جستجوی استاد راهنمای دانشگاهی

• Human-Robot Interaction
• Artificial Intelligence
• Cognitive Science
• +۳ مورد دیگر

Prof. Verena Hafner is a Professor at the Institute of Computer Science within the Faculty of Mathematics and Natural Sciences at Humboldt University of Berlin. She leads the Adaptive Systems group, focusing on interdisciplinary research at the intersection of robotics, AI, and cognitive science. Her work emphasizes human-robot interaction, adaptive learning mechanisms, and embodied cognition. Her research explores: Design and impact of socially interactive robots in educational and cognitive contexts Trust dynamics and transparency in human-robot relationships Development of bio-inspired AI models and sensorimotor learning systems Philosophical and ethical dimensions of artificial consciousness and agency Analysis of her recent publications (2023-2025) reveals strong emphasis on educational robotics, cognitive modeling, and humanoid robot design. Key trends include multimodal learning architectures, trust calibration in HRI, and biologically-inspired AI frameworks. Her work consistently bridges theoretical AI with applied human-centered experimentation. She supervises graduate students including Michael Piechotta (doctoral candidate) and leads the Adaptive Systems laboratory investigating lifelong learning in artificial agents.

Frank Hutterمشاهده پروفایل

استاد

• Automated Machine Learning (AutoML)
• Neural Architecture Search
• Efficient Hyperparameter Optimization
• +۳ مورد دیگر

Frank Hutter is a Full Professor for Machine Learning at the University of Freiburg since 2016 and an Emmy Noether Research Group Lead since 2013. His research focuses on Automated Machine Learning (AutoML), including neural architecture search, hyperparameter optimization, and meta-learning. He pioneered tools like Auto-WEKA, Auto-sklearn, and Auto-PyTorch, and co-authored the first book on AutoML. Received 2010 CAIAC award for best AI thesis in Canada Won multiple best paper awards and international ML competition prizes Director of ELLIS Unit Freiburg Recipient of 3 European Research Council (ERC) grants His recent work explores the intersection of foundation models and AutoML, including TabPFN (the first foundation model for tabular data) and improved pretraining/fine-tuning frameworks. He co-organized 15 AutoML workshops at top ML conferences and founded the AutoML Conference in 2022.

• Algorithms
• Theoretical Computer Science
• Programming Languages
• +۶ مورد دیگر

Ben Rank is a Researcher at the Max Planck Institute for Software Systems (MPI-SWS), focusing on foundational aspects of computer science with a strong emphasis on theoretical rigor and practical applications. His work bridges multiple domains including algorithms, formal verification, and cyber-physical systems. Research interests include: Algorithmic methods in programming languages and verification Cyber-physical systems design and analysis Security and privacy in distributed systems Social and information systems integration Recent publications explore cutting-edge topics such as adaptive reinforcement learning in shifting environments and ethical considerations in AI systems. No scientific awards or grants are explicitly mentioned in the provided materials.

Leo van Waverenمشاهده پروفایل

استاد

• Vocational Education
• Educational Technology
• Teacher Training
• +۳ مورد دیگر

Prof. Dr. Leo van Waveren is a Professor and Head of the Technical Didactics Group at RheinMain University of Applied Sciences (RPTU/Koziel). His academic career includes postdoctoral research at the University of Stuttgart (2018-2022) and academic roles at Technische Universität Kaiserslautern. He holds a PhD (Dr. phil.) from the University of Stuttgart (2017) and a Diplom in Technikpädagogik (Dipl.-Gwl. Informatik/Chemie). His research focuses on vocational education, ICT integration in teaching, and the impact of artificial intelligence (AI) on education. Recent work emphasizes AI's role in curriculum design and teacher training. He actively participates in national and international conferences, delivering keynote speeches on topics like generative AI in classrooms and digital transformation in vocational training. Research interests include technical competency modeling, dual education systems, and educational technology. Notable contributions include studies on vocational competencies in automation technology and teacher job satisfaction across career pathways. His work bridges theoretical frameworks with practical applications, such as smartphone-based experiments in STEM education. Prof. van Waveren leads the RPTU's efforts in digital education initiatives, including the DIGILL@Praxis program. He collaborates with regional and international institutions to advance educational innovation. Despite no listed awards, his extensive publication record and active speaking engagements underscore his scholarly impact.

