جست‌وجوی استاد و پژوهشگر

Christian Theobaltمشاهده پروفایل

استاد

• Computer Science
• Artificial Intelligence
• Computer Vision
• +۵ مورد دیگر

Christian Theobalt is a Professor of Computer Science at Saarland University and Scientific Director of the Visual Computing and Artificial Intelligence Department at the Max Planck Institute for Informatics . He leads the Saarbruecken Center for Visual Computing as a strategic partnership between Google and MPI. PhD in Computer Science (2005) from MPI-INF/Saarland University Postdoctoral Researcher at MPI (2005-2007) Visiting Assistant Professor at Stanford (2007-2009) His research focuses on the intersection of Computer Graphics, Computer Vision, and Artificial Intelligence , with specializations in: 3D/4D Human Reconstruction Neural Rendering Performance Capture Geometric Deep Learning Volumetric Video Quantum Visual Computing Recent article trends show emphasis on: Quantum computing applications in visual reconstruction Neural rendering with radiance fields Human motion capture from egocentric views Gesture-language interaction modeling Multi-modal scene understanding Real-time free-viewpoint rendering Scientific Awards : Fellow of EUROGRAPHICS (2022) CVPR Best Student Paper Honorable Mention (2020) ERC Consolidator Grant (2017) Karl Heinz Beckurts Award (2017) Busy Beaver Teaching Award (2016) ERC Starting Grant (2013) Advising over 50 students and researchers including: Current researchers: Viktor Rudnev, Linjie Lyu, Mohit Mendiratta Postdocs: Kwang In Kim, Kiran Varanasi Alumni: Franziska Mueller (Google), Dushyant Mehta (Qualcomm), Ayush Tewari (MIT) Grants include ERC grants, Google Glass Research Award, and multiple industry partnerships. His lab maintains cutting-edge facilities with: Multi-camera capture systems Quantum annealing infrastructure HDR radiance field technology GPU clusters for AI research Time-of-flight imaging systems Event camera arrays

• 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.

Jonathan T. Barronمشاهده پروفایل

پژوهشگر

• Computer Vision
• Deep Learning
• Generative AI
• +۳ مورد دیگر

Jonathan T. Barron is a Researcher at Google DeepMind in San Francisco, specializing in Computer Vision , Neural Rendering , and 3D Scene Reconstruction . He earned his PhD at UC Berkeley under Jitendra Malik and has pioneered advancements in NeRF (Neural Radiance Fields) and diffusion-based 3D generation. Research Interests : Computer Vision, Deep Learning, Generative AI, Image Processing, and 3D Reconstruction via Radiance Fields. His work includes Bolt3D for rapid 3D scene generation, CAT3D/CAT4D for text-to-3D/4D, and Zip-NeRF for anti-aliased radiance fields. He has also developed real-time rendering frameworks like SMERF and NeRF-Casting for reflections. Scientific awards: PAMI Young Researcher Award He has served as Area Chair for CVPR, ICCV, and NeurIPS, and his research is widely adopted in applications like Google's Lens Blur , Portrait Mode , and Jump VR .

Stefanie Muellerمشاهده پروفایل

دانشیار

• Human-Computer Interaction
• Computational Fabrication
• 3D Printing
• +۷ مورد دیگر

Stefanie Mueller is the TIBCO Career Development Associate Professor at MIT's Electrical Engineering and Computer Science Department, with joint affiliation in Mechanical Engineering. She leads the HCI Engineering Group at the Computer Science and Artificial Intelligence Laboratory (CSAIL), focusing on advancing fabrication techniques through hardware/software innovations that enable novel object interactions. Develops computational fabrication methods combining photochromic dyes, lenticular lenses, birefringent materials, and optical illusions Co-chaired ACM CHI 2023 and ACM UIST 2020 program committees Recipients of 9 MIT EECS Best Undergraduate Researcher Awards among mentees Her research spans four key directions: Appearance-changing Objects: Photo-Chromeleon (ACM UIST 2019), Lenticular Objects (ACM UIST 2021), and Polagons (ACM CHI 2023) demonstrate reprogrammable surfaces through advanced materials and optical engineering. Tracking Systems: InfraredTags (ACM CHI 2022) and G-ID (ACM CHI 2020) enable passive object tracking via infrared markers and slicing artifacts. Embedded Sensing: MechSense (ACM CHI 2023) and Sprayable User Interfaces (ACM CHI 2020) integrate sensing capabilities into complex geometries. Curved Surface Prototyping: FlexBoard (ACM CHI 2023) and CurveBoard (ACM CHI 2020) develop specialized tools for non-planar electronics. Her recent publications focus on functionality segmentation (UIST 2023), fluorescent markers (UIST 2023), and machine-knitted haptics (UIST 2023). These works combine machine learning, material science, and interactive design principles to push fabrication boundaries. Scientific recognition includes: 2022 MIT Technology Review Innovators Under 35 2020 Microsoft Research Faculty Fellowship 2020 Alfred P. Sloan Research Fellowship 2019 ACM UIST Best Paper Award 2019 NSF CAREER Award 2018 MIT EECS Outstanding Educator Award 2017 Forbes 30 Under 30 in Science Mentoring 9 PhD students and over 20 master's students, her lab has produced 20+ publications at top HCI conferences. She redesigned MIT's 6.810 Engineering Interactive Technologies course during the pandemic, maintaining hands-on learning through home electronics kits and Slack-based collaboration.

