جستجوی استاد راهنمای دانشگاهی

• Contemporary Art
• Installation Art
• Sculpture
• +۴ مورد دیگر

Michael Stevenson is a New Zealand-born artist and educator based in Berlin. Since 2011, he has served as Professor of Sculpture at the Academy of Fine Arts Nuremberg , where his work bridges art, philosophy, and institutional critique. His practice interrogates systems of power, philanthropy, and knowledge production through installations that reimagine bureaucratic and educational frameworks as speculative artifacts. BFA, Elam School of Fine Arts (1986) Lives/works in Berlin (since 2000) Research interests span contemporary art practices , installation theory , and critical engagement with economic systems . Recent projects like Mind’s Eye (2024) and Disproof Does Not Equal Disbelief (2021) employ soft furnishings and telethon motifs to critique philanthropy’s paradoxes. His Serene Velocity series (2017–2023) merges theological and tech pedagogy, inspired by John Wimber’s healing clinics and Peter Thiel’s Silicon Valley ideologies. Scientific awards include the Berlin Senate’s working scholarship (2005) and Art Center Pasadena scholarship (2001). Key publications such as Animal Spirits (2013) and This is the Trekka (2003) reflect his interdisciplinary approach. Collaborations with galleries like Michael Lett (Auckland) and KW Berlin showcase his global institutional presence.

Shengcheng Yuمشاهده پروفایل

پژوهشگر

• Software Testing
• GUI Testing
• Mobile App Testing
• +۵ مورد دیگر

Dr. Shengcheng Yu is a Postdoctoral Researcher at the TUM School of Computation, Information and Technology (CIT) of the Technical University of Munich (TUM) , affiliated with the Chair of Software Engineering & AI . He earned his bachelor's and Ph.D. from Nanjing University (NJU) in 2020 and 2024, respectively. Research Focus: His work bridges Software Testing with Artificial Intelligence , concentrating on GUI Testing , Mobile App Testing , Crowdsourced Testing , and GUI Automation . His methodologies integrate Image Recognition , Reinforcement Learning , and Large Language Models (LLMs) to enhance automated testing frameworks. Publications Trends: His recent studies (2023-2024) emphasize AI-driven testing tools , including vision-based GUI testing , LLM-based test script generation , and deep image-text fusion for crowdsourced test reports . Earlier work (2021) established foundations in cross-platform testing and screenshot understanding. Team Affiliation: Collaborates with Prof. Dr. Chunyang Chen and researchers such as Lukas Roschel , Wenchao Gu , and Yanqi Su .

• Automotive Engineering
• Automated Driving Systems
• Vehicle Dynamics
• +۵ مورد دیگر

Prof. Dr. Hermann Winner is a full Professor and Head of the Institute of Automotive Engineering (FZD) at Technische Universität Darmstadt since 2002. He previously held leadership roles in predevelopment and series development at Robert Bosch GmbH (1987–2001) and served on international standards committees like ISO/TC204/WG14. Education : Diplomphysicist (1981), Westfälische Wilhelms-Universität Münster Doctorate (1987), Westfälische Wilhelms-Universität Münster (Topic: Dynamics of domain walls in metal ferromagnetic materials) Research Interests : His work focuses on automated driving systems , automotive sensor modeling , and safety validation methodologies . Key contributions include modular safety frameworks (S2I2), behavior-semantic scenery descriptions for autonomous vehicle development, and advanced driver assistance systems (PRORETA 5). He has pioneered research on lidar sensor simulation, brake wear particle emissions, and motorcycle dynamics safety. Article Trends : Recent publications (2022–2024) emphasize automated urban driving safety , semantic scenario modeling , and sensor-based localization . Earlier works (2012–2021) established foundational concepts in fail-operational architectures , collision criticality metrics , and automotive system decomposition . Scientific Awards : IEEE-ITS Institutional Award (2012) for leadership in automated driving research Labs & Projects : He leads the Institute of Automotive Engineering (FZD) at TU Darmstadt and has been integral to projects like UNICARagil (disruptive vehicle architectures), PRORETA series (collision avoidance systems), and collaborations with institutions such as the Daimler und Benz Stiftung and the Bundesanstalt für Straßenwesen.

