جست‌وجوی استاد و پژوهشگر

Peter K. Allenمشاهده پروفایل

استاد

• Robotics
• Computer Vision
• Medical Robotics
• +۶ مورد دیگر

Peter K. Allen is a Professor of Computer Science at Columbia University's School of Engineering and Applied Science, with a career spanning over three decades in robotics research. His work focuses on robotic grasping , 3D vision and modeling , and medical robotics , where he has made significant contributions to autonomous manipulation and sensor integration. Current affiliation: Columbia University Robotics Lab Academic rank: Professor Key research areas: Robotics, Computer Vision, Artificial Intelligence Education A.B. in Mathematics-Economics from Brown University M.S. in Computer Science from University of Oregon Ph.D. in Computer Science from University of Pennsylvania (recipient of CBS Foundation Fellowship, Army Research Office Fellowship) Research Interests Allen's research bridges fundamental robotics challenges with applied domains. His work on robotic grasping explores low-dimensional subspaces and semantic task suitability, while 3D vision contributions include illumination coherence and texture registration methods. In medical robotics , he develops surgical imaging tools and BCI-enabled grasping systems. Recent publications show trends in: Deep learning for robotic manipulation (2017-2022) Human-robot interaction through BCI and augmented reality Deformable object manipulation (garments, thin shells) Multi-modal sensing (vision-tactile fusion) Scientific Recognition NSF Presidential Young Investigator Award Best Student Paper Award (2007) for collaborative work Over 30 years of continuous funding from NSF, Army Research Office, and medical grants Teaching and Mentorship He has taught graduate courses in robotics (COMS 4733/6731) since 2010, emphasizing hands-on projects with advanced platforms like Baxter, PR2, and Fetch robots. His lab provides immersive training in: 3D photography Humanoid robotics Autonomous navigation Grasp planning

Boris Kausمشاهده پروفایل

استاد

• Geodynamics
• Lithospheric Deformation
• Numerical Modeling
• +۵ مورد دیگر

Boris Kaus is a Full Professor and Chair of Geophysics and Geodynamics at the Institute of Geosciences, Johannes Gutenberg University Mainz, Germany. His research focuses on understanding geological processes from grain scale to planetary scale using mathematical and numerical models. Funded by the German Research Foundation, European Research Council, and BMBF, his work spans lithospheric deformation, melt migration, fold-and-thrust belts, and high-performance computing applications in geosciences. His research interests center on geodynamic modeling of lithospheric processes, including subduction zones, mantle convection, and crustal deformation. Kaus develops novel numerical approaches to simulate complex geological phenomena, with emphasis on coupling between erosion, lithosphere dynamics, and mantle flow. His group creates specialized software for high-performance computing systems to tackle multi-scale geophysical problems. His scientific awards include the Paul Niggli Medal, EGU Arne Richter Award, multiple ERC grants (Starting, Proof-of-Concept, Consolidator), and the Carl Friedrich Gauss Lecturer honor. He has received recognition for editorial contributions including G-Cubed's Excellence in Refereeing award. ERC Consolidator Grant MAGMA (2018-2023) ERC Proof of Concept Grant SALTED (2016-2017) ERC Starting Grant MODEL (2010-2015) John von Neumann Excellence Project for HPC ETH Medal for Ph.D. thesis Kaus actively supervises graduate students and leads research projects funded by major European and German agencies. His group develops open-source software like GeophysicalModelGenerator.jl and maintains strong collaborations with international institutions including ETH Zürich and USC. Current projects focus on magma dynamics, lithospheric shear localization, and the development of advanced numerical methods for geodynamic simulations. The research group operates within the Geodynamics & Geophysics team at JGU Mainz, utilizing high-performance computing resources and collaborating with multiple European research initiatives including IMPRS and FORTHEM networks. Their laboratory specializes in numerical modeling of Earth systems with applications to tectonics, volcanology, and crustal evolution.