• Computer Vision
• Machine Learning
• 3D Human Modeling
• +۴ مورد دیگر

Michael J. Black is a Professor and Honorarprofessor at the University of Tübingen's Faculty of Science, Department of Computer Science, and a founding Director of the Max Planck Institute for Intelligent Systems, leading the Perceiving Systems department. He holds a B.Sc. from the University of British Columbia (1985), M.S. from Stanford (1989), and Ph.D. in Computer Science from Yale (1992). His research focuses on computer vision, 3D human modeling, motion capture, and AI-driven digital humans. Key contributions include the SMPL body model, optical flow algorithms, and datasets like Middlebury Flow and Sintel. He has received major awards such as the PAMI Distinguished Researcher Award, multiple Koenderink and Longuet-Higgins Prizes, and is a member of the German National Academy of Sciences Leopoldina and Royal Swedish Academy of Sciences. His commercial ventures include co-founding Body Labs (acquired by Amazon) and Meshcapade, advancing 3D human generation and interaction technologies. Recent work includes markerless motion capture systems (e.g., MAMMA, PICO), 3D hair and garment synthesis, and AI tools like ChatHuman for 3D human interaction analysis. His research bridges vision, graphics, and robotics, with applications in animation, healthcare, and robotics.

Franziska Muellerمشاهده پروفایل

پژوهشگر

• Computer Vision
• Machine Learning
• 3D Hand Pose Estimation
• +۳ مورد دیگر

Franziska Mueller is a Research Scientist at Google Zurich , specializing in Augmented Perception . Prior to joining Google, she earned her Ph.D. in Computer Science at Saarland University under the supervision of Prof. Dr. Christian Theobalt, focusing on real-time hand reconstruction from RGB and depth images. Ph.D. in Computer Science (2016-2020) at Saarland University Master’s and Bachelor’s in Computer Science at Saarland University Research visits at Stanford University (2018) and Reality Labs Research (2019) Her research emphasizes the integration of model-based techniques and machine learning components for real-time 3D hand pose estimation, occlusion handling, and hand-object interaction tracking. Key contributions include methods for single-camera reconstruction and datasets like HandSeg. Scientific Awards : Dr. Eduard Martin Award (2021) Google PhD Fellowship (2017) Günter-Hotz-Medal (2016) Bachelor Award (2015) Völklinger Abiturpreis (2012)

Agnes Desolneuxمشاهده پروفایل

استاد

• Image Analysis
• Statistical Methods
• Computer Vision
• +۷ مورد دیگر

Agnes Desolneux is a CNRS Research Director at the Borelli Centre (formerly CMLA) and a Professor attached to the Mathematics Department at ENS Paris-Saclay. Education: PhD in Applied Mathematics (2000) from ENS Cachan Habilitation in Applied Mathematics (2010) from Université Paris Descartes Her research focuses on image analysis via statistical methods , particularly a contrario approaches, image restoration, texture synthesis, Determinantal Point Processes (DPP), optimal transport, Gaussian mixtures, geometry of random field excursions, shot-noise models, and mathematical modeling of visual perception through Gestalt theory. The articles extracted reflect her expertise in applied mathematics and computer vision , with recent works (2025-2020) on optimal transport algorithms, DPP applications, multiscale texture analysis, and stochastic modeling in medical imaging. Keywords span machine learning, probability theory, medical imaging, and computer vision . She has no listed scientific awards but has authored influential works including the book From Gestalt Theory to Image Analysis: A Probabilistic Approach (Springer, 2008) and Pattern Theory: the stochastic analysis of real-world signals (AK Peters, 2010).

