جستجوی استاد راهنمای دانشگاهی

Karim Cherifiمشاهده پروفایل

پژوهشگر

• Control Theory
• Numerical Analysis
• Port-Hamiltonian Systems
• +۳ مورد دیگر

Karim Cherifi is a Researcher at the Institute of Mathematics , Technical University of Berlin, within the College of Mathematics and Natural Sciences. His academic journey includes a PhD in Control Theory (2015–2019) and postdoctoral work at the Max Planck Institute Magdeburg (2019–2020). Since 2021, he contributes to the ProFIT project "Electric Drives 2.0" at the Werner von Siemens Centre (WvSC). 2010–2013: Bachelor in Electrical and Electronic Engineering 2013–2015: Master in Control Engineering 2015–2019: PhD in Control Theory His research focuses on Control Theory , Numerical Analysis , and Port-Hamiltonian Systems , with applications in Linear Systems , Data-driven Modeling , and Model Reduction . Key trends include geometric formulations for discrete-time systems, dissipativity analysis, and integration of energy-based models with machine learning. Notable scientific recognition includes the DAAD Scholarship (2018) . His work spans publications on topics like structure-preserving interconnections, digital twin simulations, and data-driven realization techniques. Affiliated with the Institute of Mathematics at TU Berlin, he is based in Room MA 469 and collaborates within the Numerical Analysis research group.

• Artificial Intelligence
• Computational Intelligence
• Neural Networks
• +۵ مورد دیگر

Lakhmi C. Jain is a distinguished academic affiliated with the University of South Australia. As a Professor, she has made significant contributions to the fields of Artificial Intelligence, Computational Intelligence, and Fuzzy Systems. Her research spans neural networks, decision support systems, robotics, and data analysis, with a focus on interdisciplinary applications. Her career includes over 445 publications, including books like Complex Networks in Software, Knowledge, and Social Systems (2019) and E-Learning Systems - Intelligent Techniques for Personalization (2017). She has held editorial roles in journals such as the International Journal of Intelligent Decision Technologies (IDT) and the Journal of Intelligent & Fuzzy Systems. Jain's work emphasizes practical applications of computational intelligence, including efforts in software development, biomedical signal processing, and multi-agent systems. She has collaborated extensively with researchers globally, contributing to advancements in AI-driven technologies and decision-making frameworks.

Peter Buxmannمشاهده پروفایل

استاد

• Artificial Intelligence
• Digital Transformation
• Business Informatics
• +۴ مورد دیگر

Prof. Dr. Peter Buxmann is a full professor of business informatics at the Technical University of Darmstadt, holding the Chair in this field. He is an internationally renowned speaker, senior business advisor, and podcaster for the Frankfurter Allgemeine Zeitung. His roles include advisory board memberships for institutions like the Weizenbaum Institute for the Networked Society and Eckelmann AG. His research focuses on AI applications, digital transformation, and future work paradigms, with over 300 publications in top journals and conferences. Education: PhD and habilitation from University of Frankfurt, including a research stay at UC Berkeley's Haas School of Business. Previous positions: Professor at Technical University of Freiberg (2000-2004). Research Interests: Artificial Intelligence (applications in business, healthcare, and ethics), Digital Transformation (organizational and societal impacts), Data-Driven Business Models (platform economics, innovation ecosystems), and Future of Work (human-robot collaboration, agile principles). Keynote Topics: Generative AI and its industry applications Strategic digital transformation frameworks Ethical AI governance Labs/Teams: Leads the HIGHEST innovation center at TU Darmstadt and collaborates with TechQuartier Frankfurt. Founded multiple startups focusing on AI solutions.

