جست‌وجوی استاد و پژوهشگر

Luis Arturo Cavazos Queroمشاهده پروفایل

استادیار

• Human–Computer Interaction
• Accessibility
• Virtual Reality / Augmented Reality
• +۳ مورد دیگر

Luis Arturo Cavazos Quero is an Assistant Professor in the Department of Computer Science and Engineering at Sejong University , South Korea. His research agenda centers on Human–Computer Interaction , accessibility for visually impaired users , and multimodal interaction technologies . Education: Ph.D. in Computer Science, Sungkyunkwan University (2022) M.S. in Computer Science, Sungkyunkwan University (2015) B.S. in Computer Science, Tecnológico de Monterrey (ITESM) (2010) Research Focus: Dr. Cavazos Quero designs and evaluates interactive systems that enable people with visual impairments to access art, education, and mobility. His projects include multimodal interfaces for artwork exploration, voice-based navigation aids, tactile map applications, and Braille text-entry tools for mobile devices. Recent Publications Trend: Since 2021 his output has concentrated on two parallel tracks: (1) assistive technologies that merge tactile, auditory, and olfactory feedback for non-visual art appreciation, and (2) robotics and data security —including quadruped robot control and reversible data-hiding algorithms—showing a broad yet accessibility-driven research portfolio. Scientific Awards: No specific awards are listed in the provided materials. Advising & Grants: Current information on funded projects or doctoral students is not available in the supplied text. Labs & Teams: He completed a postdoctoral fellowship at the Human–Computer Interaction Laboratory, Ewha Womans University (2022–2023) and now leads research activities within his department at Sejong University.

Gonzalo Besuievskyمشاهده پروفایل

دانشیار

• Computer graphics
• Global illumination
• Radiosity
• +۴ مورد دیگر

Gonzalo Besuievsky is Associate Professor at the Department of Computer Science and Applied Mathematics of the University of Girona , Spain. He leads research on physically-based rendering and global illumination, with particular emphasis on Monte-Carlo methods and dynamic radiosity environments. Education: PhD in Computer Science, Universitat Politècnica de Catalunya , 2001 — Dissertation: "A Monte Carlo Approach for Animated Radiosity Environments" Research Interests: His work spans several inter-related domains: Global Illumination & Radiosity: developing algorithms for realistic light transport in synthetic scenes. Monte Carlo Techniques: adaptive and hierarchical sampling to accelerate rendering. Dynamic Environments: efficient update schemes for animated lighting and moving light sources. Daylighting Simulation: integrating sunlight models into architectural 3-D workflows. Motion Blur & Temporal Coherence: novel methods to render motion-blurred radiosity images. Publication Trends: Across his 1993–2006 publications, a clear evolution is visible from foundational stochastic ray-tracing work toward sophisticated Monte-Carlo radiosity frameworks that handle dynamic lighting, daylighting, and frame-to-frame coherence for animations. Labs & Groups: He is affiliated with the Girona Graphics Group , a research team devoted to advanced graphics and visualization technologies.

Pete Willemsenمشاهده پروفایل

استاد

• Virtual Reality (VR)
• Augmented Reality (AR)
• Mixed Reality (MR)
• +۷ مورد دیگر

Pete Willemsen is a Professor and Department Head in the Department of Computer Science at the University of Minnesota Duluth, Swenson College of Science and Engineering. His research focuses on urban microclimate simulation, virtual reality education, and human-computer interaction. Current research includes One Night in Tarrytown (interdisciplinary VR learning environments) Development of Quick Environmental Simulation (QES) for urban wind and pollution modeling Investigation of radiance field content generation for VR applications Prior projects have explored: Locomotion mechanics in VR training systems GPU-accelerated environmental simulations Human spatial perception in virtual environments Low-cost Kinect-based tracking systems Collaborations span multiple disciplines including Communications, Digital Arts, and Mechanical Engineering. Current students include Asif Sijan (VR content generation), Christianah Adigun (spatial cognition), and Noah Miller (VR controller ergonomics).