• Augmented Reality
• Virtual Reality
• Biophilic Design
• +۳ مورد دیگر

Michele Gattullo serves as an Assistant Professor within the Department of Mechanics, Mathematics & Management at the Polytechnic University of Bari, Italy, specializing in design methods for industrial engineering (ING-IND/15). His research bridges cutting-edge extended reality technologies with practical industrial applications, focusing on human-centered solutions for manufacturing, maintenance, and workplace design. Dr. Gattullo's research portfolio centers on Augmented Reality, Virtual Reality, and Biophilic Design, with significant contributions to Human-Computer Interaction in industrial contexts. He investigates how nature-inspired elements in virtual workspaces enhance employee well-being and productivity, while simultaneously developing practical AR tools for assembly guidance, technical documentation, and maintenance support. His work uniquely integrates ergonomics, cognitive psychology, and industrial engineering to optimize human-technology interaction in complex production environments. Analysis of his 15 most recent publications reveals two dominant research trajectories: biophilic design frameworks for virtual/metaverse workspaces (2023-2025) and industrial AR authoring methodologies. The biophilic stream establishes evidence-based guidelines for digital nature integration, while the AR stream delivers validated tools like ADAM and minimal AR approaches that streamline technical documentation creation. Both trajectories emphasize user experience validation through rigorous industrial studies, demonstrating strong interdisciplinary impact across computer science, industrial engineering, and environmental psychology. Scientific Awards: No awards or honors were documented in the available sources. Advising and Grants: The provided materials contain no information regarding graduate student supervision, research grants, or funding sources. His academic profile emphasizes publication output over mentoring activities or project financing details. Laboratories and Teams: While Dr. Gattullo's research involves advanced XR technologies, the source text does not specify laboratory facilities, research groups, or collaborative teams associated with his work at Politecnico di Bari.

Peter Buiمشاهده پروفایل

استاد آموزشی

• Systems Programming
• Operating Systems
• Parallel Computing
• +۶ مورد دیگر

Peter Bui is a Teaching Professor in the Computer Science and Engineering department at the University of Notre Dame , located within the College of Engineering. He teaches courses such as Data Structures, Systems Programming, and Ethical and Professional Issues, while also managing the core Elements of Computing programming sequence for the Computing & Digital Technologies minor. Education: Ph.D. in Computer Science and Engineering from University of Notre Dame (2012) His research interests span systems programming, operating systems, parallel computing, cloud computing, distributed computing, programming languages, compilers, and web services . He actively integrates these domains into his teaching and extracurricular work with the Linux Users Group. Recent publications highlight his work in distributed computing frameworks , including the development of tools like WorkQueue and Madeup for scalable scientific workflows and 3D printing integration. Projects such as ROARS and Weaver demonstrate his focus on robust data management and workflow automation. Outside academia, he stewards the Linux Users Group , engages with open-source communities, and balances personal interests like gaming in RuneScape with family time.

Michał Paweł Michalakمشاهده پروفایل

استادیار

• computational geometry
• machine learning in Earth sciences
• statistical methods in Earth sciences
• +۲ مورد دیگر

Michał Paweł Michalak is an Assistant Professor at AGH University of Science and Technology in Kraków, affiliated with the Faculty of Geology, Geophysics and Environmental Protection and Department of Geoinformatics and Applied Informatics. His research spans computational geometry in geological modeling, machine learning applications in Earth sciences, statistical epidemiology, and ecclesiological dynamics. Doctoral degree from University of Silesia in Katowice Developed GeoAnomalia software suite combining C++, R, and ParaView Created unbiased risk metrics (WCSIR) for infectious disease surveillance Research focuses on: Subsurface geological modeling using combinatorial algorithms and machine learning; Spatial epidemiology emphasizing testing heterogeneity bias; Ecclesiological dynamics analyzing factional theological interactions. His 2020/37/N/ST10/02504 grant project received 'very good' evaluation for developing angular distance metrics in geological contacts. Scientific contributions include: 2025 Solid Earth paper on fault-related structure detection 2025 Frontiers in Public Health work on global pandemic risk evaluation 2023 AGH Rector award recipient Developer of open-source geological analysis tools Collaboration network includes Harvard University, Technische Universität Freiberg, and University of Texas at Austin. Currently teaching GIS modeling, optimization methods, and geoinformatics systems. Maintains a personal website with open data access.