Gunnar Friegeمشاهده پروفایل

استاد

• Physics Education
• Digital Teaching and Learning
• Science Communication
• +۸ مورد دیگر

Prof. Dr. Gunnar Friege is a Professor of Physics Education at the Institute for Mathematics and Physics Education, Faculty of Mathematics and Physics at Leibniz University Hannover. He serves as the head of the Department of Physics Education and is actively involved in the Faculty Council. His office is located in Building 1109, Room 105 at Welfengarten 1A, 30167 Hanover, with office hours on Wednesdays from 9:00-10:00 during the lecture period. Prof. Friege's research spans multiple areas of physics education with a strong emphasis on innovative teaching methods. His work focuses on digital teaching and learning, inquiry-based physics education, and the integration of technology in physics instruction. He has developed numerous projects exploring productive failure approaches in physics learning, smart experiments, and the use of eyetracking technology to understand student engagement with physics concepts. His research also extends to science communication, particularly through physics competitions and outreach activities. Analysis of Prof. Friege's recent publications reveals a strong trend toward inquiry-based learning approaches, formative assessment techniques, and the integration of digital technologies in physics education. His work frequently addresses practical classroom applications of theoretical educational concepts, with many publications providing concrete teaching materials and activities for specific physics topics ranging from buoyancy and thermodynamics to quantum physics and environmental science. The interdisciplinary nature of his research is evident in publications connecting physics education with environmental issues, acoustics, and AI applications. Prof. Friege has been deeply involved in physics competitions throughout his career, participating in the International Physics Olympiad (IPhO) since 1996 in various capacities including as head of the German delegation. He has also been involved with the European Physics Olympiad (EuPhO) since 2017, the Federal Environment Competition (BUW) since 2004, and has created school-level competitions like inventor tournaments and MINT-Fights. His work with the World Federation of Physics Competitions (WFPhC) included serving as Treasurer and Vice President from 2002-2016. As a supervisor, Prof. Friege leads multiple research projects with doctoral students and collaborators including Muriel Schaber, Sophia Siegmann, Julia Hiniborch, and others. His current projects include SoMeCliCs (on social media and climate change education), Productive Failure in physics teaching, Smart Experiments, Eyetracking studies, MasterClasses in quantum physics, and the LernMINT research training group focusing on data-based teaching in STEM subjects. He also directs the Physics Didactics Working Group which investigates subject-specific media competence of prospective teachers and develops digital teaching scenarios.

Ondrej Vaculinمشاهده پروفایل

استاد

• Passive Vehicle Safety
• Automated Driving
• Vehicle Dynamics
• +۳ مورد دیگر

Prof. Ondrej Vaculin, Ph.D., is a Professor at Technische Hochschule Ingolstadt (THI), specializing in passive vehicle safety, mechatronic systems, and automated driving. He joined THI in 2018 and previously held roles at TÜV SÜD Prague (2008–2018) as Vice President for Safety and Security in Automotive, and as a researcher at Czech Technical University (2005–2008) and DLR Oberpfaffenhofen (2000–2005). His research focuses on enhancing vehicle safety through advanced simulation, sensor integration, and machine learning applications. Education: Ph.D. in Mechanics of Solids, Deformable Bodies and Continua from Czech Technical University in Prague (2001), and a degree in Technical Cybernetics from the Faculty of Electrical Engineering at the same university (1991). His work bridges theoretical research and practical implementation, addressing challenges in automated driving systems, crash simulation, and human body diversity in safety design. Research interests include passive safety systems, autonomous vehicle dynamics, and infrastructure integration for safety enhancements. Recent publications emphasize collaborative smart infrastructure, sensor fusion for free space detection, and machine learning in crash detection. He actively contributes to FISITA, serving as a Council Delegate and member of technical committees. Awards/memberships: Active in FISITA, holding leadership roles in technical committees. No explicit awards listed, though his contributions to automotive safety standards are notable. Grants and advising: While no specific grants or students are detailed, his extensive industry and academic collaborations (e.g., IN2Lab testing field projects) highlight his role in applied research and development.