Fenghui Yaoمشاهده پروفایل

استاد

• Image Processing
• Robotics
• UAVs/UGVs
• +۱ مورد دیگر

Dr. Fenghui Yao is a Professor of Computer Science and Director of Graduate Studies at Tennessee State University's Department of Computer Science. His academic journey includes positions at Kyushu Institute of Technology, University of East Asia, and Shimane University prior to joining TSU in 2004. Education background: Ph.D. in Computer Engineering, Kyushu Institute of Technology, Japan (1992) M.E. in Computer Engineering, Kyushu Institute of Technology, Japan (1988) B.A. in Electronic Engineering, Dalian Maritime University, China (1984) Research focuses on interdisciplinary applications in: Image Processing : Developing algorithms for real-time target detection and calligraphy analysis Robotics : Designing systems for infrastructure inspection and cultural preservation Parallel Architecture : Exploring quantum-dot cellular automata for nanosensor data processing Publications demonstrate consistent focus on hardware-software integration, with recent work in nanotechnology (2014) complementing earlier robotics research (2003-2010). His 2004 papers on robotic calligraphy represent innovative human-robot interaction studies. Grant involvement includes multi-year sensor systems research as Co-PI: Cross Layers Decision Making and Fusion Models for Automated Sensor Exploitation ($334,678; 2013-2018)

Gilbert Bernsteinمشاهده پروفایل

استادیار

• Computer Graphics
• Programming Languages
• High-Performance DSLs
• +۷ مورد دیگر

Gilbert Bernstein is an Assistant Professor in the Computer Science & Engineering department within the College of Engineering at the University of Washington. His research bridges computer graphics and programming languages, with a focus on high-performance domain-specific languages. Previously, he was a post-doctoral scholar at UC Berkeley and MIT working with Jonathan Ragan-Kelley, and received his PhD from Stanford University under Pat Hanrahan. His research interests span Computer Graphics, Programming Languages, High-Performance DSLs, Physical Simulation, Geometry & Topology, Differentiable Programming, Hardware DSLs, Tools for Artists, Fabrication, and Human-Computer Interaction. Bernstein develops languages and compilers that enable efficient computation for creative applications, physical simulations, and graphics rendering systems. His recent publications reveal strong trends in differentiable programming for graphics applications, domain-specific languages for hardware acceleration, and computational approaches to traditional crafts like quilting and knitting. His work consistently combines formal language theory with practical applications in graphics and fabrication. Bernstein actively mentors students across multiple institutions including current advisees Felix Hahnlein (UW Postdoc), Ryan Zambrotta (UW PhD), Haoran Peng (UW PhD), and previous students including Alex Reinking (UC Berkeley PhD 2022, now at Qualcomm) and MacKenzie Leake (Stanford PhD 2021, now at Adobe Research). His lab works on diverse projects including debugging CAD programs, compilers for finite element methods, semantics for knitting machines, algebraic scheduling of tensor programs, and exocompilers for hardware accelerators. Bernstein also collaborates on DSLs for networking, Counterstrike bots, gradient-based optimization, memory management, hardware design, and garment design tools.