Jina Kangمشاهده پروفایل

استادیار

• Educational Technology
• Immersive Learning Environments
• Collaborative Learning
• +۳ مورد دیگر

Jina Kang is an Assistant Professor in the Department of Curriculum & Instruction at the University of Illinois Urbana-Champaign , with an affiliate appointment at the Siebel Center for Design . Her research focuses on immersive technology-supported learning environments , collaborative problem-solving dynamics , and educational data mining for understanding multimodal engagement in science education. Recent publications examine embodied cognition in STEM through gesture-based learning simulations, joint attention dynamics in astronomy VR environments, and systematic reviews of immersive technology applications in collaborative education. Her work integrates XR platforms , Bayesian knowledge tracing , and multimodal behavioral analysis to enhance science learning outcomes. She teaches graduate courses including CI 539: Introduction to Educational Data Mining and CI 489: Educational Technology Capstone Course , where students develop technology-supported learning activities using studio-based approaches.

Guillermo Gallegoمشاهده پروفایل

استاد

• Robotics
• Computer Vision
• Event-based Vision
• +۵ مورد دیگر

Guillermo Gallego is a Professor of Robotic Interactive Perception at the Faculty of Electrical Engineering and Computer Science , Technische Universität Berlin , holding the Einstein Center Digital Future (ECDF) Professorship since 2019. His research bridges robotics , computer vision , and applied mathematics , focusing on optimization methods for interdisciplinary imaging and control problems. Education : PhD in Electrical and Computer Engineering (Georgia Tech, 2011), MS in Mathematics (Georgia Tech, 2009), MS in Electrical Engineering (Georgia Tech, 2007), MS in Mathematical Engineering (Universidad Complutense de Madrid, 2005). Gallego's work explores event-based vision to enhance robot perception through low-latency sensing and real-time 3D reconstruction . He previously held postdoctoral positions at the Institute of Neuroinformatics (University of Zurich/ETH Zurich) and Technical University of Madrid (Marie Curie Experienced Researcher). His interdisciplinary projects span applications in ocean remote sensing , autonomous driving , and space exploration . Key scientific awards include the Fulbright Fellowship (2005-2010) and Marie Curie Experienced Researcher (2011-2014). His recent publications focus on event camera algorithms for optical flow , SLAM , and noise estimation , reflecting his leadership in event-based vision research. Collaborations include institutions like University of Zurich , Georgia Tech , and University of Pennsylvania . Research Grants : Funded through ECDF and Marie Curie programs. Labs : Affiliated with the Einstein Center Digital Future and Institute of Neuroinformatics (Zurich/ETH Zurich).

• Perceptually guided graphics
• Virtual characters and crowds
• Virtual reality
• +۴ مورد دیگر

Cathy Ennis is an Assistant Professor in the Department of Computer Science at Maynooth University, Ireland, specializing in perceptually guided graphics and virtual reality. She is actively involved in research and teaching, with affiliations to the ADAPT Centre and D-REAL SFI Centre for Research Training. Education: BEng in Electronic Engineering, Maynooth University MSc in Cognitive Science, University College Dublin PhD in Computer Graphics, Trinity College Dublin PG Dip in Higher Education Teaching and Learning, DIT Research Interests: Dr. Ennis's research centers on creating realistic virtual humans and crowds, exploring multisensory perception in VR, and applying these technologies in serious games and interactive systems. Her work integrates AI, HCI, and immersive technologies to enhance user engagement and learning. Her recent publications reflect a strong focus on virtual character realism, VR-based education, and machine learning applications in animation and interaction. Notable themes include speech-animation realism, cultural VR experiences, and reinforcement learning for character control. Scientific Awards: Best Paper Award, IEEE VR 2022 Teaching and Supervision: Dr. Ennis currently teaches CS401 (Machine Learning and Neural Networks) and CS261 (Multimedia Technology). She is actively seeking PhD students and collaborators interested in VR, games, and virtual characters, particularly using machine learning for gesture generation and engagement. Labs and Teams: She is a Funded Investigator with the ADAPT Centre and D-REAL SFI Centre for Research Training, contributing to interdisciplinary research in AI, HCI, and immersive technologies.

