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Xiaoming Liu is the Anil K. and Nandita Jain Endowed Professor of Engineering and MSU Foundation Professor in the Department of Computer Science and Engineering at Michigan State University . Holding a Ph.D. from Carnegie Mellon University (2004), he leads cutting-edge research in computer vision and machine learning. Research Interests : Computer Vision Pattern Recognition Image and Video Processing Machine Learning Medical Image Analysis Multimedia Retrieval Recent Research Trends : Focus on 3D object detection and depth estimation Development of robust biometric recognition systems Integration of radar-camera fusion for autonomous systems Advancements in self-supervised and multimodal learning Exploration of adversarial AI security Creation of interpretable forgery detection frameworks Teaching : Spring 2013: CSE891-006 Computer Vision Seminar Fall 2012-2015: CSE803 Computer Vision Spring 2014-2017: CSE 471 Media Processing and Multimedia Contact Information : Email: liuxm@cse.msu.edu Office: EB 3137, Michigan State University Phone: +1 (517) 355-2359

• Computer Vision
• Pattern Recognition
• Image and Video Processing
• +4 more

Adam Finkelstein is a Professor in the Department of Computer Science at Princeton University, where he has been a faculty member since 1997. He holds a PhD and Master's in Computer Science from the University of Washington and a dual degree in Physics and Computer Science from Swarthmore College. Finkelstein is renowned for his interdisciplinary work at the intersection of computer graphics, audio processing, and machine learning, and he co-organized the Art of Science exhibition at Princeton. Education: PhD, Computer Science, University of Washington MS, Computer Science, University of Washington BA, Physics and Computer Science, Swarthmore College His research spans audio processing (e.g., speech enhancement, voice conversion, audio metrics), computer graphics (e.g., line drawing algorithms, stylized rendering, image manipulation), and machine learning (e.g., self-supervised learning, differentiable programming). His work often bridges technical and creative domains, exemplified by collaborations at Pixar and Adobe Creative Technologies Lab. Recent publications highlight advancements in audio super-resolution and voice conversion using deep learning frameworks, as well as stylized line rendering for animated 3D models. His contributions to perceptual audio metrics and shader optimization further underscore his impact on human-centric computational systems. Scientific Awards: NSF CAREER Award Alfred P. Sloan Fellowship Fellow of the Association for Computing Machinery (ACM) Finkelstein has secured foundational grants for his research and actively mentors students, though no specific advisees are listed. He also explores collaborative tools for internet music performance, reflecting his broader interest in distributed systems and user interfaces.

• Computer Science
• Audio Processing
• Image Processing
• +3 more

David Salesin is an Affiliate Professor in the Department of Computer Science & Engineering at the University of Washington and a Principal Scientist/Director at Google Research since 2019. He has held academic roles at Cornell University (Visiting Assistant Professor, 1991-92) and guest professorships at Zhejiang University. His career spans academia and industry, including leadership at Adobe's Creative Technologies Lab (2005-17) and Microsoft Research (1999-2005). PhD, Stanford University (1991) Sc.B., Brown University (1983) His research focuses on computer graphics, particularly non-photorealistic rendering, digital typography, color science, and adaptive document layout. He pioneered techniques in image-based rendering, pen-and-ink illustration, and facial animation, with applications in multimedia and user interface design. Article Trends : His work bridges procedural content generation, 3D visualization, and artistic computing, emphasizing user-driven tools for creative industries. Key subfields include texture advection, multiresolution modeling, and real-time camera control for virtual cinematography. Scientific Awards : ACM Fellow (2002) ACM SIGGRAPH Achievement Award (2000) Carnegie Foundation Professor of the Year (1998) NSF Presidential Faculty Fellow (1995-98) Alfred P. Sloan Research Fellowship (1995-97) Numerous industry grants and lab donations He has advised over 30 PhD and Master's students, including leaders at Microsoft, Pixar, and Google. His labs at UW and Adobe focused on graphics, imaging, and creativity tools.

