جست‌وجوی استاد و پژوهشگر

Matthias Nießnerمشاهده پروفایل

استاد

• 3D Digitization
• Computer Graphics
• Computer Vision
• +۷ مورد دیگر

Prof. Matthias Nießner is a Professor at the Technical University of Munich, leading the Visual Computing Lab. His research intersects computer graphics, vision, and AI, focusing on 3D reconstruction, semantic understanding, and AI-driven video synthesis. He holds a PhD from the University of Erlangen-Nuremberg (2013) and was a Visiting Assistant Professor at Stanford University (2013–2017). Notable awards include the ERC Starting Grant (2018), Nvidia Professorship Award, and Eurographics Young Researcher Award (2019). His work has been featured in mainstream media and led to startups like Synthesia Inc. Research spans Gaussian splatting, neural radiance fields, and generative AI for 3D avatars. Over 150 publications include SIGGRAPH, CVPR, and ECCV, with best paper awards. Projects like Face2Face and ScanNet have driven innovation in facial reenactment and 3D scene datasets. Education: PhD in Computer Science, University of Erlangen-Nuremberg (2013) Diploma in Computer Science, University of Erlangen-Nuremberg (2010) Research Interests: 3D digitization, neural rendering, generative AI, non-rigid reconstruction, and applications in AR/VR. Awards: ERC Starting Grant (2018) Nvidia Professorship Award (2018) Google Faculty Award (2018) SIGGRAPH Best Emerging Tech Award (2016) Grants: Over €1.5M from ERC and industry partnerships. Labs/Teams: Visual Computing Lab at TUM and Synthesia Inc. (co-founder). Key projects include ScanNet (large 3D indoor dataset), Face2Face (real-time facial reenactment), and Gaussian-based 3D avatars. Current work focuses on diffusion models, neural radiance fields, and AI-generated media detection.

• Computer Vision
• Computer Graphics
• Machine Learning
• +۴ مورد دیگر

Prof. Matthias Nießner is a Professor at the Technical University of Munich , where he leads the Visual Computing Lab . Prior to this, he held a Visiting Assistant Professor position at Stanford University . His work bridges computer vision , graphics , and machine learning , focusing on 3D reconstruction , semantic scene understanding , and AI-driven video synthesis . Prof. Nießner has published over 150 works in top venues like SIGGRAPH , CVPR , and ECCV , with several receiving best paper awards (SIGCHI’14, HPG’15, SPG’18, SIGGRAPH’16 Emerging Tech). His research has garnered international media attention, including features in the New York Times , Wall Street Journal , and MIT Technological Review , as well as TV demonstrations (e.g., Jimmy Kimmel Live for Face2Face technology). Awards : TUM-IAS Rudolph Moessbauer Fellowship (2017–ongoing) Google Faculty Award (2017) Nvidia Professor Partnership Award (2018) ERC Starting Grant (2018, €1.5M) Eurographics Young Researcher Award (2019) Research Trends : 3D Gaussian Splatting for real-time rendering Neural Radiance Fields (NeRF) with mesh supervision Audio-driven facial animation via diffusion models Latent space diffusion for 3D scenes Self-supervised and zero-shot methods for 3D and image analysis As a co-founder and director of Synthesia Inc. , he drives democratization of synthetic media. His YouTube channel has over 5 million views, reflecting his impact beyond academia.