• Case-Based Reasoning (CBR)
• Artificial Intelligence
• Multi-Agent Systems
• +۴ مورد دیگر

Dr. Pascal Reuss is a Researcher at the Intelligent Information Systems (IIS) Division within the Institute of Computer Science , University of Hildesheim . His work focuses on Case-Based Reasoning (CBR) systems, Multi-Agent Systems , and Knowledge Management applications. Active in CBR framework development and game-based AI research Teaching Computer Science III (Databases) for winter 2025/26 Participating in university sustainability initiatives like Stadtradeln 2024/25 Reuss contributes to AI education through practical implementations in gaming environments and has developed visualization tools for CBR agent behavior. His research spans multi-agent collaboration , dynamic case bases , and domain-specific language implementations for knowledge maintenance. Notable contributions include: Co-developing the FEATURE-TAK framework for knowledge extraction Designing case factories for distributed CBR systems Implementing finite state machines for tactical game agents Creating CBR-based fitness planning systems His work appears in various CBR and Game Development publications from 2011-2024. The research demonstrates practical applications of CBR in aircraft maintenance diagnostics , training plan generation , and educational technology contexts.

Leif Kobbeltمشاهده پروفایل

استاد

• Computer Graphics
• Geometry Processing
• Interactive Visualization
• +۳ مورد دیگر

Leif Kobbelt serves as a University Professor at RWTH Aachen University, leading the Computer Graphics Group within the Department of Computer Science (Informatik 8). His research focuses on advancing geometry processing, interactive visualization, and computer graphics through innovative algorithmic solutions and interdisciplinary collaborations. Professor Kobbelt's research program centers on geometry acquisition and processing, with significant contributions to mesh generation, surface reconstruction, and neural rendering techniques. His work bridges theoretical geometry with practical applications in computer vision, photo-realistic image synthesis, and multimedia data transmission, often involving collaborations with industry partners and international research teams funded by DFG and EU sources. Recent publications (2023-2025) reveal a strategic integration of deep learning with traditional geometry processing, particularly in Gaussian splatting for real-time rendering, NeRF-based 4D content generation, and robust mesh Boolean operations. His group maintains leadership in quad mesh optimization and surface mapping while expanding into immersive visualization techniques for complex data analysis. The group has earned recognition through prestigious awards: Günter Enderle Best Paper Award at Eurographics 2023 Best Paper Award (1st place) at Symposium on Geometry Processing 2022 Honorable Mention for Best Paper at ACM Symposium on Virtual Reality Software and Technology Funding from Deutsche Forschungsgemeinschaft and European Union programs supports the group's research infrastructure and international collaborations. The team actively supervises graduate theses while developing open-source software tools that translate theoretical advances into practical industry applications, particularly in digital fabrication and immersive visualization systems. The Computer Graphics Group operates as a central hub for visual computing research at RWTH Aachen, maintaining strong ties with both academic institutions and technology companies. Their recent work on virtual reality educational tools and high-fidelity 3D reconstruction systems demonstrates commitment to knowledge transfer and real-world impact beyond traditional publication venues.

• Systems Biology
• Genomics
• Post-transcriptional Gene Regulation
• +۳ مورد دیگر

CHEN Wei is a Chair Professor at the Department of Biology, School of Life Sciences, Southern University of Science and Technology (SUSTech), Shenzhen, China. He holds a Ph.D. from the Max Planck Institute for Molecular Genetics (2006) and previously served as a Full Professor (W3) at the Max-Delbrück Center for Molecular Medicine and Charité – Universitätsmedizin Berlin (2015-2016). Prior to joining SUSTech, he led research groups at prestigious German institutions, contributing to large-scale genome centers and the Berlin Institute of Health. Education : Ph.D. (2006, Max Planck Institute), M.S. (2002, Sichuan University), B.S. (1993, Xiamen University) His research focuses on systems biology and genomics, particularly post-transcriptional gene regulation mechanisms and their roles in human diseases. His lab integrates next-generation sequencing technologies with computational approaches to study non-coding RNA functions, alternative splicing, and chromatin dynamics. Key projects include CRISPR-based functional studies, 3D genome analysis, and RNA editing in neurological and metabolic disorders. Recent publications highlight his work in Drosophila developmental genomics, chloroplast translation control, and cancer biology. The 2025 study on spatiotemporal multi-omics in Drosophila and 2024 articles on MatK's role in tRNA splicing and CRISPR-activated transcriptional regulation exemplify his interdisciplinary approach. Earlier works (2023-2022) address immune cell trafficking, alternative polyadenylation, and chromatin remodeling in cancer metastasis. At SUSTech, he leads a team with 4 research assistant professors, 2 postdoctoral fellows, 3 research assistants, and 7 graduate students. His lab has secured significant funding from EU and German agencies (€7M+), though specific awards are not detailed in the provided text. Teaching responsibilities include General Biology and Principles of Cell Biology.