• Accessibility Research
• Web Accessibility
• Mobile Accessibility
• +۵ مورد دیگر

Shari Trewin is a prominent researcher in accessibility and human-computer interaction at IBM Research with over 25 years of scholarly contributions. Her work focuses on making digital technologies accessible to people with disabilities, particularly in web and mobile contexts. She has published extensively in top-tier venues including ACM SIGACCESS conferences (ASSETS, W4A) and journals, CHI, and other leading HCI publications. Dr. Trewin's research interests span web accessibility, mobile accessibility for users with physical and cognitive disabilities, inclusive design methodologies, and the application of artificial intelligence to improve accessibility. Her work addresses both theoretical foundations and practical implementations of accessible technologies, with particular emphasis on user-centered design approaches and evaluation methodologies. She has made significant contributions to understanding how people with disabilities interact with digital interfaces and how to design systems that accommodate diverse user needs. Her publication record shows a clear progression from foundational work on input devices and keyboard accessibility in the 1990s to contemporary research on AI fairness for people with disabilities. Recent publications demonstrate her leadership in addressing emerging challenges at the intersection of AI and accessibility, particularly around algorithmic fairness and inclusive design practices for AI systems. Among her notable contributions are editorial work for ACM Transactions on Accessible Computing and co-editing conference proceedings for the ASSETS conference. She has collaborated extensively with leading researchers in the field including Vicki L. Hanson, Gregg Vanderheiden, and Calvin Swart. Dr. Trewin has advised junior researchers including Jessica J. Tran, and her work has influenced both academic research and industry practices in accessibility. Her research has practical implications for web developers, designers, and policy makers working to create more inclusive digital experiences.

• Cybersecurity
• IoT Security
• Network Anomaly Detection
• +۵ مورد دیگر

Gabriela F. Ciocarlie is a Researcher at SRI International, focusing on advancing cybersecurity, IoT security, and formal verification techniques. Her work bridges theoretical computer science with practical applications in critical infrastructure protection and manufacturing systems. She has contributed to over 48 publications across conferences like CCS, NDSS, and IEEE venues. Her research interests span adversarial machine learning, secure manufacturing automation, and resilient biomanufacturing systems. Notable projects include developing frameworks for verifying manufacturing design integrity and creating end-to-end security solutions for cyber-physical systems. She has also pioneered work on deployable adversarial attacks against neural networks and automated attack investigation tools like autoMPI. Key collaborations include partnerships with institutions like Columbia University (former affiliation) and industry leaders. Her work often addresses real-world challenges such as pandemic-resilient biomanufacturing and securing critical infrastructure through cyber-physical integration.

• Synthetic Biology
• CO2 Fixation and Photosynthesis
• Metabolic Engineering
• +۳ مورد دیگر

Tobias Erb is a Professor at the University of Marburg and Director of the Department of Biochemistry and Synthetic Metabolism at the Max Planck Institute for Terrestrial Microbiology in Marburg. He received an ERC Advanced Grant (2024) for his project 'pro2neo-RUBISCO', aiming to enhance photosynthetic efficiency through synthetic biology. His research focuses on CO2 fixation, metabolic engineering, and enzyme design to address climate and agricultural challenges. He earned his PhD in microbiology from the University of Freiburg (2009) and held research positions in the US and Switzerland before becoming a Max Planck Director (2017) and University of Marburg professor (2018). His honors include the Leibniz Prize (2024), Otto Bayer Prize (2019), and EMBO membership (2022). Research interests span synthetic carbon assimilation pathways, Rubisco enzyme evolution, and sustainable biotechnology. He leads teams developing new-to-nature metabolic cycles (e.g., the C3/C4 shuttle) and engineered organisms for CO2 conversion. His work bridges foundational biology and applied biotechnology, with implications for bioeconomy and climate mitigation. Key achievements include the THETA cycle (2023), which outperforms natural CO2 fixation, and functional screening of uncultured microbes for novel CO2-reducing enzymes. Collaborations include cell-free systems for pathway testing and machine learning-driven enzyme optimization.

• Machine Learning
• Artificial Intelligence
• Data Mining
• +۳ مورد دیگر

Thorsten Joachims is a Professor at Cornell University with a focus on machine learning, recommendation systems, and algorithmic fairness. His work spans conferences like ICML, NeurIPS, KDD, and SIGIR, emphasizing counterfactual learning, contextual bandits, and ethical AI. Key Research Themes: Fairness in rankings, reinforcement learning, position bias estimation, and NLP applications to recommendation systems. Recent Publications: 2025 work on policy decomposition for contextual bandits, 2024 studies on fairness under uncertainty, and 2023 papers on LLM steerability and bias mitigation. Awards: Recipient of the ACM SIGKDD 2020 Innovation Award . Collaborators: Regularly works with Adith Swaminathan, Tobias Schnabel, Yuta Saito, Ashudeep Singh, and Yi Su.