Benjamin Langeمشاهده پروفایل

استاد پژوهشی

• Ethics of AI
• Technology Ethics
• Normative Ethics
• +۳ مورد دیگر

Benjamin Lange is a Research Professor and Junior Research Group Leader in the Ethics of AI and Machine Learning at Ludwig Maximilians University of Munich (LMU) and the Munich Center for Machine Learning (MCML). He is also an Associate Research Fellow at the Oxford Uehiro Institute for Practical Ethics and a member of LMU's Zentrum für Ethik und Philosophie in der Praxis (ZEPP). His research bridges foundational ethical theory with practical challenges in technology, business, and organizational ethics. Lange holds a BSc from the London School of Economics, and a B.Phil and D.Phil from the University of Oxford. He previously held visiting positions at Google’s Responsible Innovation team and the University of Hamburg. His research focuses on ethical frameworks for AI, digital ethics, and corporate responsibility. Key themes include the ethics of human-AI collaboration, moral partiality in relationships, and organizational ethics. He has advised the European Commission on AI governance and developed assurance audit methodologies for algorithmic systems, including work for NYC’s AI Bias Law. His consulting practice focuses on helping organizations build ethical cultures through capabilities like moral imagination and compliance frameworks. Lange’s work has been featured in media such as CBS News, Business Insider, and ZDF heute journal. He is completing a book on the ethics of interpersonal relationships and partiality, aiming to connect philosophical insights with practical applications. His recent publications explore moral imagination in engineering teams, bias mitigation in AI systems, and the ethical implications of digital duplication technologies. He advises Fortune 500 companies, startups, and public institutions across sectors including finance, technology, and education. His approach emphasizes aligning ethical practices with organizational growth and social impact through tailored ethical frameworks and stakeholder engagement strategies.

Steffen Marburgمشاهده پروفایل

استاد

• Numerical Methods in Vibroacoustics
• Aeroacoustics
• Structural Optimization
• +۶ مورد دیگر

Prof. Dr. Steffen Marburg is a Full Professor at the Chair of Acoustics of Mobile Systems within the TUM School of Engineering and Design at the Technical University of Munich. His research focuses on numerical methods in vibroacoustics, structural optimization, and acoustic modeling for applications in automotive, maritime, and musical instrument domains. Education: PhD from Technical University of Dresden (1998). Academic Career: Junior Professor at TU Dresden (2004), Chair of Technical Dynamics at University of the Federal Armed Forces Munich (2010), Full Professor at TUM (2015–present). Editorial Roles: Co-Editor-in-Chief of Journal of Theoretical and Computational Acoustics, Associate Editor of Journal of the Acoustical Society of America, Editor of Acoustics Australia and Mechanical Systems and Signal Processing. His research integrates computational acoustics, boundary element methods, and machine learning to address noise control and structural optimization challenges. Recent work explores acoustic metamaterials, viscothermal losses, and data-driven modeling. He has co-authored over 150 publications and led advancements in multifrequency solution methods and noise-insulating structures. Scientific awards include the Innovation Award of the Industrieclub Sachsen e.V. (1999). His editorial contributions and leadership in journals highlight his influence in computational acoustics and structural dynamics.

Toby Jia-Jun Liمشاهده پروفایل

استادیار

• Human-Computer Interaction
• Artificial Intelligence
• Machine Learning
• +۶ مورد دیگر

Toby Jia-Jun Li is an Assistant Professor in the Department of Computer Science and Engineering at the University of Notre Dame, where he leads the SaNDwich Lab. He also serves as the Director of the Human-Centered Responsible AI Lab in the Lucy Family Institute for Data & Society and is a Faculty Fellow at the Institute for Educational Initiatives (IEI). Previously, he was affiliated with Carnegie Mellon University's Human-Computer Interaction Institute (HCII) and GroupLens Research. Dr. Li's research spans the intersection of Human-Computer Interaction (HCI), End-User Software Engineering, Machine Learning (ML), and Natural Language Processing (NLP), with recent work focusing on addressing societal challenges in the future of work through human-AI collaborative approaches. His work has resulted in over 40 publications at premier venues including CHI, UIST, CSCW, ACL, and ICSE, with 8 papers winning Best Paper or Honorable Mention awards. His recent publications demonstrate a strong focus on human-AI collaboration across various domains, including code understanding, privacy, accessibility, and creative tools. The work shows a trajectory toward increasingly sophisticated integration of human-centered design with AI capabilities, particularly using large language models to enhance human productivity and address societal challenges. Google Research Scholar Award recipient Recipient of Yahoo! Fellowship ($100,000/year) Best Paper Award at UIST 2020 Best Paper Honorable Mention Award at CHI 2021 Best Paper Award at CSCW 2024 Best Paper Award at CHI 2025 Dr. Li actively mentors Ph.D. students and has established collaborations with Google, Microsoft Research, IBM Research, Adobe, Verizon, and J.P. Morgan. His research has been supported by NSF, Google Research Scholar Program, AnalytiXIN Initiative, Yahoo! InMind project, and J.P. Morgan. He is currently recruiting Ph.D. students and undergraduate researchers for his SaNDwich Lab, which focuses on developing interactive systems to empower individuals to create, configure, and extend AI-powered computing systems.