Alison Langmeadمشاهده پروفایل

دانشیار بالینی

• Digital Humanities
• Digital Art History
• Visual Culture Studies
• +۳ مورد دیگر

Alison Langmead serves as Clinical Associate Professor and Director of the Visual Media Workshop in the Department of Art History and Architecture at the University of Pittsburgh's Dietrich School of Arts and Sciences, with a joint appointment as Associate Professor in the School of Computing and Information. Her work bridges digital humanities, visual culture studies, and information management history through mindful technological application. Education: PhD, Columbia University MLIS, University of California at Los Angeles Langmead's research centers on the intersection of digital methods and visual/material culture, examining historical information practices alongside contemporary computational approaches. She pioneers sustainable digital scholarship frameworks while critically analyzing AI's role in art historical connoisseurship and cultural preservation. Her work emphasizes intentional technology use that respects scholarly integrity and humanistic values. Recent publications reveal consistent focus on collaborative digital art history methodologies, computational modeling of visual data, and sustainable infrastructure development. Key trends include network analysis applications, role-based collaboration frameworks, and ethical considerations in AI-driven art scholarship, demonstrating evolution from technical implementation toward systemic sustainability and human-centered design. Scientific Awards: Award for Excellence in Graduate Mentoring, Dietrich School of Arts and Sciences, University of Pittsburgh, May 2023 Langmead actively mentors graduate students through the DHRX initiative while securing significant research funding. Her current grants include 'Teaching Art History with AI' (PI, 2023-present), 'InfoEco Cookbook' (2021-2022), and 'The Socio-Technical Sustainability Roadmap' (PI, 2015-2018, ongoing dissemination), reflecting her commitment to practical digital scholarship frameworks. As Director of the Visual Media Workshop, Langmead cultivates interdisciplinary collaboration across campus, creating spaces where faculty and students develop innovative digital research tools while critically examining technology's role in scholarly practice and cultural preservation.

Daragh Byrneمشاهده پروفایل

عضو هیئت علمی

• Human-Computer Interaction
• Internet of Things (IoT)
• Tangible Interaction Design
• +۴ مورد دیگر

Daragh Byrne is an Associate Teaching Professor at the Carnegie Mellon University School of Architecture , with courtesy appointments in the School of Design and Human-Computer Interaction Institute (HCII) . Previously an Assistant Research Professor at Arizona State University’s School of Arts, Media and Engineering, he manages the NSF-funded XSEAD project and leads MakeSchools , a catalog of making practices in higher education. PhD in Digital Media from Dublin City University (2011) M.Res. in Design and Evaluation of Advanced Interactive Systems from Lancaster University B.Sc. in Computer Applications from Dublin City University His research explores experiential media systems through Internet of Things and tangible interaction design , focusing on how computational tools can capture human experience and enable multidisciplinary collaboration. Key projects include Sentient Concrete (thermochromic architectural surfaces) and Spooky Technology (speculative design around invisible technologies). He has developed CMU’s Designing for the Internet of Things course since 2016, creating hands-on curricula for connected product design. Recent publications examine creative physical computing education , AI-driven documentation systems , and XR-enabled skill training . Awards include multiple CMU research grants and the CHI 2018 Best Paper Award . He actively advises PhD and Masters students in Computational Design, emphasizing human-centered design and speculative technology research .