Sang-Hoon Kimمشاهده پروفایل

دانشیار

• Operating Systems
• Memory Systems
• Storage Systems
• +۴ مورد دیگر

Sang-Hoon Kim is an Associate Professor in the Department of Software and Computer Engineering and Department of Artificial Intelligence at Ajou University, South Korea. He leads the Systems Software Lab (Paldal Hall 1004-2) and maintains active collaborations with Virginia Tech as a Visiting Scholar since August 2024. His academic journey includes a Ph.D. in Computer Science from KAIST (2016) under advisors Seungryoul Maeng and Jin-Soo Kim, and a B.S. in Computer Science from KAIST (2002). His research spans operating systems, memory management, and storage systems with focus on mobile platforms, heterogeneous architectures, and SSD technologies. Key interests include memory fragmentation control , distributed thread execution , key-value storage optimization , and resource disaggregation . His work bridges theoretical innovation with practical system implementations, particularly for mobile and datacenter environments. Kim's publication portfolio shows consistent output in top-tier venues including USENIX FAST, VLDB, ICDCS, and ASPLOS. His research demonstrates evolution from mobile memory management (2015-2017) toward distributed systems and hardware-aware software (2019-present), with recent emphasis on resource-disaggregated environments and heterogeneous-ISA computing. The 2024 Best Paper Award at USENIX FAST highlights his impact in storage systems research. Best Paper Award at USENIX FAST'24 Multiple patents including US-9588912B2 for memory control He directs significant research projects funded by ETRI, NRF, and US ONR, including current work on memory-centric computing systems (2020-2023) and disaggregated non-volatile memory systems using RDMA (2018-2020). His Systems Software Lab maintains strong industry partnerships with Samsung Electronics and NHN, with prior projects improving Android memory management and developing SSD-based storage systems for large-scale internet services.

• Industrial Engineering
• Operations Research
• Artificial Intelligence
• +۵ مورد دیگر

Dr. James Curry serves as Department Chair and Associate Professor in the Department of Industrial and Systems Engineering at Lamar University's College of Engineering, while also directing Online Programs and Outreach for the College. His leadership drives the development of innovative engineering education pathways and industry-focused research initiatives. Dr. Curry earned his Ph.D. in Industrial Engineering from Texas A&M University, complemented by an M.S. in Operations Research and Industrial Engineering and a B.S. in Mechanical Engineering from the University of Texas. His research integrates Logistics and Scheduling, Software Development, and Natural Language Generation with practical applications in Supply Chain Management and Optimization. Current work focuses on marine safety culture assessment, where he develops computational frameworks for processing safety data and generating natural language reports. This bridges theoretical optimization with real-world industrial engineering challenges, particularly in offshore energy systems. Analysis of Dr. Curry's 15 most recent publications reveals a strategic shift from pure algorithm development toward interdisciplinary applications. Recent work emphasizes safety culture assessment toolkits for offshore industries and machine learning applications in environmental modeling, demonstrating growing collaboration between engineering education, marine safety, and data science domains. Dr. Curry's scientific recognition includes: Anita Riddle Excellence in Engineering Teaching Fellowship As an active mentor, he has guided 14 graduate students through doctoral and master's research while securing $1.5+ million in funding across 10 projects. His grant portfolio spans NSF education initiatives, National Academies safety research, and industry partnerships with American Bureau of Shipping, focusing on practical solutions for marine safety and engineering education innovation. The Mariner Safety Research Initiative processes over 100,000 safety events from international marine organizations, developing assessment toolboxes that translate complex data into actionable safety improvements. This lab serves as a nexus for students to gain hands-on experience with industry-standard safety systems and international collaboration networks.

Marie-Christine ROUSSETمشاهده پروفایل

استاد

• Knowledge Representation
• Information Integration
• Ontology-based data access
• +۷ مورد دیگر