• Ancient History
• Greek Family History
• Economic History of Antiquity
• +۴ مورد دیگر

Christian Weigel serves as a Researcher at the Department of Ancient History within the Institute for Historical Science at the University of Bonn, a position he has held continuously since October 2016. His academic career includes prior roles as a lecturer (2014-2016) and research associate in the DFG-Graduiertenkolleg 1878 on pre-modern economic spaces (2013-2016), demonstrating deep institutional integration at Bonn. His educational foundation includes: Magister degree (2012) in Ancient History, Political Science, and Public Law from the University of Bonn Advanced studies (2005-2012) in Ancient History, Political Science, and Public Law Foundational studies (1999-2005) in Medieval/Modern History, Political Science, and Law Weigel's research interrogates Greek family structures through ancient novels while examining economic and social frameworks of antiquity. His focus on demographic patterns, ancient international law, and literary sources reveals innovative methodological approaches to social history. Recent work analyzes how ancient novels function as socioeconomic mirrors, particularly regarding slavery, migration, and gender dynamics in Greco-Roman societies. His publication trajectory (2015-2019) demonstrates consistent exploration of antiquity's socioeconomic textures through diverse lenses—from piracy in ancient fiction to Cold War-era science fiction's classical reception. This body of work establishes connections between ancient economic mentalities and modern cultural productions while maintaining rigorous historical analysis of demographic patterns and legal frameworks. As an active conference participant, Weigel has presented at major venues including the German Historians' Congress and German Sociological Association meetings. His teaching portfolio reveals substantive engagement with students through specialized courses on Homer's society, Roman slavery, Greek federalism, and ancient demographics, often incorporating field components like Adriatic coast excursions.

Stefan Eisebittمشاهده پروفایل

استاد

• Ultrafast Spectroscopy
• Magnetism
• Materials Science
• +۵ مورد دیگر

Prof. Stefan Eisebitt is a Director at the Max-Born-Institut für Nichtlineare Optik und Kurzzeitspektroskopie and holds a Professorship in Experimental Physics at the Technische Universität Berlin. His research focuses on ultrafast magnetization dynamics, nanoscale structure analysis, and novel imaging techniques using coherent XUV/X-ray spectroscopy. He leads the Transient Electronic Structure and Nanoscience group and is involved in cutting-edge projects involving femtosecond laser-driven X-ray sources and spintronic materials. Education and Career: He obtained his Diplom (1992) and Ph.D. (1996) from Cologne University, followed by postdoctoral research at the University of British Columbia and Forschungszentrum Jülich. He became a Privatdozent at Humboldt-Universität Berlin (2005) and held professorships at TU Berlin (2008–2015) and Lund University (2012–2015) before his current role since 2015. He leads the Functional Nanomaterials joint research group between Helmholtz-Zentrum Berlin and TU Berlin. Research Interests: His work spans transient electronic structure, ultrafast optical manipulation of magnetization, nanoscale material characterization, and advanced coherent imaging methods. Key techniques include XUV/X-ray spectroscopy, laser-driven plasma sources, and femtosecond time-resolved studies. Professional Roles: He chairs the Physikalische Gesellschaft zu Berlin and the Elettra Scientific Advisory Council. He has held leadership roles in the European XFEL Scientific Advisory Committee and the Komitee für Forschung mit Synchrotronstrahlung (KFS). His lab develops state-of-the-art setups for ultrafast X-ray scattering and holography.