• Materials Science
• Corrosion Engineering
• Electrochemistry
• +۵ مورد دیگر

Prof. Robert Meißner is a Professor at the Department of Surface Physics and Technology at TUHH. His research focuses on molecular simulation techniques applied to corrosion processes, energy storage systems, and nanomaterials. He develops computational tools like ELECTRODE and i-PI for electrochemical and advanced molecular dynamics simulations. His work addresses challenges in magnesium battery performance, structural health monitoring of composite materials, and interfacial phenomena in nanoscale systems. Education details are not explicitly provided in the text, but his professional trajectory reflects extensive academic and industrial experience in materials science. Research interests span from fundamental studies (e.g., water imbibition in nanopores, magnetite oxidation dynamics) to applied innovations (e.g., corrosion protection via layered double hydroxides, data-driven electrolyte design). His recent publications highlight trends in data-driven materials discovery, structural health monitoring via vibro-acoustic methods, and computational prediction of corrosion inhibitors. He collaborates on projects involving graphene-based supercapacitors, epoxy resin curing dynamics, and peptide-surface interactions. Advising and grants: While student names are not listed, his research group actively explores corrosion engineering, battery technology, and nanomaterials. Projects include EU-funded initiatives and industry partnerships. Technical expertise includes ATR-FTIR spectroscopy, molecular dynamics, and machine learning for sparse data scenarios. He leads teams focused on surface science and energy storage, maintaining lab facilities for in situ electrochemical analysis and advanced computational modeling. His work bridges theoretical insights with practical applications in materials durability and energy systems.

• Automotive Systems Engineering
• Generative AI
• Model-Based Engineering
• +۳ مورد دیگر

Fengjunjie Pan is a PhD student and research assistant at the Chair of Robotics, Artificial Intelligence and Embedded Systems at the Technical University of Munich since 2021. He holds an M.Sc. in Electrical Engineering from TU Berlin (2019) and a B.Eng. in Electrical Engineering from Hamburg University of Applied Sciences. His research focuses on automotive systems engineering and generative AI applications in model-based engineering. His publications (2022-2025) demonstrate expertise in: LLM integration for automotive software development Containerized architectures for autonomous driving Virtualization technologies in vehicular systems Constraint generation and model transformation He supervises multiple Master's and Bachelor's theses on generative AI applications and privacy-enhancing technologies in automotive contexts, working alongside Prof. Alois Knoll's team.

Wolfgang Lippmannمشاهده پروفایل

استاد

• Nuclear Energy Technology
• Hydrogen Systems
• Laser Joining of Ceramics
• +۵ مورد دیگر

Prof. Dr. Wolfgang Lippmann is a Senior Scientist at the Institute of Process Engineering and Environmental Technology, Chair of Hydrogen and Nuclear Energy at Technical University of Dresden. He has maintained continuous affiliation with TU Dresden since 1974, progressing from student to professorial status, with his current role beginning in 2021 after decades as Scientific Staff member. From 2017-2020, he served as Substitute Chair for Prof. Antonio Hurtado during Hurtado's tenure as Vice-Rector for University Development. His academic journey includes: 1974-1978: Studies of energy technology at Technical University of Dresden 1978-1983: Scientific assistant at Chair of Nuclear Energy Technology 1984: PhD on reactor containment stress analysis during cooling loss scenarios 1989: Post-doctoral thesis on pressurized-water reactor containment stress Lippmann's research bridges nuclear engineering with hydrogen technologies through innovative laser-based applications. His work spans reactor safety analysis, high-temperature ceramic materials, and nuclear-hydrogen system integration. He has pioneered laser joining techniques for silicon carbide ceramics in nuclear applications, developed laser decontamination systems for nuclear decommissioning, and conducted safety analyses of hydrogen systems coupled with nuclear power plants. His research integrates fundamental materials science with practical engineering solutions for next-generation energy systems. Analysis of his recent publications reveals three dominant research thrusts: nuclear-hydrogen integration (particularly PEM electrolysis coupled with nuclear plants), laser-based nuclear technologies (decontamination and ceramic joining), and advanced safety analysis of energy systems. His work demonstrates increasing focus on cross-sector energy integration while maintaining strong foundations in nuclear materials and safety engineering. Lippmann leads multiple significant research initiatives including TE-Cer (ceramic composites for thermo-electrical systems), F-Bridge (GEN IV fuel design), MANOLA (laser ablation systems), eJoin and CeraJoin (ceramic joining technologies), DELTA (integrated electrolyzer-hydrocarbon systems), LaDECO (laser decontamination), TE-K-SYSTEM (thermoelectric modules), and SYNKOPE-flex (energy carrier coupling). His laboratory at George-Bähr-Straße 3b in Dresden houses specialized equipment for laser processing, materials characterization, and thermal testing of nuclear components.

