive and Mobile Action Assistance in Daily Living Activities), which received national recognition. He has collaborated extensively with the Neurocognition and Action-Biomechanics Research Group at Bielefeld University and the Excellence Cluster CITEC. While no formal advising of students is listed, his publications suggest mentorship and collaboration with junior researchers. His lab work is centered on eye-tracking systems, multimodal interaction, and cognitive modeling , particularly within applied environments like smart glasses and assistive technologies.

• Industry 4.0
• Internet of Things (IoT)
• OT/IT Integration
• +۴ مورد دیگر

Prof. Dennis Kolberg serves as Professor of Industrial Engineering at Lübeck University of Applied Sciences, holding dual leadership roles as Head of Industrial Engineering Bachelor/Master programs and Head of the Institute for Entrepreneurship and Business Development (IEBD). His career uniquely bridges academic research and industry implementation, with recent executive experience as Chief Product Officer at DIGIMONDO (2020-2023) and co-founding SPARETECH (2019). M.Sc. Industrial Engineering, University of Bremen (2007-2014) Ph.D. in Industrial Engineering, Technical University of Kaiserslautern (2014-2018) focusing on Industry 4.0 and Lean Management Vocational Training as Industrial Clerk, RK Rose+Krieger (2004-2007) His research pioneers the integration of lean production methodologies with digital technologies , specializing in Industry 4.0 implementation and OT/IT convergence for manufacturing environments. Key contributions include developing reference architectures for cyber-physical production systems and optimizing human-machine interfaces through lean automation principles. Current work emphasizes digital transformation in B2B contexts , particularly for software startups in industrial settings. Publications from 2015-2022 reveal a consistent trajectory from foundational CPS architectures toward applied IoT solutions, with recent focus on digital twins for production optimization. His work consistently bridges theoretical frameworks and practical implementation , demonstrating how lean principles enhance digital transformation outcomes in manufacturing. Kolberg actively supervises bachelor's and master's theses at Lübeck University of Applied Sciences, with students registering via email for thesis topics. His industry background informs practical research directions, though specific grant funding isn't detailed in available sources. As IEBD Director, he drives academic-industry partnerships focused on digital entrepreneurship. Leading the Institute for Entrepreneurship and Business Development, Kolberg oversees initiatives connecting academic research with business development in digital manufacturing. Previously at DFKI's SmartFactory KL, he directed research on changeable cyber-physical production systems, establishing methodologies now applied in his current industry collaborations.

Oliver Karrasمشاهده پروفایل

مدرس

• Data Science
• Artificial Intelligence
• Knowledge Representation
• +۴ مورد دیگر

Oliver Karras is a researcher, data scientist, and lecturer at the Data Science and Digital Libraries research group at TIB – Leibniz Information Centre for Science and Technology. He holds a BSc, MSc, and PhD in Computer Science from Leibniz University Hannover. His research focuses on FAIR scientific knowledge, Open Research Knowledge Graph (ORKG), and national research infrastructure projects like NFDI-4Ing and FAIR-DS. He is a member of the German Informatics Society (GI) and spokesperson of the Requirements Engineering (RE) group, contributing to conferences and journals as a reviewer. Previously, he was a research associate and PhD student in the Software Engineering group at Leibniz University, leading the DFG project ViViReq on video integration in requirements engineering. His research interests include Data Science, AI, Knowledge Representation, Software Engineering, Requirements Engineering, Empirical Research, and Open Science. He has published over 60 papers in these areas, with notable contributions to knowledge graphs, FAIR data, and reproducibility frameworks. His work emphasizes organizing scientific knowledge for accessibility and collaboration across disciplines. He is actively involved in initiatives like the ORKG, promoting sustainable literature reviews and open science practices. His professional contributions extend to tool development, such as OntoAligner for ontology alignment and SciKGTeX for semantic annotation in LaTeX. Oliver Karras collaborates with institutions like Leibniz University, contributing to the NFDI consortium and energy research projects. His expertise bridges technical innovation and academic rigor, addressing challenges in knowledge management and reproducibility. His current roles include advancing TIB’s research infrastructure and fostering interdisciplinary collaboration through knowledge graph applications.

Martin Hoffmannمشاهده پروفایل

پژوهشگر

• Embedded Systems
• Real-Time Systems
• Fault Tolerance
• +۳ مورد دیگر

Dr. Martin Hoffmann is a former research staff member at the Department of Computer Science 4 (Distributed Systems and Operating Systems) at Friedrich-Alexander-University Erlangen-Nuremberg (FAU). He now works at Brose Fahrzeugteile in Bamberg. His research focuses on dependability, fault tolerance, and real-time systems, with emphasis on embedded systems and safety-critical applications. He taught courses such as Echtzeitsysteme (Real-Time Systems) and Verlässliche Echtzeitsysteme (Reliable Real-Time Systems) across multiple semesters. His work includes projects like dOSEK (a dependability-oriented RTOS), DanceOS (fault-tolerant OS design), and CoRed (software-based redundancy for mixed-criticality systems). He also contributed to the I4Copter interdisciplinary quadrocopter project. His research interests span fault-injection frameworks, static kernel analysis, and soft-error mitigation. Notable contributions include Fail* (a versatile fault-injection tool) and dOSEK (RTOS for automotive safety). He has advised multiple students on topics like fault-tolerant garbage collectors and modular OS service frameworks. No scientific awards are explicitly mentioned in the provided text. His work emphasizes interdisciplinary collaboration, with projects bridging embedded systems, robotics, and safety-critical applications.