Ohad Friedمشاهده پروفایل

دانشیار

• Computer Graphics
• Computer Vision
• Generative AI (GenAI)
• +۵ مورد دیگر

Ohad Fried is an Associate Professor of Computer Science at Reichman University. He was previously a postdoctoral research scholar at Stanford University under Prof. Maneesh Agrawala and completed his PhD with Prof. Adam Finkelstein as part of the Princeton Graphics group. He holds an M.Sc. in Computer Science and a B.Sc. in Computational Biology from The Hebrew University. His research lies at the intersection of computer graphics, computer vision, and Generative AI , focusing on tools, algorithms, and paradigms for photo and video editing and synthesis . His work has been widely recognized in top conferences including CVPR, SIGGRAPH, and ECCV, with recent contributions to tiled diffusion models, expressive 4D facial motion generation, and synthetic image detection. Ohad has received numerous awards, including the Israel Science Foundation personal research grant (2021) , the Outstanding faculty researcher at Reichman University (2022) , and the Siebel Scholar award (2017) . He has advised multiple students in research projects, and his work is covered by media outlets like Wired , The Washington Post , and CNN . Teaching roles include courses at Reichman University such as "GenAI for Games & Entertainment" and "Synthetic Media Detection", and at Stanford University "Computational Video Manipulation". Key Research Themes: Neural Rendering Diffusion Models 3D Facial Animation Image/Video Editing Media Forensics Scientific Awards: ISF Personal Grant (2021) Siebel Scholar (2017) Google PhD Fellowship (2014-2016) Gordon Y.S. Wu Fellowship (2012-2013) Excellence Scholarships

• Computer Vision
• Computer Graphics
• Machine Learning
• +۳ مورد دیگر

Gerard Pons-Moll is a Professor at the University of Tübingen, endowed by the Carl Zeiss Foundation, and heads the Emmy Noether independent research group 'Real Virtual Humans'. He is a core faculty member at the Tübingen AI Center, a senior researcher at the Max Planck Institute for Informatics (MPII), and faculty at the International Max Planck Research School for Intelligent Systems (IMPRS-IS) and the Saarland Informatics Campus. His research focuses on computer vision, graphics, and machine learning, particularly in creating virtual human models and analyzing human motion from video and sensor data. Education: PhD (with distinction) in 2014 from Leibniz University of Hannover, Master's in Telecommunications Engineering (Northeastern University, 2008), and B.S./M.Sc. in Telecommunications Engineering from the Technical University of Catalonia (2002–2008). Research Interests: 3D human modeling, pose estimation, human-object interaction, and applications in industry and research. His work emphasizes real-world applications like virtual avatars and motion capture systems. Awards: Emmy Noether Grant (2018), German Pattern Recognition Award (2019), Google Faculty Research Award (2019), and multiple best paper awards at top conferences (BMVC’13, Eurographics’17, 3DV'18, CVPR'20). Advising & Grants: Served as program chair of 3DV 2021, area chair for ECCV, CVPR, and IJCAI. Active in reviewing for DFG, ANR, and ISF. Supervises research in areas like neural rendering frameworks (Blendify) and synthetic data generation (STAGE). Labs/Teams: Leads the Emmy Noether group and collaborates with MPII, Tübingen AI Center, and IMPRS-IS on projects like XNect (real-time 3D motion capture) and Human 3Diffusion (avatar creation).

Christian Krupitzerمشاهده پروفایل

استاد

• Food Informatics
• Self-adaptive Software Systems
• Machine Learning
• +۴ مورد دیگر

Jun.-Prof. Dr. Christian Krupitzer is a Tenure Track Professor in Food Informatics at the University of Hohenheim's Institute of Food Science and Biotechnology, part of the Faculty of Natural Sciences. He leads the Department of Food Informatics and is a member of the Computational Science Hub (CSH). His research focuses on self-adaptive software systems, machine learning (especially edge computing), IoT technologies, and software engineering applied to food processing and agricultural systems. Education: PhD in Business Information Systems (Dr. rer. pol.), University of Mannheim (2018) M.Sc. and B.Sc. in Business Information Systems, University of Mannheim (2010–2012) High School Diploma (Abitur) from Wilhelmi-Gymnasium Sinsheim (2007) Research Interests: Krupitzer’s work integrates computational methods with food science, emphasizing adaptive systems for food quality monitoring, IoT in agriculture, and machine learning for predictive analytics. He explores edge computing’s role in real-time decision-making and secure group communication schemes for IoT networks. Publications: His recent work spans predictive maintenance in Industry 4.0, digital twins in food systems, and blockchain applications in supply chain authentication. The articles highlight trends in interdisciplinary approaches combining AI, IoT, and domain-specific challenges in food production and logistics. Awards: No scientific awards explicitly listed in the provided materials. Grants & Advising: While specific grants are unmentioned, his roles as department head and tenure-track professor suggest involvement in research funding. No formal advisee list provided, though his team includes postgraduate researchers like Dana Jox, Daniel Einsiedel, and others. Labs & Teams: Leads the Food Informatics department and collaborates with the Computational Science Hub. His team focuses on developing innovative solutions for food systems through computational methods.