• Computer Graphics
• Digital Photography and Video
• Non-Photorealistic Rendering
• +7 more

Charles Walter is an Assistant Professor of Computer and Information Science at the University of Mississippi, joining in Fall 2019. He holds a PhD in Computer Science from The University of Tulsa (2018), with prior degrees from the same institution (M.Sc 2016; B.S. 2014). His research focuses on Mobile and Wearable Security, Adversarial Machine Learning, Privacy, Malware Analysis, Fog Computing, and Self-Adaptive Systems. He leads the SPARC Lab, exploring cutting-edge topics like data privacy, malware detection, and security in fog computing environments. Education: B.S. Computer Science, University of Tulsa (2014) M.Sc Computer Science, University of Tulsa (2016) Ph.D. Computer Science, University of Tulsa (2018) Research Interests: His work addresses critical challenges in cybersecurity, including securing low-power wearable devices through fog computing architectures, developing adversarial machine learning defenses, and investigating human factors in code trustworthiness. Recent projects include studying privacy threats in diffusion models and creating frameworks for robust stability estimation in AI systems. Lab Activities: The SPARC Lab actively researches topics such as adversarial ML attacks, privacy-preserving video processing, and adaptive system security. Collaborative efforts focus on real-world applications like improving university transportation systems through smart bike rental programs.

• Mobile and Wearable Security
• Adversarial Machine Learning
• Privacy
• +5 more

Jia-Bin Huang is an Associate Professor in the Department of Computer Science at University of Maryland, College Park , with a secondary appointment at the University of Maryland Institute for Advanced Computer Studies . His work bridges computer vision , computer graphics , and machine learning . His research focuses on 3D scene reconstruction , neural radiance fields , generative models , and multimodal foundation models . He has made significant contributions to video super-resolution , text-driven 3D modeling , and inverse rendering techniques. 15 recent publications (2024-2025) at top venues: CVPR , NeurIPS , SIGGRAPH Asia , 3DV , and ECCV Pioneering work in Urban Scene Inverse Rendering , Generative Video Editing , and 3D Human Digitization He has received multiple awards including the 3M Non-Tenured Faculty Award , ETRA Best Paper , and NSF Grants . His lab trains 12 PhD students and has graduated 18 Masters/PhD students now at institutions like Stanford , Meta , and Google .

• Computer Vision
• Computer Graphics
• Machine Learning
• +4 more

Professor Mihran Tuceryan is a Professor of Computer Science at Purdue University Indianapolis, affiliated with the Department of Computer Science within the College of Science. He holds a PhD from the University of Illinois at Urbana-Champaign (1986) and a BS from MIT (1978). His expertise spans Computer Vision, Image Processing, Pattern Recognition, and Augmented Reality. Recent research focuses on crime prediction via video analysis, forensic imaging, and distributed tracking systems. He is a Senior Member of IEEE and ACM. Key research interests include augmented reality integration for industrial training, real-time illumination modeling, and monocular SLAM algorithms. His work addresses challenges in photorealistic AR, dynamic object labeling, and medical imaging applications such as hepatic fibrosis detection. He has contributed to projects like the e-DOTS indoor tracking system and forensic 3D impression acquisition. His publications span over three decades, emphasizing real-world applications in security, healthcare, and robotics. Education: Bachelor of Science in Computer Science and Engineering, MIT, 1978 PhD in Computer Science, University of Illinois at Urbana-Champaign, 1986 Awards: Senior Member, IEEE Senior Member, ACM Labs/Teams: Focus on AR, SLAM, and medical imaging applications Collaborative frameworks for distributed visual SLAM

• Computer Vision
• Image Processing
• Pattern Recognition
• +3 more

Jonathan Ragan-Kelley is the Esther and Harold E. Edgerton Assistant Professor of Electrical Engineering & Computer Science at MIT and an Assistant Professor of EECS at UC Berkeley. He leads the Visual Computing group at CSAIL, focusing on high-efficiency visual computing, compilers, and architectures for image processing, machine learning, and 3D rendering. His research bridges systems, compilers, and hardware design, emphasizing scalable solutions for computational challenges. Education: PhD in Computer Science from MIT (2014), postdoc at Stanford University, and visiting researcher at Google. He co-created the Halide language and has developed multiple domain-specific languages (DSLs) and compiler systems. Research interests include compiler optimization, scheduling languages (e.g., Exo), and efficient computing frameworks. He has received awards such as the NSF CAREER Award and ACM SIGGRAPH’s Significant New Researcher Award. Awards: ACM SIGGRAPH Award, NSF CAREER, Intel Outstanding Researcher Award Key Contributions: Halide compiler framework, Exo scheduling language, machine learning acceleration techniques Labs/Teams: Visual Computing at MIT CSAIL