Marie-Christine ROUSSET is a Professor of Computer Science at the University of Grenoble Alpes (UGA) in France, where she is a member of the LIG (Laboratoire d'Informatique de Grenoble) in the SLIDE group. Previously affiliated with Paris-Saclay (LRI), she has established herself as a leading researcher in Knowledge Representation and Information Integration. She holds the distinguished position of Senior member of the Institut Universitaire de France (IUF) (2011-2016, renewed for 2016-2021) and serves as co-responsible for the chair Explainable and Responsible AI within MIAI Grenoble Alpes. Her research focuses on ontology-based data access, logic-based mediation between distributed data sources, query rewriting using views, data linkage, and distributed reasoning for the Semantic Web. She skillfully combines artificial intelligence and database techniques to address complex information integration challenges, with applications spanning biomedical informatics, educational technology, and trustworthy AI. Her work demonstrates consistent innovation from foundational research to practical implementations, as evidenced by her co-authorship of the book 'Web Data Management' published by Cambridge University Press. Professor ROUSSET's recent publications (2019-2022) reveal a growing emphasis on data privacy, RDF graph anonymization, and interactive ontology engineering, while maintaining her strong contributions to semantic web technologies and knowledge representation. Her research shows increasing attention to trustworthy AI concerns, aligning with her leadership roles in relevant projects. Scientific Recognition Senior member of Institut Universitaire de France (IUF) (2011-2016, renewed for 2016-2021) Junior member of Institut Universitaire de France (IUF) from 1997 to 2002 Chevalier de l'Ordre National du Merite (July 11, 2011) EurAI Fellow (nominated ECCAI Fellow in 2005) Best Paper Award at AAAI'96 for 'Verification of Knowledge Bases based on Containment Checking' Professor ROUSSET maintains an active role in the scientific community through editorial work and organizational leadership. She serves on the Editorial Board of Communications of the ACM (CACM) and has held significant roles including PC chair of EGC 2019, Workshops co-Chair of WWW 2018, and Area Chair of IJCAI 2017. Her consistent service on program committees of major international conferences demonstrates her standing in the field. Her laboratory, the SLIDE group within LIG, focuses on semantic web technologies, knowledge representation, and data integration. The group maintains strong connections with the international research community and participates in collaborative projects addressing cutting-edge challenges in artificial intelligence and data management, with particular emphasis on trustworthy and explainable AI systems.

Chang-Shyh Pengمشاهده پروفایل

استاد

• Networking (LAN/WAN)
• Data Communication
• Parallel Processing
• +۵ مورد دیگر

Chang-Shyh Peng is a Professor of Computer Science at California Lutheran University, teaching undergraduate and graduate courses while collaborating with corporate partners to develop industry-responsive curricula. His research expertise spans critical computing domains with emphasis on infrastructure and systems innovation: Networking (LAN/WAN) Data Communication Parallel Processing Client-Server Development Graphical User Interface Network Simulation and Modeling Computer and System Applications Advanced Algorithms Dr. Peng has published extensively across these areas, contributing to academic and practical advancements in computer science.

Gang Meiمشاهده پروفایل

دانشیار

• Numerical Simulation and Computational Modeling
• GPU Computing
• Machine Learning
• +۵ مورد دیگر

Dr. Gang Mei is an Associate Professor in Scientific Computing within the School of Engineering and Technology at China University of Geosciences (Beijing), where he has held academic positions since 2014. His career progression includes Postdoctoral Researcher (2014-2016), Lecturer (Oct-Dec 2016), and current Associate Professor (since Jan 2017). His research bridges computational science and engineering applications with significant editorial contributions to computer science literature. Education: Ph.D. in Computer Science, University of Freiburg, Germany (2014) Research Interests: Dr. Mei specializes in Numerical Simulation and Computational Modeling, GPU Computing, Machine Learning, and Data Mining, with strong applications in Network Science and Spatial Information Systems. His work integrates Distributed and Parallel Computing techniques for large-scale scientific simulations, particularly in geospatial modeling and network analysis. The research demonstrates consistent focus on computational efficiency through hardware acceleration and algorithmic optimization across diverse domains including satellite imagery processing, financial event detection, and medical image classification. Publication Trends: His editorial portfolio reveals strong interdisciplinary patterns connecting computer science fundamentals with domain-specific applications. Recent works emphasize GPU-accelerated methods for data-intensive problems (2020-2022), spatial-temporal modeling (2019-2020), and network science applications (2021). The publications consistently address computational scalability challenges while maintaining practical relevance across geospatial, financial, medical, and engineering contexts. Professional Recognition: As an IEEE Member, Dr. Mei serves on editorial boards for IEEE Access and PeerJ Computer Science, reflecting peer recognition in computational fields. His editorial contributions span 15+ publications demonstrating expertise in evaluating cutting-edge computer science research. Academic Service: Beyond editorial work, Dr. Mei's service includes advising on computational methodology across multiple disciplines. His role as Academic Editor demonstrates commitment to scholarly communication, particularly in bridging theoretical computer science with practical engineering applications. No grant funding details were specified in available materials.