Sandra Diaz Pierمشاهده پروفایل

پژوهشگر

• Computational Neuroscience
• High Performance Computing
• Machine Learning
• +۳ مورد دیگر

Dr. Sandra Diaz Pier is a Scientific Lead at the Jülich Supercomputing Centre (JSC) within the Jülich Research Centre , Germany. Specializing in computational neuroscience , high performance computing (HPC) , and machine learning , she bridges neuroscience and advanced computational methods through her research. Education: B.Sc. in Electronic Systems Engineering, Mexico M.Sc. in Computer Science (focus: machine learning, quantum computing), Mexico Second M.Sc. in Electrical Engineering, Ontario, Canada Ph.D. in Computer Science, Germany (2021) Her research focuses on modeling and simulating brain dynamics and plasticity at multiple scales, leveraging HPC to accelerate large-scale neural network simulations. She actively contributes to EU projects like the Human Brain Project (HBP) , Virtual Brain Cloud , and EBRAINS 2.0 , emphasizing infrastructure development and educational training. Her work includes open-source tools such as the NEST simulator , The Virtual Brain , and L2L , enabling efficient parameter exploration and multiscale co-simulation frameworks. The 15 most recent publications highlight her interdisciplinary approach, spanning topics from quantum computing in biomolecular simulations to neural plasticity algorithms and cloud-based brain modeling . These articles reflect her expertise in integrating machine learning , multi-scale simulation , and HPC infrastructure for neuroscience challenges, including seizure propagation, Parkinson’s disease progression, and swarm intelligence in spiking networks. She leads technical coordination in projects like EBRAINS and serves as a task leader in the HBP infrastructure work package , while also organizing workshops and hackathons for open-source tools. Her role involves supporting domain scientists through methodological research and workflow optimization for brain simulations.

Ying Wangمشاهده پروفایل

دانشیار

• Dependency management
• Software ecosystem
• Software refactoring
• +۷ مورد دیگر

Dr. Ying Wang is an Associate Professor and doctoral supervisor at the Software College of Northeastern University (China), where she has been working since February 2019. She serves as Assistant Dean at the School of Software and is an active member of several CCF committees including the System Software Committee, Software Engineering Committee, Open Source Development Committee, and Women's Committee. Dr. Wang received her Ph.D. in Software Engineering from Northeastern University in January 2019 under the supervision of Professor Zhiliang Zhu. She completed postdoctoral research at the Hong Kong University of Science and Technology (HKUST) from 2022 to 2023 under Professor Shing-Chi Cheung and was a visiting scholar at Microsoft Research Asia through the StarTrack Program in 2021. Her research focuses on intelligent software development technologies, large AI models, open source software big data analysis, and software supply chain security. She has made significant contributions to the governance of open source software ecosystems across multiple programming languages including Java, C#, Python, Go, JavaScript, Android, and Rust. Her work has led to the development of practical tools like 'League of Legends' for monitoring dependency defects in open source ecosystems, with several technologies commercialized by Huawei and Microsoft. Dr. Wang's recent publications demonstrate her expertise in cross-language dependencies, software component analysis, software refactoring, and the application of large language models in software engineering. Her work spans both theoretical foundations and practical applications, with a strong emphasis on real-world impact through industry collaboration. Among her notable achievements are the ACM SIGSOFT Distinguished Paper Awards at ICSE 2021 and ESEC/FSE 2023, making her the first researcher from Northeastern University to receive this honor. She has also received multiple awards for her doctoral dissertation and prototype implementations. Dr. Wang actively contributes to the academic community as an Associate Editor for IEEE Transactions on Software Engineering and serves on program committees for top conferences including ASE, ICSE, and ESEC/FSE. She mentors a large group of doctoral and master's students, with many alumni securing positions at major technology companies including Huawei, Microsoft, Alibaba, and Tencent.

• Construction Logistics
• Digital Twin Frameworks
• Building Information Modeling (BIM)
• +۴ مورد دیگر

Stephan Kessler is a researcher at the Technical University of Munich , affiliated with the Department of Mechanical Engineering and the Chair of Conveying Technology, Material Handling, and Logistics . His work focuses on construction logistics, digital twins, and IoT integration in building processes. Contact: stephan.kessler@tum.de Key research areas: Digital Twin, BIM, DEM simulations, IoT in construction Collaborates with Prof. Johannes Fottner on construction automation projects His research emphasizes digitalization of construction processes through technologies like RFID, machine learning, and simulation tools. Recent publications address tower crane planning, co-robot integration, and bulk material handling standards. Article trends show consistent focus on construction automation (IoT, digital twins, BIM), material flow optimization (DEM simulations, screw conveyor standards), and equipment lifecycle management (telematics, RFID identification). Kessler contributes to industry-university collaborations through projects like BauFlott (fleet management systems) and TEP (Tower Crane Deployment Planner). His work bridges theoretical research with practical implementations in construction site logistics.

Gefei Zhangمشاهده پروفایل

استاد

• Data Science
• Software Engineering
• Model-Driven Software Development
• +۳ مورد دیگر

Prof. Dr. Gefei Zhang is a Professor of Media Informatics at HTW Berlin. He holds a Master’s and PhD from Ludwig-Maximilians-Universität München (LMU). His research focuses on Data Science and Software Engineering, with expertise in aspect-oriented modeling, UML state machines, and model-driven development. He teaches software and data science courses and previously contributed to the Programming and Software Engineering Group (PST) at LMU, now part of the Software and Computational Systems Lab (SoSy). Research interests include aspect-oriented programming, web engineering, and adaptive systems. He has published extensively on topics like UML state machines, software metrics, and HiLA framework applications. Awards include the Best Paper Award at AOM@MoDELS'09. Office hours are by appointment. His work bridges academic research and industry, with past roles in software development for large-scale web applications. Collaborations and grants are part of his ongoing contributions to computer science education and innovation.