جستجوی استاد راهنمای دانشگاهی

Sahra Kunzمشاهده پروفایل

استادیار

• Animation
• Motion Capture
• Character Design
• +۳ مورد دیگر

Sahra Kunz is an Assistant Professor at the School of Arts, Portuguese Catholic University, and a Researcher at the Research Center for Science and Technology of the Arts (CITAR). She has taught the Sound and Image course since 1998 and leads key projects including CITAR (2020-2025) and CCD: Centro de Criatividade Digital (2017-2021), focusing on digital arts innovation and cultural heritage preservation. Her academic background includes a PhD in Drawing from the University of the Basque Country (2011), a Master's Degree in Sound and Image from the Portuguese Catholic University (2001), and a degree in Fine Arts - Painting from the School of Fine Arts, University of Porto (1997). These qualifications underpin her interdisciplinary approach to artistic research. Kunz's research explores animation, motion capture, and character design through lenses of gender representation, cultural studies, and mental health. She investigates how animation techniques empower female characters, analyzes the uncanny valley phenomenon, and examines anime's global cultural impact. Her work bridges technical animation practices with theoretical frameworks in digital arts, emphasizing practical applications in education and healthcare contexts. Analysis of her 15 most recent publications (2018-2023) reveals three dominant trends: (1) motion capture technology for character animation and gender empowerment, (2) the revival of 2D animation through streaming platforms, and (3) interdisciplinary health applications during the pandemic. Her publications consistently integrate computer graphics with cultural analysis, particularly in Japanese animation studies and mental health interventions. Kunz has supervised 48 students at UCP and serves as main examiner for numerous theses. Her grant activities include CITAR's €1.2M project on science and technology of the arts (2020-2025) and CCD's digital creativity initiative (2017-2021), both involving industry partnerships with cultural institutions and technology firms. As a core member of CITAR, she collaborates with over 20 researchers across animation production, motion capture visualization, and digital drawing. She co-organizes major events including the Olho Animation Film Festival (2022) and CINANIMA (2024), fostering connections between academic research and professional animation communities.

• Image Processing
• Signal Processing
• Computer Vision
• +۴ مورد دیگر

Marc Donias is an Associate Professor at the University of Bordeaux, affiliated with the IMS (Laboratory of Integration, Material to System) which is part of the College of Engineering. He is a member of the Signal and Image Processing research group and works within the MOTIVE team, focusing on advanced image processing and computer vision applications. His research interests span across multiple domains including image processing, signal processing, computer vision, machine learning, and seismic data analysis. Dr. Donias has made significant contributions in texture analysis, image colorization algorithms, and geological data interpretation. His work often bridges theoretical advances with practical applications in agriculture, materials science, and geophysics. Analysis of his recent publications reveals a strong trend toward deep learning applications in image processing, particularly generative models for image colorization and object detection. His work demonstrates interdisciplinary reach, connecting computer vision with agricultural technology, materials science, and geophysical interpretation. The publications show consistent collaboration with researchers from the IMS laboratory, particularly with Yannick Berthoumieu and other members of the MOTIVE team. Dr. Donias has been actively involved in developing innovative approaches for seismic horizon reconstruction, texture analysis, and agricultural image processing. His work on SPD manifold learning for image colorization represents a sophisticated mathematical approach to a challenging computer vision problem. The practical applications of his research are evident in precision agriculture technologies and geological interpretation tools.