Christof Büskensمشاهده پروفایل

استاد

• Optimization
• Optimal Control
• Control Systems
• +۵ مورد دیگر

Prof. Dr. Christof Büskens is a Professor of Technomathematics at the University of Bremen, leading the AG Optimierung und Optimale Steuerung (Optimization and Optimal Control Group) within the Faculty of Mathematics and Computer Science . His research focuses on Optimization, Optimal Control, and their applications in industrial and real-time systems. He holds leadership roles in interdisciplinary projects such as BESTVILLE and Safety Control Center for autonomous vehicle systems, and has contributed to maritime navigation, renewable energy management, and agricultural robotics. Büskens has supervised numerous PhD and master's students, advancing topics like autonomous exploration, neural architecture search, and trajectory optimization. His work integrates advanced numerical methods with practical applications, emphasizing real-world problem-solving in dynamic systems. Key affiliations include the ZeTeM (Center for Industrial Mathematics) and collaborations with industry partners. He has led over 20 projects since 2020, addressing challenges in autonomous systems, energy systems, and robotics. His educational contributions include courses on numerical analysis and optimal control, fostering interdisciplinary training for future researchers. Büskens' expertise bridges theoretical optimization and applied engineering, with over 100 publications and contributions to software tools like the WORHP solver.

• 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.

• 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.

• 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.

Srishti Yadavمشاهده پروفایل

پژوهشگر ارشد

• AI and Society
• Machine Learning
• Computer Science
• +۳ مورد دیگر

Srishti Yadav is a Research Fellow at the University of Copenhagen and University of Amsterdam , affiliated with the Pioneer Centre for AI and ILLC respectively. She is advised by Dr. Serge Belongie and Dr. Ekaterina Shutova . Education: M.Sc. (Research-Track) in Computing Science, Simon Fraser University , Canada Research Interests: AI and Society Cross-Cultural Competency in Multimodal Models AI Safety and Evaluation Frameworks Model Interpretability and Dataset Creation Scientific Awards: ELLIS PhD Fellowship Advising & Community: Board Member, Women in Computer Vision (WiCV) Advisor for WiCV@ICCV2023 and WiCV@CVPR 2021 Chaired workshops at CVPR 2024, CVPR 2023, CVPR 2020 Labs & Teams: Belongie Lab (University of Copenhagen) Shutova Lab (University of Amsterdam) Collaborator at MILA Biodiversity Monitoring Project

Santiago Berrezuetaمشاهده پروفایل

مدرس

• Virtual Reality
• Augmented Reality
• eXtended Reality
• +۷ مورد دیگر

Santiago Berrezueta is a Lecturer at the School of Computation, Information and Technology within Technical University of Munich (TUM). He actively contributes to research in Virtual Reality , Artificial Intelligence , and Robotic Assistance , with a focus on applications in Education and Healthcare . 2025 : 10 publications in VR, robotics, and AI ethics. 2024 : 4 co-authored studies on ChatGPT in ADHD therapy and collaborative learning. His research intersects Interactive Learning and Computer Vision , particularly in ADHD treatment , Language disorder detection , and VR-based education . He supervises Bachelor’s/Master’s theses on topics like gaze-based interaction, collaborative VR workflows, and AI-driven therapeutic tools. 2025: Excellent Paper Award at International Symposium on Educational Technology (ISET 2025) 2024: Best Presentation Award at International Conference in Intelligent Environments (IE 2024) He leads courses on Software Engineering and Programming Fundamentals at TUM’s Heilbronn campus. His work also explores IoT applications and ethical AI in vulnerable populations.

Tobias Bornemannمشاهده پروفایل

استاد

• Production Management
• Lean Management
• Industrial Engineering
• +۵ مورد دیگر

Prof. Dr.-Ing. Tobias Bornemann holds a Cooperative Professorship for Production & Lean Management at Frankfurt University of Applied Sciences , while also serving as Head of Product Management for Autonomous Mobile Robotics at Continental AG . His work bridges theory and practice in areas such as Lean Management , Industrial Engineering , and Smart Factory through teaching, research, and industry collaboration. His research focuses on Intralogistics , Autonomous Mobile Robotics , and Agile Product Development . He leads projects at the Research Lab for Urban Transport (ReLUT) and contributes to the House of Logistics and Mobility (HOLM) , where he co-developed a learning factory. His publications emphasize Industry 4.0 , AMR fleet management , and digital education tools . Cooperative Professorship at Frankfurt UAS Head of Industrial Engineering (M.Sc.) program Research Lab for Urban Transport (ReLUT) House of Logistics and Mobility (HOLM) collaboration Continental AG Tech Matinees and Ambassadorship His academic efforts include mentorship for students, interdisciplinary teaching , and industry-academia partnerships under the PROFfm initiative.