Matthias Feurerمشاهده پروفایل

استاد

• Automated Machine Learning
• Hyperparameter Optimization
• Bayesian Optimization
• +۵ مورد دیگر

Matthias Feurer is a Thomas Bayes Fellow and interim professor at the Chair of Statistical Learning and Data Science, funded by the Munich Center for Machine Learning (MCML) at Ludwig Maximilian University of Munich. He is a member of the Department of Statistics at LMU Munich, working under Prof. Dr. Bernd Bischl. His academic background includes: PhD in Computer Science from Albert-Ludwigs-Universität Freiburg, supervised by Prof. Dr. Frank Hutter M.Sc. in Computer Science from the University of Freiburg B.Sc. in Computer Science and Media from the Media University Stuttgart Feurer's research focuses on simplifying machine learning usage through Automated Machine Learning (AutoML). His work encompasses hyperparameter optimization, meta-learning, and model selection, with increasing emphasis on multi-objective AutoML that considers factors beyond predictive performance such as interpretability, deployability, and fairness. He actively develops open-source tools to advance the field. His recent publications demonstrate a strong trajectory in practical AutoML systems, with growing attention to tabular machine learning, foundation models integration, and addressing real-world constraints in optimization. His work consistently bridges theoretical advances with practical implementations through several widely-used open-source projects. Notable achievements include: 1st place in the warmstarting-friendly leaderboard of the BBO NeurIPS challenge Winner of the 2nd AutoML challenge Winner of the kdnuggets blog contest on AutoML Feurer is actively mentoring and teaching, having advertised PhD positions focused on AutoML, optimization, and benchmarking. He co-founded the Open Machine Learning Foundation supporting OpenML.org. His upcoming move to TU Dortmund as an assistant professor in AutoML and Optimization signals continued growth in his academic career while maintaining his research focus on making machine learning more accessible and rigorous.

Benjamin Mako Hillمشاهده پروفایل

دانشیار

• Peer Production
• Online Communities
• Collective Action
• +۷ مورد دیگر

Benjamin Mako Hill is an Associate Professor in the University of Washington Department of Communication and an Adjunct Associate Professor in Human-Centered Design & Engineering , the Paul G. Allen School of Computer Science & Engineering , and the Information School at UW. He is a Faculty Associate at the Berkman Klein Center for Internet and Society at Harvard University and a Fellow at the Center for Information Technology Policy at Princeton University during the 2023–2024 academic year. Educational Background : PhD in an interdepartmental program at Massachusetts Institute of Technology (MIT) , involving the MIT Sloan School of Management and the MIT Media Lab , advised by Eric von Hippel, Yochai Benkler, Tom Malone, and Mitch Resnick. MS in Media Arts and Sciences from MIT. B.A. in Technological and Legal History from Hampshire College . Research Interests span peer production, online communities, collective action, cooperation, learning, and computer-mediated communication. His work explores how communication and information technologies shape social outcomes in collaborative environments like Wikipedia and Linux, focusing on governance, moderation, anonymity, and educational platforms such as Scratch. Article Trends : His publications analyze peer production dynamics, privacy in open collaboration, and computational thinking in youth. Topics include underproduction in open source software, algorithmic fairness, taboo knowledge production, and legitimate peripheral participation in online communities. Methodologies combine big data, quasi-experimental, and comparative analyses. Scientific Awards : Dordick Award for Best Dissertation (2013). CHI '22 Best Paper Honorable Mention (2022). CSCW '18 Best Paper Honorable Mention (2018). CHI '17 Best Paper Honorable Mention (2017). CSCW '13 Best Paper Award (2013). CHI '11 Best Paper Honorable Mention (2011). Advising and Grants : He co-founded the Community Data Science Collective and collaborates with researchers like Aaron Shaw. Grants include multiple National Science Foundation awards for studies on digital knowledge commons, anonymous participation, and collaborative success, as well as a Sloan Foundation grant for modeling underproduction in peer production. Labs and Teams : He leads the Community Data Science Collective , an interdisciplinary research group studying online communities, and contributes to open-source projects like Debian and Ubuntu . He actively edits Wikimedia projects and participates in the Cascadia Wikimedians User Group .