Henry Segermanمشاهده پروفایل

دانشیار

• Geometry
• Topology
• 3D Printing
• +۵ مورد دیگر

Henry Segerman is an Associate Professor of Mathematics at Oklahoma State University, specializing in geometric topology, 3D printing, virtual reality, and mathematical visualization. His work bridges theoretical mathematics with physical and digital artistic expression, creating tangible and virtual representations of complex mathematical concepts. His research interests focus on three-dimensional geometry and topology, particularly exploring triangulations of 3-manifolds, veering triangulations, and hyperbolic geometry. He extends these mathematical concepts into the realm of visualization through 3D printing, spherical video, and virtual reality applications. Segerman has developed innovative techniques for representing four-dimensional objects in three-dimensional space using stereographic projection and has created numerous mathematical sculptures that visualize abstract topological concepts. Segerman's publication record reveals a consistent focus on the intersection of combinatorial topology and geometric structures, with a recent emphasis on veering triangulations and their connections to dynamic systems. His work demonstrates a progression from theoretical foundations toward increasingly sophisticated visualization techniques, culminating in interactive virtual reality experiences of non-Euclidean geometries. The substantial number of figures in his papers (often exceeding 50 per publication) highlights his commitment to visual explanation alongside mathematical rigor. Most Innovative People's Choice Award at Bridges 2013 for 'Triple gear' Most Effective Use of Mathematics People's Choice Award at Bridges 2012 for 'Dual Half 120- and 600-Cells' Segerman maintains an extensive collaborative network with mathematicians including Saul Schleimer, David Bachman, and Matthias Goerner, as well as artists and technologists like Vi Hart and Sabetta Matsumoto. His work has been supported by National Science Foundation grant DMS-2203993. He has created numerous mathematical art pieces that have been exhibited at major conferences including multiple Bridges Conferences and Joint Mathematics Meetings, with sculptures appearing in galleries worldwide. His laboratory work centers around the production of mathematical visualization tools and 3D printed sculptures. Segerman has developed specialized techniques for creating mathematical models using CAD software, Python scripting, and 3D printing technologies. His work with spherical video and virtual reality represents a significant contribution to non-Euclidean visualization, allowing viewers to experience geometries that cannot exist in our physical space.

• Assistive Technologies
• Chemistry Education
• 3D Printing
• +۷ مورد دیگر

Dr. Terence Cavanaugh is a full professor of Instructional Technology at the University of North Florida’s College of Education and Human Services, specializing in curriculum design, instructional technology, and assistive technology. As a Fulbright Specialist, he brings global experience from teaching in diverse regions including China, Korea, Bahrain, Kuwait, Tuvalu, and the Caribbean, alongside a robust publication record in educational technology and open-source resources. Education: Science Education (with certifications in Physics, Chemistry, Biology, Earth Science, General Science, and Middle Grades) Instructional Technology State-certified media specialist Research Interests: Assistive Technologies for disabilities and Deaf/Hard of Hearing learners 3D Printing applications in STEM education and tactile learning Digital Learning strategies across K-12 and higher education Open Educational Resources (OER) and textbook innovation Scientific Contributions: 15+ publications on technology integration, including books on OER and science education Key focus areas: computational thinking, infographic resumes, and performance-based funding Scientific Awards: Fulbright Specialist for global educational collaboration

Erik Wolfمشاهده پروفایل

پژوهشگر

• Human-Computer Interaction
• Virtual Reality
• Augmented Reality
• +۲ مورد دیگر

Erik Wolf is a research associate at the University of Hamburg's Department of Informatics, specializing in Human-Computer Interaction (HCI) and Extended Reality (XR) technologies. His work focuses on optimizing presence in virtual environments through studies of plausibility , co-presence , and place illusion , particularly in the Horizon Europe project 'PRESENCE'. Prior to this role, he completed his PhD at the University of Würzburg, investigating Individual-, System-, and Application-Related Factors Influencing the Perception of Virtual Humans in Virtual Environments . Education : Bachelor's and Master's in Human-Computer Interaction from the University of Würzburg Visiting researcher at University of Queensland's Cognitive Engineering Research Group (2016-2017) Research Interests : XR User Experience Virtual Human Perception Body Awareness & Self-Identification in VR Digital Health Applications Presence & Immersion Scientific Contributions : Developed validated scales for virtual human plausibility Explored avatar personalization effects on body perception Investigated multimodal interaction frameworks Created tools for intelligent virtual humans development His work has been recognized with multiple awards including the DIVR Science Award 2019 and multiple Best Paper distinctions. He serves as a reviewer for leading conferences including IEEE VR, ACM CHI, and IEEE ISMAR.

• High-Performance Computing
• Parallel Computing
• Heterogeneous Computing
• +۷ مورد دیگر