• Robotics
• Industrial Automation
• Control Systems
• +۶ مورد دیگر

Petter Falkman is a researcher at Chalmers University of Technology, specializing in robotics, industrial automation, and control systems. His work bridges theoretical advancements with practical applications in manufacturing, leveraging technologies like digital twins, eye tracking, and virtual reality. Key Research Areas: Robotics, Industrial Automation, Control Systems, Digital Twins, Human-Computer Interaction, Machine Learning. Collaborations: Frequently works with Bengt Lennartson, Kristofer Bengtsson, Martin Dahl, and colleagues across institutions. Publication Trends: Recent articles focus on gaze-based human intention prediction, ROS2 control architectures, and compositional automated planning. His work integrates machine learning with industrial control systems, emphasizing event-driven design and virtual commissioning. Methodologies: Develops frameworks like EPypes for data pipelines, contributes to STEP AP214 model generation, and explores energy optimization in multi-robot systems.

Adrian Paschkeمشاهده پروفایل

استاد

• Semantic AI
• Machine Learning
• Symbolic AI
• +۱۰ مورد دیگر

Prof. Dr. Adrian Paschke serves as Professor of Semantic Data Intelligence at the Einstein Center Digital Future (ECDF), holding a joint appointment between Freie Universität Berlin and Fraunhofer FOKUS since October 2019. He has been Professor and Head of the Corporate Semantic Web Group at the Institute of Computer Science, Department of Mathematics and Computer Science of Freie Universität Berlin since 2008, and Director of the Data Analytics Center at Fraunhofer FOKUS since 2016. Paschke is also a professoral member at the Institute for Applied Informatics at the University of Leipzig and Director of RuleML Inc. Dr. Paschke's research centers on integrating semantic AI with machine learning to bridge symbolic and sub-symbolic artificial intelligence approaches. His work explores semantic plausibilization techniques that enhance machine learning systems, particularly in computer vision applications where semantic knowledge helps distinguish between plausible and implausible interpretations. This research has significant applications in autonomous driving systems, where understanding exceptional scenarios requires combining data-driven learning with semantic knowledge representation. His work also extends to Edge Intelligence for Industrial IoT, bringing AI processing closer to data sources to improve system responsiveness and data privacy, as well as exploring the potential of quantum computing for AI applications. As an active member of the Dahlem Center for Machine Learning and Robotics, Paschke collaborates with researchers working on autonomous vehicles, collective intelligence, and logical reasoning systems. His research philosophy emphasizes the connection between theoretical advancements at Freie Universität Berlin and practical implementations with industrial partners through Fraunhofer FOKUS. Primary Affiliation: Institute of Computer Science, Department of Mathematics and Computer Science, Freie Universität Berlin Joint Appointment: Einstein Center Digital Future (ECDF) Leadership Role: Director of Data Analytics Center at Fraunhofer FOKUS Additional Affiliation: Professoral Member, Institute for Applied Informatics, University of Leipzig Paschke actively teaches Semantic Technologies through research seminars and software projects, mentoring students in developing semantic AI applications that bridge theoretical knowledge with practical implementation.

Zhenyu Chenمشاهده پروفایل

استاد

• AI for Testing
• Testing for AI
• Software Testing
• +۳ مورد دیگر

Zhenyu Chen is a Full Professor and Director of the iSE Laboratory at Nanjing University, specializing in AI-driven software testing methodologies. His research bridges artificial intelligence and software engineering with dual focus areas: leveraging AI to enhance testing processes ( AI for Testing ) and validating AI/ML systems ( Testing for AI ). His research interests center on deep learning framework testing , crowdsourced testing optimization , and Large Language Model applications in verification . Recent work demonstrates innovative approaches to metamorphic testing of neural networks, LLM-based test report analysis, and security hardening of code models against backdoors. Key contributions include the development of mooctest.com and frameworks like DevMuT for mutation testing of deep learning APIs. His publication trajectory reveals evolving focus from crowdsourced testing (2018-2020) to deep learning system validation (2021-2023) and current emphasis on LLM-powered testing solutions. Major venues include ASE, ICSE, and ISSTA where he serves regularly on program committees.