• Human-Computer Interaction
• Textile User Interfaces
• Soft Robotics
• +۵ مورد دیگر

Jan Oliver Borchers is a full professor of computer science and head of the Media Computing Group at RWTH Aachen University, where he holds the endowed Chair in Media Informatics and Human-Computer Interaction (Computer Science 10). He established his research group in 2003 and pioneered modern HCI academic research and teaching in Germany, becoming a leading lab in terms of archival publications at CHI, the top international conference in HCI. Before joining RWTH, he held faculty positions at Stanford University and ETH Zurich. His research focuses on Human-Computer Interaction with particular interest in new user interfaces for soft robotics, textile user interfaces, 3D printing and personal fabrication, augmented reality, wearable and tangible computing, interfaces for software development, deceptive patterns, and interactive guides and exhibits. He opened Germany's first Fab Lab in 2009 and has been instrumental in advancing digital fabrication and maker culture in academia. His work bridges theoretical HCI research with practical applications, as evidenced by his consulting for major companies including AirBus, Apple, ARD, Bayer, Children's Museum Boston, Daimler, Handelsblatt, OTIS, Scout24, TEDx, and Deutsche Telekom. His recent publications show a strong focus on deceptive patterns in UI design, textile interfaces, and the intersection of AI with human interaction. The research demonstrates consistent innovation in tactile interaction techniques, with numerous honorable mentions at top conferences like CHI. His lab has produced significant contributions to eyes-free interaction, textile computing, and the ethical implications of dark patterns, particularly regarding children's experiences with deceptive designs. IDC 2025 Best Work in Progress for research on children's assessment of deceptive designs CHI'25 Student Games Competition Winner for The Deceptive Dungeon RWTH-Wissenschaftsnacht 2024 Best Science Slam for Usability: 4 Prinzipien guter User Interfaces Multiple CHI Honorable Mentions spanning from 2008-2021 Best Note and Best Demo awards at ITS and UIST conferences Borchers has served in numerous leadership roles including heading the Computer Science Department's Examination Board (2015-2025), coordinating the department's public relations since 2010, and organizing the weekly Faculty Lunch since 2003. He is an active member of the ACM, SIGCHI, SIGCHI Germany, and GI, and introduced the Interactivity format to the CHI conference in 2005. His PhD thesis, A Pattern Approach to Interaction Design, became the first book to bring design patterns to HCI. The Media Computing Group under his leadership has developed significant expertise in physical computing, textile interfaces, and fabrication technologies, with a strong emphasis on both theoretical contributions and practical applications. His lab continues to push boundaries in interactive technologies while maintaining a strong ethical stance on user experience, particularly regarding deceptive design patterns.

• Human-Computer Interaction
• Virtual Reality
• Augmented Reality
• +۵ مورد دیگر

Prof. Dr. Andreas Butz is a Full Professor and Chair for Human-Computer Interaction at the Department for Informatics, Ludwig-Maximilians-Universität München (LMU Munich). He leads the Media Informatics Group, focusing on innovative interaction techniques and interfaces in immersive environments like VR/AR, automotive systems, and smart spaces. His research emphasizes perceptual user interfaces, social robotics, and designing systems that balance invisibility with transparency. Key research areas include: Virtual/Augmented Reality interfaces for productivity and social interaction AI-driven decision support in safety-critical domains (aviation, healthcare) Haptic and wearable interaction technologies Automotive UI design for driver assistance systems Principles of explainable AI and human-AI collaboration His work bridges theory and practice through projects like: VR-based movement training systems AI trust calibration mechanisms Multi-modal interaction frameworks for automotive environments Systems for analyzing long-term music listening behavior Recent articles explore topics ranging from AI support in pilot decision-making to haptic wearables and creative writing interfaces. His team collaborates with industry partners on electric vehicle information systems and in-car interaction challenges.