Dieter Trautzمشاهده پروفایل

استاد

• Sustainable Agriculture
• Organic Farming
• Crop Quality Analysis
• +۴ مورد دیگر

Prof. Dr. Dieter Trautz is a retired professor at the Faculty of Agricultural Sciences and Landscape Architecture at Osnabrück University of Applied Sciences. His career includes academic roles at Christian-Albrechts University Kiel (1982-1988), TU Berlin (1988-1989), and the Kirgizian Agrarian Academy (1998-2000). He focuses on sustainable agriculture, organic farming systems, and precision farming technologies. Education: Studied Agricultural Sciences at Christian-Albrechts University Kiel (1976-1982), PhD in 1987. Research spans crop quality, organic-mineral fertilizers, intercropping, and climate change impacts. He has collaborated internationally in over 20 countries, including projects in Russia, China, and Uganda. Key research areas include: Sustainable intensification of farming systems Organic cultivation of cereals, soybeans, and potatoes Precision farming technologies for organic agriculture Climate-resilient urban agriculture Technology transfer between conventional and organic practices Projects include the MuP project (reducing fertilization in water protection areas) and HerbfreiErbAB (sensor-based mechanical weed control). Active in international research networks and capacity building in developing regions.

• Software Engineering
• Machine Learning Operations (MLOps)
• Cyber-Physical Systems
• +۴ مورد دیگر

Prof. Dr. Klaus Schmid is a Professor in the Department of Software Systems Engineering at the University of Hildesheim, part of the Faculty of Mathematics, Natural Sciences, Economics, and Computer Science. His research focuses on Machine Learning Operations (MLOps), software product lines, adaptive systems, and variability modeling. He leads projects such as EXPLAIN and ReGaP, emphasizing explainable AI and industrial MLOps integration. His work addresses challenges in Cyber-Physical Production Systems (CPPS), including data management, model calibration, and domain knowledge integration. Key research interests include MLOps architecture design, variability modeling transformations (e.g., UVL to IVML), and incremental verification techniques for software product lines. He has published extensively in venues like IEEE ETFA, IEEE Software, and SPLC conferences. Notable achievements include a Best Paper Award for work on control patterns in self-adaptive systems. Collaborations with industry partners highlight his focus on bridging academic research and practical industrial applications. Prof. Schmid’s contributions extend to tool development, such as EASy-Producer for variability-aware software ecosystems, and frameworks for environment modeling in adaptive systems. His research addresses both foundational challenges (e.g., syntax-preserving slicing) and applied topics like MLOps platform comparisons and industrial case studies in Industry 4.0.

Hendro Wicaksonoمشاهده پروفایل

استاد

• Data-Driven Approaches
• Causal AI
• Explainable AI
• +۵ مورد دیگر

Prof. Hendro Wicaksono is a Professor of Data-Driven Industrial Systems at the School of Business, Social & Decision Sciences, Constructor University Bremen gGmbH. His expertise lies in applying AI and data-driven methods to enhance decision-making in complex industrial systems. He holds a Dr.-Ing. from Karlsruhe Institute of Technology (Germany) and M.Sc./B.Sc. degrees from German and Indonesian institutions. Research Interests : Focuses on causal AI, explainable AI, digital twins, sustainable industrial systems, and smart cities. His work integrates machine learning with domain-specific challenges in supply chains and energy management. Projects : Led over 10 funded projects including Delfine (accelerating energy transition), Talenta (digital asset management), and xAgri (agri-food supply chain analytics). Collaborates with global partners like Stadtwerke Trier and JetBrains. Teaching : Courses include Data Management in Industry 4.0, Production Planning, and Smart Cities. Recently on sabbatical in Spring 2023. Students : Supervises 20+ PhD/Master students researching topics like causal ML in software projects, EV adoption modeling, and blockchain logistics. Affiliations : Visiting Professor at University of Exeter, Adjunct Professor at Sebelas Maret/Airlangga Universities (Indonesia), and Academic Leader at Bandung Institute of Technology.