Sung-Eui Yoonمشاهده پروفایل

استاد

• Scalable Graphics
• Computer Vision
• Robotics
• +۶ مورد دیگر

Sung-Eui Yoon is a Professor at the Department of Computer Science, Korea Advanced Institute of Science and Technology (KAIST), where he leads the Scalable Graphics, Vision, & Robotics Lab (SGVR Lab). He also holds affiliations with KAIST AI, KAIST Robotics Program, and CS Robotics. His academic career spans over 15 years at KAIST, where he has established himself as a leading researcher in graphics, vision, and robotics. Dr. Yoon received his Ph.D. from the Department of Computer Science at the University of North Carolina at Chapel Hill under the advisory of Dr. Dinesh Manocha, completed a postdoc at Lawrence Livermore National Lab, and earned his B.S. and M.S. from the Department of Computer Science at Seoul National University. His academic lineage traces back to Carl Friedrich Gauss through a distinguished line of mathematicians and computer scientists. His research spans scalable graphics, vision, robotics, and AI problems, with a particular focus on real-time rendering, collision detection, motion planning, and image retrieval. Dr. Yoon's work bridges theoretical foundations with practical applications, resulting in numerous publications, tutorials, and workshops at major conferences including SIGGRAPH, ICRA, and CVPR. His publications demonstrate a consistent focus on scalability and efficiency in graphics and robotics systems, with recent work emphasizing deep learning applications in image search and advanced motion planning algorithms for robotics. His research has evolved from foundational work in massive model rendering to cutting-edge applications in robotics and AI. Among his notable recognitions are the Outstanding Paper Award at ICRA 2023, Outstanding Navigation Award Finalist at ICRA 2022, Next-Generation Scientist Award (IT category) in 2019, and Technical Innovation Award from KAIST in 2018. Dr. Yoon has advised 4 Ph.D. students at KAIST between 2007-2014 and has secured numerous research grants supporting his lab's work. He has also authored influential books including "Rendering" (2018) and "Real-Time Massive Model Rendering" (2008). His teaching portfolio includes graduate courses on Web-Scale Image Retrieval, Motion Planning, and Graduate-level Computer Graphics, as well as undergraduate courses in Computer Graphics and Data Structures.

• Computational Chemistry
• Quantum Chemistry
• Theoretical Chemistry
• +۲ مورد دیگر

Theo Juncker von Buchwald serves as a Guest Researcher in the Department of Chemistry at the University of Copenhagen, located at Universitetsparken 5 in Copenhagen Ø. His research focuses on advanced computational methods in quantum chemistry, particularly developing and implementing cluster perturbation theories for molecular excitation energies and ground-state properties. His primary research interests center on Computational and Theoretical Chemistry, specializing in electronic structure theory. He develops high-accuracy quantum chemical methods including coupled cluster theory, variational excitation-energy functions, and core-valence separation techniques. His work bridges theoretical chemistry with high-performance computing, implementing parallel algorithms for large-scale molecular systems. Analysis of his four recent publications reveals a consistent research trajectory in Cluster Perturbation Theory (CPT), with increasing computational sophistication. His work demonstrates expertise in both theoretical development (variational formulations, Lagrangian approaches) and practical implementation (parallelization, GPU acceleration). Key trends include targeting CCSD/CCSDT accuracy with reduced computational cost, developing diagnostics for model reliability, and extending CPT to core-excited states for X-ray spectroscopy applications. Research Collaborations and Infrastructure: Collaborates extensively with Kurt V. Mikkelsen, Poul Jørgensen, and Jeppe Olsen Utilizes Frontier supercomputer at Oak Ridge National Laboratory Employs hybrid MPI/OpenMP parallelization with GPU acceleration Receives funding from Danish Council for Independent Research (Grants DFF-0136-00081B, DFF-10.46540/3103-00261B)