Matteo Dal Peraroمشاهده پروفایل

دانشیار

• Computational Biophysics
• Molecular Modeling
• Structural Biology
• +۵ مورد دیگر

Matteo Dal Peraro is an Associate Professor at École polytechnique fédérale de Lausanne (EPFL) in the School of Life Sciences, where he leads the Laboratory for Biomolecular Modeling (LBM) within the Interfaculty Institute of Bioengineering (IBI). He also holds significant administrative roles as Head of IBI-SV Administration and Co-Director of IBI-STI Administration, demonstrating his leadership across both the School of Life Sciences and School of Engineering. His research bridges computational approaches with experimental validation to understand complex biological systems at multiple scales. His educational background includes a B.S. and M.S. in Physics from the University of Padua (2000), followed by a Ph.D. in Biophysics from the International School for Advanced Studies (SISSA) in Trieste (2004). He then completed postdoctoral training at the University of Pennsylvania under Professor M. L. Klein before joining EPFL as a Tenure Track Assistant Professor in late 2007. Dal Peraro's research focuses on computational biophysics and multiscale modeling of biological systems, with particular emphasis on membrane-protein interactions, nanopore sensing technologies, and structural biology. His work spans fundamental molecular mechanisms to applied educational technologies, demonstrating a commitment to both scientific discovery and knowledge dissemination. He has made significant contributions to understanding protein-membrane interactions, antibiotic resistance mechanisms, mitochondrial disorders, and viral pathogenesis through advanced computational approaches. His publication record shows a strong trend toward integrating augmented and virtual reality technologies with molecular modeling, exemplified by his development of the moleculARweb platform for chemistry and structural biology education. His research spans computational methods development, structural characterization of biomolecules, membrane biophysics, and applications to medically relevant problems including antibiotic resistance and neurodegenerative disorders. This interdisciplinary approach connects fundamental biophysical principles with practical applications in medicine and education. Dal Peraro has mentored numerous doctoral students through EPFL's PhD programs, particularly in Computational and Quantitative Biology. His leadership extends to serving on PhD program committees and directing research groups focused on computational molecular biology. He has established collaborations across multiple disciplines, facilitating integrative approaches to complex biological problems. He leads the Laboratory for Biomolecular Modeling (LBM), which develops and applies computational methods to study biological systems at multiple scales. The lab bridges molecular simulations with experimental validation, creating a synergistic approach to understanding complex biological phenomena. Dal Peraro's team has made significant contributions to membrane biophysics, protein folding, and the development of educational technologies that make structural biology accessible through augmented reality platforms.

Kobus Barnardمشاهده پروفایل

استاد

• Computer Vision
• Machine Learning
• Scientific Applications
• +۳ مورد دیگر

Kobus Barnard is a Professor in the Department of Computer Science at the University of Arizona, with his office located in GS 708. His research bridges computer vision, machine learning, and interdisciplinary scientific applications across diverse domains. Education: Ph.D. from Simon Fraser University (1999) His research interests focus on extracting meaningful insights from complex data through computer vision and probabilistic modeling. Key areas include machine learning for environmental monitoring (flood detection, plant disease analysis), social dynamics (interpersonal coordination, emotional coregulation), astronomy (transient classification), and multimodal learning (visual-linguistic integration). His work consistently applies deep learning to real-world problems requiring high-resolution data interpretation. Analysis of his 2022-2025 publications reveals three dominant trends: (1) Environmental applications using satellite imagery for flood mapping and agricultural monitoring, (2) Cognitive modeling of human teams and emotional dynamics through probabilistic frameworks, and (3) Astronomical data analysis leveraging host galaxy properties for transient classification. These threads demonstrate his commitment to solving practical scientific challenges through computational innovation. While scientific awards aren't documented in available sources, his leadership in projects like FloodPlanet and ToMCAT indicates significant contributions to data infrastructure. His advising and grant activities remain unreported in the source material, though his extensive interdisciplinary collaborations suggest substantial mentorship impact. Barnard's work operates at the intersection of multiple scientific communities, evidenced by applications spanning neuroscience, agriculture, astronomy, and social science. His current focus on high-resolution data fusion and multimodal modeling positions him at the forefront of real-world AI deployment.