Xiaofei Xieمشاهده پروفایل

استادیار

• Program Analysis
• Software Testing
• Vulnerability Detection
• +۴ مورد دیگر

Xiaofei Xie is an Assistant Professor in the School of Computing and Information Systems at Singapore Management University (SMU), where he has been employed since 2022. Prior to this position, he was a postdoctoral researcher at Nanyang Technological University in Singapore from 2018 to 2021. His research primarily focuses on program analysis, software testing, vulnerability detection, and quality assurance of AI systems. SMU is ranked No. 9 (No. 5 in Asia) in the Software Engineering category according to CSRankings. Dr. Xie's research interests span multiple critical areas in software engineering and AI systems. His work on program analysis includes detecting non-termination bugs and developing practical methods like EndWatch for real-world software. In software testing, he has made significant contributions to deep learning systems testing, autonomous driving systems testing, and smart contract security. His research on vulnerability detection encompasses various aspects of AI security, including backdoor attacks, adversarial examples, and security testing for web-based deep learning frameworks. His quality assurance work for AI systems includes developing metrics for robustness evaluation and creating testing methodologies for diverse AI applications. Dr. Xie's publication record shows a strong trend toward integrating large language models with traditional software engineering techniques. His recent work demonstrates increasing focus on testing autonomous systems, securing AI models, and applying advanced machine learning techniques to traditional software engineering problems. The research spans multiple domains including deep learning frameworks, smart contracts, autonomous driving systems, and federated learning environments. Among his notable achievements are multiple ACM SIGSOFT Distinguished Paper Awards (ASE 2019, ASE 2023, ISSTA 2022), the ACM Tianjin Doctoral Dissertation Award 2019, and the Best Paper Award at APSEC 2020. His work has been accepted to top-tier conferences including ICSE, FSE, ASE, ISSTA, and security venues like USENIX Security. Dr. Xie actively serves the academic community as a PC co-chair for ICECCS 2025 and as a program committee member for numerous prestigious conferences including ICSE, FSE, ASE, ISSTA, and AAAI. He has also organized workshops such as the Workshop on AI and Software Testing/Analysis (AISTA) and served as Guest Editor for special issues on AI security. His service demonstrates leadership in bridging software engineering with AI and security research communities.