Alberto José Gonçalves Carvalho Proença serves as Full Professor in the Department of Informatics at the School of Engineering, University of Minho, and holds the position of Senior Researcher with Dr. habil at Centro ALGORITMI. His academic career spans over 45 years, beginning at the University of Porto in 1976 before transitioning to the University of Minho in 1977 where he has remained ever since. His educational foundation includes: Licentiate in Electrical Engineering from Coimbra, Portugal (1976) MSc in Digital Electronics from UMIST, Manchester, UK (1979) PhD from Manchester, UK (1982) Dr. habil (Habilitation) from the University of Minho (1998) Professor Proença's research spans from digital electronics to cutting-edge high-performance computing, with core expertise in computer architecture, parallel computing, and heterogeneous computing systems. His work bridges theoretical computer science with practical applications across diverse domains including particle physics (LHC data analysis), forensic science (DNA library systems), materials science (crystallographic imaging), and cultural heritage preservation. Current research focuses on optimizing computational efficiency across heterogeneous resources for scientific applications, addressing challenges in big data processing, parallel random number generation, and scheduling algorithms for distributed environments. Throughout his career, Professor Proença has successfully supervised numerous MSc dissertations and PhD theses while contributing significantly to institutional computing infrastructure. He chaired the University Computer Centre for 17 years (1985-2002), establishing Portugal's first national parallel computing service. For 11 years (2006-2017), he led the Advanced Computing theme in the University of Texas at Austin-Portugal cooperation program. Since 2005, he has directed the university's SeARCH heterogeneous computing cluster, supporting research across multiple scientific disciplines. His research group has developed several influential frameworks including JaSkel (Java Skeleton-Based Framework for Cluster and Grid Computing), HEP-Frame (for LHC data analysis), Im2Cr (crystallographic imaging tool), and CROSS-Fire (risk management decision support system). These platforms demonstrate his commitment to translating theoretical advances into practical tools that address real-world scientific and societal challenges.

Vijay Narayananمشاهده پروفایل

استاد

• Power Aware Computing
• Computer Architecture
• Embedded Systems
• +۴ مورد دیگر

Vijay Narayanan is the Robert Noll Chair Professor in Computer Science & Engineering and Electrical Engineering at Pennsylvania State University. He co-directs the Microsystems Design Lab and leads research in embedded visual analytics, self-powered processors, and system design using emerging devices. Education: B.E in Computer Science and Engineering (1993) from University of Madras, India Ph.D. in Computer Science and Engineering (1998) from University of South Florida, USA His research spans Power Aware Computing , Computer Architecture , and Embedded Systems , with emphasis on Visual Cortex on Silicon and Self-Powered Processors . Current work includes Non-Volatile Processors and Design Automation under unreliable power conditions via NSF ERC ASSIST. Recent publications focus on GPU architecture (Tensor Cores, ACE), Memory Consistency Verification (QED), and Neural Radiance Fields (Disorf, Distwar) for robotics and rendering. Key collaborations include Tsinghua University and DARPA/SRC LEAST Center . Scientific Awards: IEEE Fellow ACM Fellow He leads the Architecture, Benchmarking and Circuits Thrust in the DARPA/SRC LEAST Center and contributes to NSF ERC ASSIST for self-powered systems. Grants and projects emphasize cross-layer optimizations and hardware-software co-design.

Wong K.K.Y.مشاهده پروفایل

دانشیار

• Computer Vision
• Machine Learning
• Medical Imaging
• +۵ مورد دیگر

Prof. Kenneth K.Y. Wong is an Associate Professor and Division Associate Head (AI & Data Science Division) at the School of Computing and Data Science (CDS), The University of Hong Kong. He holds a BEng from The Chinese University of Hong Kong and MPhil/PhD from the University of Cambridge in Computer Vision. His career spans over 20 years in academia, including roles as Associate Head of the Department (2008-2012) and Programme Director of the BEng(CompSci) programme (2008-2015). Research Focus: Computer Vision, Machine Learning, Medical Imaging, Generative Models Key Roles: Director of Computer Vision Laboratory, Associate Editor of IJCV His research emphasizes camera calibration, 3D model reconstruction, generative AI, and medical image understanding. Over 160 peer-reviewed publications appear in top venues like CVPR, ECCV, and TPAMI. Active in professional service, he serves on program committees of major AI/conference events. Grants include projects in medical imaging (e.g., mitral valve analysis) and autonomous driving (DriveGPT4 series). His lab focuses on cutting-edge topics like video diffusion models, text-to-image synthesis, and 3D avatar generation.