• Literary Theory
• Cultural History
• German Literature
• +۱۰ مورد دیگر

Yashar Mohagheghi is a Researcher at the Department of German and General Literary Studies, RWTH Aachen University, where he has worked since 2018 under Prof. Dr. Caroline Torra-Mattenklott. His academic trajectory includes a postdoctoral fellowship at Bielefeld University's Graduate School of Linguistics and Literary Studies (2012–2017), a research stint at the Bibliothèque Nationale de France (2015), and a Junior Lecturer position at Johns Hopkins University (2011). His research interests span Literary Theory, Cultural History, and German Literature with specialized focus on Time Theory, Festival Culture, Material Philology, and Small Literary Forms. Mohagheghi's work bridges systematic analysis of concepts like Festkultur and Zeitlichkeit with historical investigations of Early Modern literature, Goethe-era writings, Aestheticism, and Modernism. His scholarship frequently examines intersections between material culture, sensory theory, and political communication across different historical periods. Mohagheghi's publications reveal a trajectory emphasizing temporal aesthetics in Hölderlin's work, material philology in 19th-century literature, and sociological analyses of Weimar Republic culture. His research demonstrates increasing engagement with ecological perspectives in literary studies, particularly regarding resource economies in book production and sustainability in literary materiality. Publikationspreis 2021 der Philosophischen Fakultät der RWTH Aachen Dissertationspreis 2018 der Kulturwissenschaftlichen Gesellschaft As an active academic organizer, Mohagheghi has co-chaired significant conferences including Wissenschaften des Konkreten (2023) and Ressource ‚Schriftträger‘ (2021), demonstrating leadership in contemporary literary theory discussions. His scholarly network extends across German, French, and American institutions, with particular strength in European literary theory and cultural history.

Jenelle Featherمشاهده پروفایل

استادیار

• Neuroscience
• Cognitive Science
• Artificial Intelligence
• +۷ مورد دیگر

Jenelle Feather is an Assistant Professor at Carnegie Mellon University, affiliated with the Neuroscience Institute and Psychology Department . She leads the Laboratory for Computational Perception , focusing on neural activity patterns in perception and cognition through computational modeling, behavioral studies, and brain measurements. Education : PhD in Brain and Cognitive Science (2022), MIT Prior Affiliations : Research Fellow, Flatiron Institute Center for Computational Neuroscience Her research spans auditory and visual perception , comparing artificial neural networks with biological systems. Recent studies include model metamers (2023) and neural population geometry (2021). Key software contributions include chcochleagram (PyTorch) and tfcochleagram (TensorFlow) for auditory signal processing. Key Awards : Friends of McGovern Institute Graduate Fellow DOE Computational Science Graduate Fellow She advises students through multiple programs and develops open-source tools for auditory neuroscience.

• Medical Image Computing
• Tumor Growth Modeling
• Computational Physiology
• +۳ مورد دیگر

Bjoern Menze is a Professor and Rudolf Mößbauer Tenure Track Chair at the Technical University of Munich (TUM), leading the Image-based Biomedical Modeling Group within the Munich School of Bioengineering. His research focuses on medical image computing, tumor growth modeling, and computational physiology, with applications in clinical neuroimaging and personalized radiotherapy design. He holds a Ph.D. in Computer Science from Heidelberg University and has held positions at ETH Zurich, INRIA Sophia Antipolis, MIT, and Harvard Medical School. His academic journey includes a postdoc at MIT’s CSAIL and Harvard Medical School, followed by roles at ETH Zurich and INRIA. His work bridges biomedical imaging with machine learning, emphasizing model-driven analysis of physiological processes. He has been a visiting professor at Maastricht University and contributes to initiatives like the Center for Translational Cancer Research at TUM. Key research areas include tumor growth modeling, quantitative imaging biomarkers, and integrating mathematical models with clinical data. His awards include the MICCAI Young Scientist Award (2014), Leopoldina Fellowship (2009), and DFG Research Fellowship (2008). He advises on medical AI, leads interdisciplinary projects, and publishes extensively in top journals like Nature Neuroscience and IEEE Transactions on Medical Imaging. His lab’s work spans applications such as glioblastoma radiotherapy optimization, whole-body bone lesion detection, and neural connectivity imaging. Collaborations include institutions like Harvard, MIT, and ETH Zurich. He emphasizes translating computational methods into clinical practice for personalized healthcare solutions.