• Digital Signal Processing
• Audio Technology
• Acoustics
• +۵ مورد دیگر

Prof. Dr.-Ing. André Jakob is a faculty member at Berlin University of Technology , affiliated with the Department VII - Electrical Engineering - Mechatronics - Optometry. His academic role spans teaching and research in digital signal processing, audio technology, and acoustics. Digital Signal Processing Audio Technology Acoustics Active Noise Control His research focuses on active noise control , simulation of moving sound sources , and audio signal processing , with applications in robotics, building acoustics, and medical devices. Publications include advancements in anti-noise window systems , sound source localization , and acoustic measurement techniques . His recent work explores real-time auralization for educational robotics and nonlinear acoustic modeling with neural networks. The 15 most recent articles demonstrate a consistent focus on acoustic simulation , active control systems , and sound propagation modeling , with conference contributions at DAGA, NAG-DAGA, and international acoustics events. Topics range from dental drill noise reduction to active sound design in musical instruments , reflecting interdisciplinary applications. He supervises numerous Master's and Bachelor's theses in areas like real-time signal processing, deep learning for sound recognition, and virtual acoustics. His lab at TU Berlin explores multi-loudspeaker systems , acoustic beamforming , and active noise cancellation for both industrial and consumer applications.

Oliver Deussenمشاهده پروفایل

استاد

• Visualization
• Computer Graphics
• Digitalization Processes
• +۴ مورد دیگر

Oliver Deussen is a Professor of Visual Computing at the University of Konstanz, recognized by the German Informatics Society (GSI) as a Fellow for his contributions to computer science. His research focuses on visualization, robotics, and environmental modeling, particularly in plant and landscape representation. He has pioneered methods in image manipulation and robotic painting, emphasizing digitalization's societal impacts. His work spans computational biology (e.g., schooling fish behavior) and AI-driven creative technologies. Research Interests: Visualization techniques, swarm behavior analysis, robotic creativity, and interdisciplinary applications of computer science. He explores how computational methods can model natural systems and enhance human-machine interaction. Awards: Fellow of the German Informatics Society (GSI) His research often bridges theory and practice, with contributions to SLAM frameworks, style transfer algorithms, and uncertainty visualization tools. Collaborations in robotics and biology reflect his commitment to applied computational research.

Enrico Rukzioمشاهده پروفایل

استاد

• Human-Computer Interaction (HCI)
• Automotive User Interfaces
• Extended Reality (XR)
• +۵ مورد دیگر

Enrico Rukzio is a Full Professor of Human-Computer Interaction at the University of Ulm, leading the Human-Computer Interaction group and directing the Institute for Media Research and Media Development. His research spans interactive systems design, focusing on automotive UIs, extended reality, accessibility, and sustainable interaction. He holds a Ph.D. in Computer Science from the University of Munich and has held prior roles at Lancaster University and the Ruhr Institute for Software Technology. Roles: Faculty Dean (2017–2020), Admissions Committee Chairman, Doctoral Committee Chairman Educations: Ph.D., Munich; Lecturer qualifications from Lancaster and Duisburg-Essen Research emphasizes enabling efficient, inclusive, and sustainable interactions through novel interfaces. His work addresses automated vehicles, health-supporting tech, and accessibility for visually impaired users. Recent articles explore Bayesian optimization for UI design, automated vehicle communication, and urban air mobility visualization. Notable awards include best paper recognitions at CHI, EuroVR, and IEEE VR. His grants come from BMBF, DFG, and industry partners like Mercedes-Benz Group. Advises on over 20 funded projects and has mentored award-winning students.

Iason Papaioannouمشاهده پروفایل

استاد مدعو

• Uncertainty Quantification
• Structural Reliability
• Reliability-Based Optimization
• +۵ مورد دیگر

Iason Papaioannou is an Adjunct Professor in the area of Uncertainty Quantification at the Technical University of Munich (TUM), affiliated with the Engineering Risk Analysis Group. He holds a habilitation from the TUM School of Engineering and Design and has been tenured since 2021 as an Akademischer Rat. His academic journey includes a Ph.D. in Civil Engineering from TUM (2012), an M.Sc. in Computational Mechanics (2007), and a Diploma in Civil Engineering from the National Technical University of Athens (2005). His research focuses on uncertainty quantification , reliability assessment , and Bayesian updating of engineering systems. Key areas include probabilistic modeling, machine learning applications, spatial variability analysis, and geotechnical reliability. He has pioneered methods for system reliability analysis, adaptive subset simulation, and cross-entropy-based importance sampling. Teaching responsibilities include courses such as Stochastic Finite Element Methods, Structural Reliability Methods, and Elements of Machine Learning. His work integrates advanced computational techniques with practical engineering challenges, emphasizing high-dimensional uncertainty analysis and data-driven model updating.