Christian López Bencosmeمشاهده پروفایل

استادیار

• Machine Learning
• Data Science
• Persuasive Technologies
• +۷ مورد دیگر

Christian López Bencosme is an Assistant Professor of Computer Science with an affiliation in Mechanical Engineering at Lafayette College. He holds a Ph.D. from the Harold and Inge Marcus Department of Industrial and Manufacturing Engineering at the Pennsylvania State University and a Master of Science in Industrial and Systems Engineering from the Rochester Institute of Technology, NY. Prior to his academic career, he worked in both the Service and Manufacturing sectors. Dr. López's research focuses on the design and optimization of intelligent decision support systems and persuasive technologies to augment human proficiencies. His work integrates technologies and methods from science and engineering, particularly Machine Learning, Virtual Reality, and Gamification, to create systems that improve decision-making and task performance across education, business, health, and wellness domains. He has established several significant research projects including the Adaptable Game-based, Interactive Learning Environments for STEM Education (AGILE STEM), a Machine Learning and Gamification project for personalized-adaptive educational applications, and the VR CLICK Approach Project for improving spatial visualization skills. His scholarly work demonstrates consistent innovation in educational technology, with particular emphasis on developing machine learning algorithms that can personalize learning experiences and adapt pedagogical content to individual students' needs. His research on multilingual Twitter datasets related to the COVID-19 pandemic has generated significant scholarly interest, resulting in over 3 billion collected tweets and multiple publications analyzing global reactions to pandemic policies. Dr. López's work consistently bridges theoretical computer science with practical educational applications, creating systems that not only advance knowledge but also have immediate impact in classroom settings. Best Paper Award from Consortium for Computing Sciences in Colleges Regional Conference New IE Educator Outstanding Paper Award (awarded twice) ASME CIE Virtual Environments & Systems Best Paper Award Mid-Atlantic ASEE Committee Best Paper Award As an educator, Dr. López teaches courses including Introduction to Engineering: Design & Data Mining (ES 101), Introduction to Game Programming (CS 104), Introduction to Machine Learning (CS 414), and Principles of Data Science (DS 201). He has mentored numerous undergraduate students including Nathan Dinh, Alexa Gould, and Malolan Vasu on research projects related to gamification, machine learning, and virtual reality applications. His students have presented their collaborative work at major conferences including the ASME International Design Engineering Technical Conferences. Dr. López leads the VR/AR Community of Practice at Lafayette College, fostering interdisciplinary collaboration around virtual and augmented reality technologies. His research lab focuses on developing innovative educational applications that leverage machine learning algorithms to personalize learning experiences and improve student outcomes in STEM fields, with current projects including AI-driven educational game development and VR applications for spatial visualization training.

Wei-Chiu Maمشاهده پروفایل

استادیار

• 3D Computer Vision
• 4D Computer Vision
• Robotics
• +۵ مورد دیگر

Wei-Chiu Ma is an Assistant Professor of Computer Science at Cornell University, where he leads research at the intersection of 3D/4D computer vision and robotics. His work focuses on building AI systems that can understand, reconstruct, and re-simulate our dynamic world to enable more robust autonomous systems and advance entertainment applications. Prior to joining Cornell, Dr. Ma was a Young Investigator/Postdoc at AI2 / University of Washington. He received his Ph.D. from MIT, working with Antonio Torralba and Raquel Urtasun. Before his Ph.D., he was a Senior Research Scientist at Uber ATG R&D and Waabi working on self-driving vehicles, and completed his M.S. in Robotics at Carnegie Mellon University under the advisement of Kris M. Kitani. Dr. Ma's research interests span several interconnected areas in computer vision and robotics: 3D/4D Computer Vision: Focused on scene reconstruction, modeling, and understanding from visual inputs Neural Radiance Fields (NeRF): Developing techniques for novel view synthesis and scene representation Robotics and Simulation: Creating realistic sensor simulation for autonomous systems Digital Twins: Building interactive, game-engine compatible virtual environments Self-Driving Technology: Working on scene flow estimation, sensor simulation, and vehicle localization His recent publications demonstrate a strong focus on pushing the boundaries of 3D scene understanding, with particular emphasis on extreme-view geometry, neural rendering techniques, and creating realistic simulations for autonomous systems. His work often bridges theoretical computer vision with practical applications in robotics and autonomous vehicles. Dr. Ma has received several notable recognitions including being selected as a Cyber-Physical Systems (CPS) rising star and a Siebel Scholar. He has also earned the Best Application Award for his work on TDTOS: T-Shirt Design and Try On System. As an educator and mentor, Dr. Ma is actively involved in guiding the next generation of researchers. He hosts pro bono office hours for students from underrepresented groups and is committed to fostering diversity in the field. He is currently building his research group at Cornell and plans to hire 1-2 graduate students during the 2024-25 cycle. Dr. Ma has organized several influential workshops including the "Synthetic Data for Computer Vision" workshop at CVPR 2025, the "Agent in Interaction, from Humans to Robots" workshop at CVPR 2025, and the "3D Modeling, Reconstruction, and Generation in the Wild" workshop at ECCV 2024, demonstrating his leadership in the computer vision community.