• High-Efficiency Visual Computing
• Compilers
• Computer Architecture
• +3 more

Marc Olano is an Associate Professor in the Department of Computer Science and Electrical Engineering at the University of Maryland, Baltimore County (UMBC), and serves as the Associate Dean of Academic Programs and Learning in the College of Engineering and Information Technology. He leads the Computer Science Game Development Track and co-directs the VANGOGH lab. His research focuses on interactive 3D computer graphics, programmable shading, graphics hardware, and surface appearance modeling, with contributions to foundational graphics technologies like procedural shading and normal mapping. Research Interests: Olano’s work spans real-time rendering, GPU algorithms, texture compression, and procedural shading. He has pioneered techniques such as LEAN mapping and variable bitrate texture compression, significantly impacting game development and real-time graphics. His research often explores the intersection of hardware capabilities and algorithmic innovation, with applications in medical visualization, visualization of scientific data, and haptic interaction. Key Contributions: Olano’s accomplishments include pioneering procedural shading on graphics hardware, developing homogeneous rendering techniques, and advancing normal mapping. His work on GPU-based curvature estimation and BT volumes for volume rendering exemplifies his focus on leveraging GPU parallelism for real-time visualization challenges. He has also contributed to standards in shading languages and GPU programming. Teaching & Mentorship: Olano teaches courses in computer graphics, game development, and advanced computer architecture. He mentors students in independent studies and has advised numerous MS theses exploring topics like GPU random number generation, volume rendering, and soft shadow algorithms. His students’ work often bridges theoretical research and practical GPU implementations. Labs & Projects: The VANGOGH lab under his co-direction focuses on advanced visualization and graphics research, including real-time rendering techniques, GPU algorithms, and interactive data visualization. His research collaborations span industry partners like Firaxis Games, contributing to titles such as Civilization V through texture compression innovations.

• Computer Graphics
• Real-Time Rendering
• Graphics Hardware
• +4 more

Hazar Dib is an Associate Professor at the School of Construction Management Technology, Purdue Polytechnic Institute, Purdue University. His work bridges Building Information Modeling (BIM) , knowledge management , and interactive learning technologies to advance construction education and process efficiency. Ph.D. in Building Construction (2007, University of Florida) MSc. in Civil Engineering (2002, University of Balamand) BSc. in Civil Engineering (2000, University of Balamand) Research Interests focus on: BIM lifecycle integration AI/knowledge-based systems for construction Digital tools for surveying and steel connection education Collaborative communication frameworks Sustainability metrics in building practices Human factors in technology adoption Scientific Awards include multiple Charles B. Murphy Awards for undergraduate teaching and the Society of Leaders in Construction induction. His NSF-funded projects like VELS (Virtual Environment for Learning Surveying) and Steel Connection Teaching Tool highlight his innovation in STEM education . Articles span serious games , visual learning , and BIM maturity assessments , reflecting his interdisciplinary approach.

• Building Information Modeling (BIM)
• Information Systems
• Knowledge Management
• +7 more

Henry Kang is an Associate Professor in the Department of Computer Science at the University of Missouri–St. Louis, College of Arts and Sciences. His expertise spans computer graphics, data visualization, and computational art, with extensive experience in full-stack web development and programming frameworks. Education: Ph.D. in Computer Science, Korea Advanced Institute of Science and Technology (2002) Research Interests: Kang's work focuses on computer graphics, non-photorealistic rendering, and data visualization. Key projects include coherence-enhancing filtering, stereoscopic 3D line drawing, and emotion-driven image recoloring. He integrates machine learning and GPU computing for real-time scene navigation and artistic effects. Publication Trends: His research emphasizes texture filtering, computational art, and perceptual modeling. Recent work includes Gaussian image binarization (2021) and coherence-enhancing GPU filtering (2018), while earlier contributions explore stereoscopic depth perception (2013) and directional stippling (2011). Contact: Email: kangh@umsl.edu Phone: (314) 516-5841 Office: 318 ESH

• Computer Graphics
• Data Visualization
• Computer Animation
• +3 more

A.B. Osborne is an Associate Professor and Director of the Animation Program at Augusta University's Pamplin College of Arts, Humanities, and Social Sciences. Specializing in technical animation and visual storytelling, he focuses on 2D/3D hybrid rigging, real-time animation workflows, and non-photorealistic rendering techniques. Education: MFA in Animation, Interactive Technology, Video Graphics, and Special Effects from Savannah College of Art & Design (2013) BA in Radio and Television from Eastern Kentucky University (2010) His research bridges computer science , digital media , and creative technology , with applications in game development, social media visualization, and technical art. Osborne's scholarship includes innovative animation projects like Hay Day and Stylized Extinction , focusing on hybrid rendering and ecological storytelling. Osborne is actively engaged in academic service, chairing search committees and participating in university governance through roles like Lyceum Committee member and Pamplin Faculty Council representative. His teaching emphasizes: 3D Animation Look Development Game Development Animation History Technical Animation Notable awards include the Greater Augusta Arts Council Arts Educator Award (2025) , Silver Telly Award (2025) , and Boundless Teaching Award (2021) . These recognize his contributions to animation education and creative technology.