Jifeng Xuanمشاهده پروفایل

استاد

• Software Testing and Debugging
• Software Data Analysis
• Search Based Software Engineering
• +۲ مورد دیگر

Dr. Jifeng Xuan is a Professor and Deputy Dean at the School of Computer Science, Wuhan University, China. He founded the CSTAR (Centre of Software Testing, Analysis and Reliability) and holds editorial roles at Empirical Software Engineering and PLOS One . Previously, he was a postdoctoral researcher at INRIA Lille-Nord Europe (France) and earned his PhD from Dalian University of Technology. Research Interests: His work focuses on software testing, debugging, automated program repair, software data analysis, and search-based software engineering. He integrates AI/ML techniques for tasks like log analysis, fuzz testing, and vulnerability detection, with applications in robotics, microservices, and Android development. Publication Trends: Recent articles (2022–2025) emphasize AI-driven software engineering, including LLM-based repair, reinforcement learning for testing, and deep learning surveys. Security (vulnerability logs) and empirical studies on industrial challenges (e.g., C program repair) are recurring themes. Awards & Honors: ACM SIGSOFT Distinguished Paper Award (2025) IEEE TCSE Distinguished Paper Award (2025) CCF NASAC Youth Software Innovation Award (2024) Outstanding Doctoral Dissertation Award, China Computer Federation (2014) Luojia Young Scholar (2015) Student Advising & Labs: Actively recruits PhD and master students for CSTAR Lab. Research areas include automated debugging, testing tools (e.g., Mergebot, FastLog), and AI-generated code assessment. No specific grants listed.

Daniel Strüberمشاهده پروفایل

دانشیار

• Model-Driven Engineering
• AI Engineering
• Software Quality Assurance
• +۷ مورد دیگر

Daniel Strüber is an Associate Professor in Software Engineering at Chalmers University of Technology and the University of Gothenburg, Sweden, and an affiliate of the Department of Software Science at Radboud University Nijmegen, Netherlands. His research focuses on model-driven engineering, AI engineering, and empirical software engineering, addressing challenges in software quality, variability management, and security. He holds a PhD (summa cum laude) from Philipps University Marburg and has held academic positions including Assistant Professor at Chalmers and postdoctoral roles at King's College London and Philipps University Marburg. Education: PhD in Computer Science, Philipps University Marburg (2011–2016) Diplom (M.Sc. equivalent) in Computer Science, Philipps University Marburg (2005–2011) Research Interests: Strüber's work spans model-driven engineering, AI integration in software systems, and empirical studies. Key areas include: Model-based languages and tools for software quality assurance Machine learning-enabled systems and their engineering principles Robotics software engineering and variability management Formal methods for consistency and security Search-based optimization in model-driven development Recent Contributions: Recent work includes studies on LLM-assisted reverse engineering, empirical analysis of manual abstraction in software systems, and model-driven approaches for edge deployment of ML models. His research bridges theory with practical implementations in domains like robotics and web-based systems. Awards: Best Reviewer Award (SoSyM 2025) Distinguished Reviewer Awards (GPCE 2024, SPLC 2023) Transformation Tool Contest Awards (2020, 2016) EASST Best Paper Awards (ICGT 2020, ICGT 2017) Grants & Leadership: Co-editor of a JSS special issue on Product Line Engineering (2024) and program co-chair of SPLC 2024. Active in conferences like ICSE, ICGT, and MODELS. Leads grants such as the VR SEMLA project (2022–2024) and the DFG EUphORia fellowship (2019). Teaching: Courses include 'Software Engineering for AI Systems' at Chalmers and 'Software Product Lines' at Radboud University. Involves students in real-world projects via GiPHouse, a student-run company.