Martin Fedaمشاهده پروفایل

پژوهشگر

• Radiosity
• Photorealistic Image Synthesis
• Parallel Graphics Algorithms
• +۱ مورد دیگر

Martin Feda is an Associated Researcher at the Institute of Computer Graphics, Vienna University of Technology, where he previously served as Assistant Professor. His research focuses on advancing radiosity methods for photorealistic image synthesis, with significant contributions to algorithmic efficiency and visual quality in global illumination rendering. Feda's primary research interests include radiosity, photorealistic image synthesis, and parallel graphics algorithms. He has pioneered techniques for stochastic radiosity, progressive refinement, and parallel implementations to accelerate computation. Key innovations involve hierarchical subdivision algorithms, methods for reducing shadow leaks without explicit meshing, improvements to intermediate radiosity images through directional light, and overshooting techniques to speed up progressive radiosity. His work consistently bridges theoretical advancements with practical applications for handling highly complex scenes. Analysis of his 1991-1997 publication record reveals a clear evolution in radiosity research: early work established parallel implementations on transputers and foundational radiosity algorithms, while later contributions developed sophisticated stochastic and hierarchical methods. The trajectory shows increasing emphasis on Monte Carlo techniques and computational optimizations to achieve greater efficiency and visual fidelity in global illumination, with consistent publication in top-tier graphics venues like Eurographics and Computer Graphics Forum.

Lukas Radlمشاهده پروفایل

پژوهشگر

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

Lukas Radl is a University Assistant and PhD Student at the Institute of Visual Computing, Graz University of Technology, where he works on 3D Scene Representations for View Synthesis under the supervision of Markus Steinberger. His research focuses on advancing real-time rendering techniques, particularly in Neural Radiance Fields (NeRF) and Gaussian Splatting, to bridge digital and physical world representation. Education: Master of Science in Computer Science (with distinction), Graz University of Technology, 2018-2023 Bachelor of Science in Software Engineering, Graz University of Technology, 2018-2023 Research Focus: Radl's work intersects Computer Graphics, Computer Vision, Machine Learning, and Parallel Processing. He pioneers practical implementations of Radiance Field Representations, addressing critical challenges in view consistency, anti-aliasing, and real-time performance for interactive applications. His innovations enable robust rendering in virtual reality and complex lighting scenarios through novel geometric and neural approaches. Publication Impact: Recent publications (2024-2025) demonstrate a cohesive trajectory toward production-ready radiance field systems. Key advances include sorting algorithms for view consistency (StopThePop), anti-aliasing frameworks for Gaussian Splatting (AAA-Gaussians), and VR-optimized pipelines (VRSplat). These contributions establish new standards for real-time performance while maintaining visual fidelity across diverse hardware platforms. Scientific Recognition: Dean's List (top 5% of students) at Graz University of Technology (2019, 2020) Mentorship & Service: Radl actively shapes academic discourse as a reviewer for premier venues (CGF, ICCV, TVCG) and mentors students through open projects in real-time rendering. His teaching portfolio spans exercise coordination for core visual computing courses since 2020, with current leadership in Real-Time Graphics and Computer Graphics instruction. He fosters talent through student projects advancing Gaussian Splatting implementations. Research Ecosystem: Embedded in Graz University of Technology's Institute of Visual Computing, Radl collaborates within a specialized team focused on radiance field optimization. The group maintains active pipelines for NeRF and Gaussian Splatting research, with strong industry connections evidenced by his upcoming Meta Reality Labs internship. Current projects target foveated rendering, geometric consistency, and editing capabilities for next-generation AR/VR systems.