• 2D/3D hybrid rigging methods
• efficient animation pipeline processes
• real-time animation techniques
• +3 more

Sarah Abraham is an Assistant Professor in the Department of Computer Science at the University of Texas at Austin, affiliated with the Real-time Graphics and Parallel Systems research group. She holds a Ph.D. and M.S. from the University of Texas at Austin and a B.A. from Wellesley College. Research Interests: Dr. Abraham focuses on non-photorealistic rendering artistic tools for physical simulation video game mechanics that foster cooperation and empathy interactive narratives for prosocial engagement visualization techniques parallel computing in graphics Publications Trends: Her work bridges computer graphics, game design, and human-computer interaction, exploring innovative tools for artists and games that promote empathy through cooperative mechanics and narrative design. Scientific Awards: CNS Teaching Excellence Award Labs & Teams: She is a member of the Real-time Graphics and Parallel Systems research group at UT Austin.

• Computer Graphics
• Visualization
• Video Game Development
• +3 more

Ergun Akleman is a Professor at Texas A&M University, affiliated with the College of Performance, Visualization & Fine Arts, Department of Visualization. He holds degrees from Istanbul Technical University (B.S. Electrical Engineering, 1981) and Georgia Institute of Technology (M.S. and Ph.D. in Electrical Engineering, 1986 and 1992). His research focuses on shape modeling, geometric data structures, non-photorealistic rendering, volume modeling, and 3D printing innovations. His work explores cutting-edge topics such as topologically interlocked structures, space-filling geometries, and cooperative robotics in additive manufacturing. Recent studies include frameworks for collision-free 3D printing and theoretical advancements in computational design. His articles often bridge computational geometry with real-world applications in materials science and manufacturing. No scientific awards are explicitly mentioned in the provided texts. His research has implications for architecture, material science, and digital fabrication. He has contributed to projects like SafeZone and VoroNoodles , emphasizing interdisciplinary approaches to geometric challenges.

• Shape Modeling
• Geometric Data Structures
• Non-Photorealistic Rendering
• +6 more

Szymon Rusinkiewicz is the David M. Siegel ’83 Professor and Chair of the Department of Computer Science at Princeton University. His research bridges computation with the visual and tangible world, focusing on 3D shape, motion, and appearance. Department Chair: Computer Science University: Princeton University Research Areas: Computational fabrication, 3D scan acquisition/registration/reconstruction, machine learning for image/shape analysis, robotic localization/planning, and appearance/performance capture for digital humans. Applications include cultural heritage documentation, non-photorealistic shading models for illustrative depiction, and interdisciplinary work with robotics and machine learning.

• Computer Science
• 3D Shape Acquisition
• Computational Fabrication
• +7 more

Manmohan Chandraker is a Professor in the Department of Computer Science & Engineering at the University of California, San Diego (UCSD). His research focuses on computer vision, 3D reconstruction, and autonomous driving, with interdisciplinary links to robotics, machine learning, and computer graphics. He leads projects in 3D scene understanding, real-time visual odometry, and sensor fusion for autonomous systems. His work has been recognized with top academic awards and industry accolades. Education: B.Tech. in Electrical Engineering from IIT Bombay Ph.D. in Computer Science from UCSD Postdoctoral scholarship at UC Berkeley Research Interests: Chandraker’s work addresses challenges in 3D reconstruction under complex lighting and materials, autonomous driving systems, and physically-based inverse rendering. Key contributions include frameworks for non-convex optimization in geometric reconstruction and semantic-driven dense reconstruction techniques. His research bridges theory and practice, with applications in augmented reality, robotics navigation, and automotive safety systems. Key Awards: Best Paper Award at CVPR 2014 UCSD CSE Dissertation Award (2009) NEC Business Contribution Award (2015) Advising & Industry Collaboration: He has led teams at NEC Labs America, collaborating with automobile manufacturers to develop single-camera systems for real-time autonomous driving. His work on closed-loop traffic simulations and adversarial scenario generation has driven industry partnerships and patents. Current research explores multimodal LLM integration, data-centric AI tools (e.g., Ymir platform), and photorealistic scene synthesis. Labs & Projects: Chandraker’s group develops open frameworks like OpenRooms and TRoVE for 3D scene datasets, and contributes to benchmarks for domain adaptation in vision tasks. His team also works on safety-critical systems for autonomous vehicles through projects like SAFE-SIM and Drive-1-to-3.

• Computer Vision
• 3D Reconstruction
• Scene Understanding
• +5 more