• Neural circuit mechanisms
• Adaptive learning
• State-dependent decision-making
• +۴ مورد دیگر

Dr. Sabine Krabbe is a Group Leader at the German Center for Neurodegenerative Diseases (DZNE) in Bonn, Germany, where she leads research on neural circuit mechanisms underlying adaptive learning and state-dependent decision-making. Her work integrates neuroscience, molecular biology, and behavioral approaches to understand how internal states influence behavior and how these processes are disrupted in neurological disorders. Dr. Krabbe's research focuses on the interactions between midbrain circuits of the substantia nigra and ventral tegmental area with their output structures such as the striatum and amygdala. She investigates how these networks integrate internal states with environmental cues to produce appropriate behavioral responses. Her laboratory employs state-of-the-art techniques including deep-brain calcium imaging at single-cell resolution in mice, opto- and pharmacogenetic manipulations, anatomical tracings, and molecular approaches to characterize neural circuit elements in detail. Her recent publications reveal significant insights into amygdala interneuron plasticity during fear learning, brain-wide representational drift in memory consolidation, and the molecular mechanisms underlying Parkinson's disease progression. Her work demonstrates how activity patterns within specific neural circuits change in early stages of neurodegenerative diseases and how this dysfunction contributes to cognitive deficits and emotional disturbances. Dr. Krabbe is actively involved in the neuroscience community, organizing the BonnBrain Conference 2026 and sharing research through social media platforms. She has established herself as an emerging leader in the field of systems neuroscience with a particular focus on the neural basis of emotional states and decision-making processes.

• Artificial Intelligence
• Machine Learning
• Cognitive Robotics
• +۳ مورد دیگر

Dr. Ulrike Kuhl is a Researcher at the University of Bielefeld, serving as Project Coordinator for the AI Academy OWL at the Research Institute for Cognition and Robotics and as Scientific Project Coordinator within the Faculty of Engineering's Machine Learning Group. Her office is located at CITEC 2-412, and she can be reached at +49 521 106-12125. Dr. Kuhl's research spans several interconnected domains at the forefront of human-centered AI development: Explainable Artificial Intelligence (XAI) frameworks and their psychological impact Cognitive learning enhanced through AI technologies Counterfactual explanation methodologies and user behavior Human-AI interaction design principles Applications of machine learning in environmental monitoring and sports analytics Analysis of Dr. Kuhl's publication trajectory reveals a consistent focus on bridging the gap between sophisticated AI systems and human understanding. Her work particularly examines how different explanation types affect user trust and decision-making, with recent publications exploring counterfactual explanations in contexts ranging from water distribution networks to educational technology. She has developed experimental frameworks like the 'Alien Zoo' methodology for systematically studying explanation usability. Dr. Kuhl actively contributes to the Center for Cognitive Interaction Technology (CITEC) at the University of Bielefeld, an interdisciplinary hub where computer scientists, engineers, and cognitive scientists collaborate on next-generation interactive technologies. Through her coordination of the AI Academy OWL initiative, she facilitates regional collaboration between academic researchers and industry partners to advance artificial intelligence applications in the Ostwestfalen-Lippe region.

Shrikanth Narayananمشاهده پروفایل

استاد

• Human-centered signal processing
• Machine intelligence
• Affective computing
• +۱۰ مورد دیگر

Shrikanth (Shri) Narayanan is University Professor and Niki & C. L. Max Nikias Chair in Engineering at the University of Southern California (USC), with appointments spanning Electrical & Computer Engineering, Computer Science, Linguistics, Psychology, Neuroscience, Pediatrics, and Otolaryngology-Head & Neck Surgery. He serves as Research Director of the Information Sciences Institute and Director of the Ming Hsieh Institute. PhD in Electrical Engineering (UCLA, 1995) Engineer and MS in Electrical Engineering (UCLA, 1992 and 1990) BE in Electrical Engineering (Anna University, India, 1988) His interdisciplinary research focuses on human-centered signal processing and machine intelligence , addressing societal challenges in health, education, defense, and media arts. Key areas include: Behavioral signal processing Affective computing Multimodal signal processing Computational speech science Biomedical applications Scientific Awards : IEEE James L. Flanagan Speech and Audio Processing Award (2025) Edward J. McCluskey Technical Achievement Award (2024) ISCA Medal for Scientific Achievement (2023) Claude Shannon-Harry Nyquist Technical Achievement Award (2023) ACM ICMI Sustained Accomplishment Award (2020) USC Distinguished Faculty Service Award With over 1,000 publications and 19 patents , his work has been commercialized through startups like Behavioral Signals Technologies and Lyssn . He leads transformative university initiatives and has served in editorial roles for top journals including Computer Speech and Language and IEEE Transactions on Affective Computing .