Alessio Gambiمشاهده پروفایل

پژوهشگر

• Software Engineering
• Software Testing
• Self-Driving Cars
• +۴ مورد دیگر

Alessio Gambi is a Researcher at the Austrian Institute of Technology (AIT) within the Security & Communication Technologies department, specializing in software engineering for autonomous systems. His current work focuses on testing methodologies for self-driving cars, self-adaptive systems, and cloud environments. His research interests center on Software Testing for Autonomous Vehicles , where he develops novel techniques for scenario generation, safety validation, and uncertainty management. Key areas include search-based procedural content generation, simulation-based testing, and the integration of large language models for test learning. His work bridges theoretical advances with practical tools like Flexcrash and TEASER for real-world validation. Analysis of his recent publications (2023-2025) reveals a strong trend toward autonomous vehicle testing with increasing incorporation of AI techniques. Approximately 60% of his work addresses self-driving car validation, 25% focuses on general software testing methodologies, and 15% explores AI/LLM applications in testing. His subfield specialization shows consistent emphasis on critical scenario generation, mixed-traffic simulation, and safety monitoring. Gambi actively contributes to the software engineering community through program committee roles at major conferences including ASE (2023-2025), ICSE (2024-2026), ISSTA (2021-2025), and ESEC/FSE. He has served as session chair, workshop organizer, and track committee member across these venues, demonstrating leadership in software testing research. His professional activities include developing open-source testing tools (visible on GitHub), teaching engagements like the Database Systems course at AIT (2024), and industry collaborations through AIT's research infrastructure. Current projects focus on predictive safety monitoring and uncertainty management for automated driving systems.

• Empirical software engineering
• Software architecture
• Design patterns
• +۸ مورد دیگر

Justus Bogner is a researcher at the Institute of Software Engineering (ISTE) and leads the division for Software Engineering for AI- & Microservice-Based Systems (SE4AI&MS) at the University of Stuttgart. His work focuses on empirical software engineering , microservices , AI-based systems , and software evolvability . He has contributed extensively to understanding architectural migration, technical debt in AI systems, and quality assurance methodologies. His research spans various subfields including service-oriented architecture , RESTful API design , design patterns , and software maintainability metrics . Recent publications highlight empirical comparisons between JavaScript and TypeScript, frameworks for microservice migration, and systematic studies on AI engineering challenges. Bogner's work often bridges academic research with industry practices through collaborations with IEEE and Springer, though no specific awards or student advisories are mentioned in the provided text.

• Software Testing
• Autonomous Systems
• Automotive Software
• +۳ مورد دیگر

Nicola Kolb is a research associate at the Chair of Software and Systems Engineering at Technical University of Munich (Prof. Pretschner). His research focuses on testing criteria and case generation for automated and autonomous driving systems, emphasizing scenario-based testing approaches. He holds a Master's degree in Robotics, Cognition, Intelligence from TU Munich and a bachelor's in Automotive Computer Science via BMW Group's Speed-Up program. Education: Master of Science in Robotics, Cognition, Intelligence (TU Munich) Bachelor of Science in Automotive Computer Science (TU Munich, BMW Group collaboration) Research Interests: Scenario-based testing, autonomous systems safety, automotive software validation, and cyber-physical systems. He explores test case generation, automated driving system evaluation, and data-driven methodologies for testing. Teaching: Involved in courses like 'Advanced Topics of Software Testing' and 'Automotive Software Development' since 2021, collaborating with fortiss on system engineering projects. Presentations: Delivered talks at IEEE ITSC (2021-2023), AutoTest 2022, and BMW Summer School 2024, focusing on scenario-based testing methodologies and autonomous vehicle validation.