Andreas Andreouمشاهده پروفایل

استاد

• Neuromorphic Engineering
• CMOS Microsystems
• Sensory Information Processing
• +۶ مورد دیگر

Andreas Andreou is a Professor of Electrical and Computer Engineering at Johns Hopkins University (JHU), with secondary appointments in Computer Science and the Whitaker Biomedical Engineering Institute. He co-founded the JHU Center for Language and Speech Processing (CLSP) and co-directs the Andreou Lab, focusing on brain-inspired microsystems, neuromorphic engineering, and biomedical sensors. His research spans CMOS-based neuromorphic processors, event-based vision systems, and wearable health monitoring devices like the StethoVest. Key contributions include silicon retinas, polarization-sensitive imagers, and algorithms for pattern analysis. Research Interests: Neuromorphic Computing: Designing energy-efficient brain-inspired chips using 3D CMOS, FETs, and memristive technologies. Biomedical Microsystems: Wearable acoustic sensors for cardiac monitoring and vestibular prosthetics. AI Hardware: Neuromorphic accelerators for edge computing, leveraging LLMs for automated circuit design. Notable Achievements: IEEE Fellow (since 2020) Recipient of the 3rd Best Paper Award at IEEE BioCAS 2018 $2M DARPA grant for bio-inspired event cameras Labs/Teams: The Andreou Lab collaborates with the Kavli Neuroscience Discovery Institute and NSF-funded neuromorphic projects. Ongoing work includes neuromorphic Ising machines, LLM-driven chip design, and quantum sensing for medical applications.

Jiří Kosinkaمشاهده پروفایل

دانشیار

• Computer Graphics
• Geometric Modelling
• Computer Aided Design
• +۳ مورد دیگر

Jiří Kosinka is an Associate Professor (Tenure Track) at the University of Groningen, affiliated with the Faculty of Science and Engineering and the Bernoulli Institute. He leads the Scientific Visualization and Computer Graphics research group. His roles include coordinating and lecturing in Computer Graphics and Advanced Computer Graphics courses, as well as serving as an editor for journals like Computer-Aided Design and Graphical Models . Academic Position: Associate Professor, Tenure Track Affiliations: Bernoulli Institute, Faculty of Science and Engineering Research Group: Scientific Visualization and Computer Graphics Education PhD in Mathematics (2006), Charles University, Prague MSc in Mathematics (2002), Charles University, Prague Research Interests Kosinka's work focuses on geometric modeling, computer graphics, and image processing. He develops algorithms for subdivision surfaces, numerical quadrature, and fluid simulation, with applications in surgical planning and medical visualization. His research bridges theoretical contributions with practical implementations in CAD systems and real-time rendering. Conference Contributions Co-organizer of DGMM 2025 (Discrete Geometry and Mathematical Morphology) in Groningen Program Chair for AniNex 2022/2023 (Next Generation Computer Animation) IPC member for SGP, SPM, Pacific Graphics, and other key conferences Editorial Roles He serves on the editorial boards of Computer-Aided Design and Graphical Models , and has guest-edited special issues in Computer Aided Geometric Design . Labs & Teams He leads the Scientific Visualization and Computer Graphics group, collaborating on projects like BoneStory (3D surgical planning) and fluid dynamics simulations. His lab focuses on advancing geometric algorithms and their real-world applications.

Mallesham Dasariمشاهده پروفایل

استادیار

• Immersive Media
• XR Systems
• Wireless Networks
• +۵ مورد دیگر

Mallesham Dasari is an Assistant Professor in the Electrical and Computer Engineering department at Northeastern University. His research focuses on immersive media, XR systems, wireless networks, and wearable computing, with a particular emphasis on optimizing video streaming and human-robot collaboration in extended reality environments. He joined Northeastern in January 2024 and is affiliated with the Institute for the Wireless Internet of Things. Education: PhD in Computer Science from Stony Brook University (2021). Research Interests: His work spans advanced video codecs, spatial video distribution, and sensor fusion technologies. Recent projects include developing FSO-based wireless links for VR headsets and neural compression techniques for point cloud streaming. He explores how XR technologies can enhance healthcare through systems like XRAI Care and enable seamless human-robot collaboration via platforms like RoboTwin. Publications: Over 30 peer-reviewed articles in top conferences like ACM SIGCOMM, NSDI, and MMSys, focusing on network optimization, immersive media systems, and edge computing. Awards: Received the Best Reproducible Paper Award at ACM MMSys 2025 and the Best Demo Award at ACM HotMobile 2025 for RoboTwin. His team also pioneered award-winning solutions for NASA’s SUIT Competition and developed markerless localization systems for AR. Advising & Grants: Mentors students in Northeastern’s College of Engineering, leading projects funded by industry partnerships and federal grants. His lab collaborates on multi-agent tracking systems combining visual and RF sensing technologies. Labs/Teams: Active in Northeastern’s XR systems research group, focusing on scalable 3D scene capture (MeshReduce) and time-varying mesh compression (TVMC). His work intersects with digital twin technologies and edge-based asset virtualization frameworks.