• Sports Science
• Football (Soccer) Analytics
• Cognitive Psychology in Sports
• +۶ مورد دیگر

Prof. Daniel Memmert is a Professor at the German Sport University Cologne, leading research in Sport Informatics and Sports Games within the Institute of Exercise Training and Sport Informatics. His work focuses on cognitive aspects of sports performance, decision-making, and data-driven analysis in football (soccer) and other sports. He has published extensively on topics like penalty kick strategies, home advantage dynamics, artificial intelligence applications in coaching, and route-setting in climbing. Memmert's research bridges sports science, computer science, and psychology, with over 550 publications and 41 projects to his name. He frequently engages with media, explaining complex sports phenomena to the public. Key Research Areas: Football analytics, cognitive psychology in sports, sports technology, decision-making under pressure Media Contributions: Over 50 media features discussing topics such as AI in coaching, referee bias, and athlete creativity Projects: Includes initiatives on sports data visualization, performance metrics, and prevention of sports betting addiction His work emphasizes translating academic findings into practical tools for athletes, coaches, and sports organizations, combining rigorous data analysis with real-world applications.

Niels Henzeمشاهده پروفایل

استاد

• Human-Computer Interaction
• Predictive Models in Interactive Systems
• Mobile Human-Computer Interaction
• +۵ مورد دیگر

Niels Henze is a Professor at the Chair of Media Informatics within the Faculty of Languages, Literature and Cultural Studies at the University of Regensburg, where he has been serving since May 2018. His research centers on human-computer interaction, with a strong focus on predictive models in interactive systems, mobile interaction, augmented and virtual reality, and attention-aware computing. His research interests include: Human-Computer Interaction (HCI) Predictive modeling for runtime adaptation Mobile and wearable interaction Augmented and Virtual Reality (AR/VR) Attention-aware and context-sensitive systems Sociocognitive aspects of interactive technologies The analysis of his recent publications reveals a consistent focus on leveraging user behavior and contextual cues to build intelligent, adaptive interfaces. His work integrates machine learning with interaction design, emphasizing real-time model updates, implicit feedback, and cognitive load awareness to improve usability and user experience across mobile and immersive platforms. Scientific awards: No awards mentioned in the provided text. Niels Henze leads research in adaptive interactive systems and advises students in the field of media informatics. He has previously held a junior professorship at the University of Stuttgart and completed his doctorate at the University of Oldenburg under Susanne Boll. He is actively involved in advancing the theoretical and practical foundations of predictive and attention-aware computing. Grants and funding sources are not specified in the text. He is associated with the Institute for Information and Media, Language and Culture (I:IMSK) at the University of Regensburg, contributing to a multidisciplinary environment that bridges informatics with cultural and linguistic studies.

Emilio Ferraraمشاهده پروفایل

استاد

• Artificial Intelligence
• Computational Social Science
• Network Analysis
• +۵ مورد دیگر

Dr. Emilio Ferrara is a Professor of Computer Science & Communication at the University of Southern California, holding appointments in the Viterbi School of Engineering, Annenberg School for Communication and Journalism, and Keck School of Medicine. He serves as Associate Director of Applied Data Science at USC, Research Team Leader at the USC Information Sciences Institute, and Principal Investigator at the USC/ISI Machine Intelligence and Data Science (MINDS) group. His educational background includes a PhD in Machine Learning and BSc & MSc in Computer Science. Ferrara's research focuses on the intersection of artificial intelligence and computational social science, specifically using AI to model and predict human behavior in techno-social systems. His work spans social networks, machine learning, and network science with applications to understanding communication dynamics in digital environments. Ferrara has published over 150 articles in prestigious venues including Proceedings of the National Academy of Sciences, Communications of the ACM, and Physical Review Letters. His research has been widely featured in major news outlets and examines topics ranging from social media manipulation to AI ethics and online behavior. His scientific achievements have been recognized with numerous awards: 2019 Viterbi Scientific Award 2018 DARPA Director's Fellowship 2016 DARPA Young Faculty Award 2016 Complex Systems Society Junior Scientific Award 2015 IBM Watson Big Data Influencer Ferrara's research is supported by major funding agencies including DARPA, IARPA, Air Force, and Office of Naval Research. He leads the HUMANS LAB (Humans & Machines + Networks & Social Systems) which has trained numerous PhD students who have gone on to successful careers in academia and industry. His work on social bots, election integrity, and AI ethics continues to shape understanding of digital social dynamics.