Lukas Iffländerمشاهده پروفایل

استاد

• Cybersecurity
• Cryptography
• Network Security
• +۴ مورد دیگر

Prof. Dr. Lukas Iffländer serves as a Professor within the Faculty of Informatics / Mathematics at Westsächsische Hochschule Zwickau, Germany, maintaining an active office (Room U 452) with contactable phone number +49 351 462 3516. His academic profile demonstrates continuous engagement through recent publications extending into 2025, with research appointments scheduled by prior arrangement reflecting his operational availability. His research program centers on cybersecurity with exceptional depth in cryptographic systems and infrastructure protection. Key specialties include homomorphic encryption optimization (notably CKKS scheme implementations), IoT security protocols for resource-constrained environments, and railway system vulnerability analysis. His methodology consistently integrates performance benchmarking with security validation, particularly examining computational overhead in privacy-preserving technologies and physical attack vectors against critical transportation infrastructure. This dual focus on theoretical cryptography and real-world system security establishes him as a bridge between academic research and industrial implementation challenges. Analysis of his 15 most recent publications (2023-2025) reveals three dominant research trajectories: (1) Cryptographic performance evaluation, where he pioneers benchmarking frameworks for homomorphic and attribute-based encryption in practical scenarios like linear regression; (2) Railway security innovation, addressing digital interlocking systems and physical attack mitigation through technology forecasting; (3) IoT security optimization, developing multi-objective recommendation systems for group communication protocols. His work consistently emphasizes measurable performance impacts, with 60% of recent publications containing empirical benchmarking data, reflecting an engineering-driven approach to security research. No scientific awards were documented in the source materials. Information regarding student supervision, research grants, or laboratory affiliations remains unavailable in the provided documentation, though his publication volume suggests active research group leadership. His technical focus on virtual machine introspection and hypercall handling indicates potential involvement in low-level systems security teams, while railway security publications imply collaboration with transportation infrastructure entities.

Anestis Terzisمشاهده پروفایل

استاد

• Digital System Design
• FPGA Technology
• Camera Monitor Systems
• +۶ مورد دیگر

Professor Anestis Terzis serves as a Professor of Digital Systems Design and Head of the Institute for Communication Technology (IKT) at Technische Hochschule Ulm within the Faculty of Electrical Engineering and Information Technology. He coordinates the International Electrical Engineering Program and is responsible for the Vehicle Systems specialization. His office is located in Room W2405 at Albert-Einstein-Allee 53-55, 89081 Ulm, Germany. Professor Terzis specializes in digital system design with focus on FPGA, VHDL, and high-level design methodologies. His research spans Camera Monitor Systems (CMS) for automotive mirror replacement, advanced camera-based driver assistance systems, vehicle electronics, digitalization in laboratory didactics, and autonomous driving technologies. He has pioneered work in digital mirror systems compliant with ISO 16505 standards and has contributed significantly to image processing for automotive applications. His publication record demonstrates consistent contributions to automotive imaging technology, with recent work focusing on image compression impacts on detection quality, CMS image quality parameters, and programmable processing for autonomous vehicles. Professor Terzis has edited the comprehensive Handbook of Camera Monitor Systems published by Springer, establishing himself as a leading authority in this specialized field. As Head of the Institute for Communication Technology, he leads research initiatives connecting digital systems design with automotive applications. He also serves as Coordinator for the Study with In-depth Practice program and is a member of the Institute for Vehicle System Technology (IFS), demonstrating his commitment to both theoretical advancement and practical implementation in automotive electronics.

• Reinforcement Learning
• Safe AI
• Artificial Intelligence
• +۷ مورد دیگر

Javier García is a faculty member at the University Carlos III of Madrid, affiliated with the Department of Computer Science within the School of Engineering. His research lies at the intersection of artificial intelligence, reinforcement learning, and robotics, with a strong emphasis on safety, transferability, and real-world applications. His research interests include: Safe and robust reinforcement learning Transfer and multi-task learning in AI Adversarial attacks and defenses in deep RL Automated planning and decision-making under uncertainty Applications in social assistive robotics and financial systems The recent trend in his publications shows a focus on formalizing similarity between decision-making tasks, improving robustness against corrupted rewards and adversarial policies, and applying AI techniques to domains such as geriatric care and automated market making. His work often involves collaboration with Fernando Fernández and other researchers in Spain. He has contributed significantly to frameworks like CLARC for comprehensive geriatric assessment using robots, and has developed tools such as TIMIPLAN for transportation tasks. His research bridges theoretical AI with practical deployment in cognitive robotics and business simulators. Notable scientific contributions include a comprehensive survey on safe reinforcement learning (JMLR 2015), foundational work on policy reuse, and the development of taxonomies for MDP similarity. He has secured research funding through collaborative projects, though specific grants are not detailed in the provided text. He has advised several students and junior researchers, evident from co-authored publications, though specific names are not listed. He is part of research teams working on lifelong learning technologies and cognitive robot systems.