Bio

Maneesh Agrawala is the Forest Baskett Professor of Computer Science and Director of the Brown Institute for Media Innovation at Stanford University. He was previously a Professor of Electrical Engineering and Computer Science at the University of California, Berkeley (2005 - 2015). He works on computer graphics, human computer interaction and visualization. His focus is on investigating how cognitive design principles can be used to improve the effectiveness of audio/visual media. The goals of this work are to discover the design principles and then instantiate them in both interactive and automated design tools. He received an Okawa Foundation Research Grant in 2006, an Alfred P. Sloan Foundation Fellowship and an NSF CAREER Award in 2007, a SIGGRAPH Significant New Researcher Award in 2008, and a MacArthur Foundation Fellowship in 2009.

Academic Appointments

Administrative Appointments

  • Director, David and Helen Gurley Brown Institute for Media Innovation (2015 - Present)
  • Professor, Computer Science (2015 - Present)

Honors & Awards

  • Research Grant, Okawa Foundation (2006)
  • CAREER Award, National Science Foundation (2007)
  • Research Fellow, Alfred P. Sloan Foundation (2007)
  • Significant New Researcher Award, ACM SIGGRAPH (2008)
  • Fellow, MacArthur Foundation (2009)
  • SIGCHI Academy, ACM SIGCHI (2021)
  • ACM Fellow, ACM (2022)

Boards, Advisory Committees, Professional Organizations

  • Advisor, Human Computation Journal (2013 - Present)
  • Science and Creativity Advisor, Studio 360 with Kurt Andersen (2012 - Present)

Program Affiliations

  • Symbolic Systems Program

Professional Education

  • Ph.D., Stanford University, Computer Science (2002)
  • B.S., Stanford University, Mathematics (1994)

Contact

Additional Info

Links

Current Research and Scholarly Interests

Computer Graphics, Human Computer Interaction and Visualization.

2023-24 Courses

Stanford Advisees

All Publications

  • Editing Motion Graphics Video via Motion Vectorization and Transformation ACM TRANSACTIONS ON GRAPHICS Zhang, S., Ma, J., Wu, J., Ritchie, D., Agrawala, M. 2023; 42 (6)

    View details for DOI 10.1145/3618316

    View details for Web of Science ID 001139790400057

  • EMPHASISCHECKER: A Tool for Guiding Chart and Caption Emphasis. IEEE transactions on visualization and computer graphics Kim, D. H., Choi, S., Kim, J., Setlur, V., Agrawala, M. 2023; PP

    Abstract

    Recent work has shown that when both the chart and caption emphasize the same aspects of the data, readers tend to remember the doubly-emphasized features as takeaways; when there is a mismatch, readers rely on the chart to form takeaways and can miss information in the caption text. Through a survey of 280 chart-caption pairs in real-world sources (e.g., news media, poll reports, government reports, academic articles, and Tableau Public), we find that captions often do not emphasize the same information in practice, which could limit how effectively readers take away the authors' intended messages. Motivated by the survey findings, we present EMPHASISCHECKER, an interactive tool that highlights visually prominent chart features as well as the features emphasized by the caption text along with any mismatches in the emphasis. The tool implements a time-series prominent feature detector based on the Ramer-Douglas-Peucker algorithm and a text reference extractor that identifies time references and data descriptions in the caption and matches them with chart data. This information enables authors to compare features emphasized by these two modalities, quickly see mismatches, and make necessary revisions. A user study confirms that our tool is both useful and easy to use when authoring charts and captions.

    View details for DOI 10.1109/TVCG.2023.3327150

    View details for PubMedID 37922182

  • ZoomShop: Depth-Aware Editing of Photographic Composition Liu, S. J., Agrawala, M., DiVerdi, S., Hertzmann, A. WILEY. 2022: 57-70

    View details for DOI 10.1111/cgf.14458

    View details for Web of Science ID 000802723900007

  • Modular Information Flow through Ownership Crichton, W., Patrignani, M., Agrawala, M., Hanrahan, P., Jhala, R., Dillig ASSOC COMPUTING MACHINERY. 2022: 1-14

    View details for DOI 10.1145/3519939.3523445

    View details for Web of Science ID 000850435600001

  • Disentangled3D: Learning a 3D Generative Model with Disentangled Geometry and Appearance from Monocular Images Tewari, A., Mallikarjun, B. R., Pan, X., Fried, O., Agrawala, M., Theobalt, C., IEEE COMP SOC IEEE COMPUTER SOC. 2022: 1506-1515

    View details for DOI 10.1109/CVPR52688.2022.00157

    View details for Web of Science ID 000867754201074

  • Measuring Compositional Consistency for Video Question Answering Gandhi, M., Gul, M., Prakash, E., Grunde-McLaughlin, M., Krishna, R., Agrawala, M., IEEE COMP SOC IEEE COMPUTER SOC. 2022: 5036-5045

    View details for DOI 10.1109/CVPR52688.2022.00499

    View details for Web of Science ID 000867754205030

  • Sketch-Based Design of Foundation Paper Pieceable Qilts Leake, M., Bernstein, G., Agrawala, M., ACM ASSOC COMPUTING MACHINERY. 2022

    View details for DOI 10.1145/3526113.3545643

    View details for Web of Science ID 001046841800032

  • A Mathematical Foundation for Foundation Paper Pieceable Quilts ACM TRANSACTIONS ON GRAPHICS Leake, M., Bernstein, G., Davis, A., Agrawala, M. 2021; 40 (4)

    View details for DOI 10.1145/3450626.3459853

    View details for Web of Science ID 000674930900032

  • Vid2Player: Controllable Video Sprites That Behave and Appear Like Professional Tennis Players ACM TRANSACTIONS ON GRAPHICS Zhang, H., Sciutto, C., Agrawala, M., Fatahalian, K. 2021; 40 (3)

    View details for DOI 10.1145/3448978

    View details for Web of Science ID 000695551400005

  • Iterative Text-Based Editing of Talking-Heads Using Neural Retargeting ACM TRANSACTIONS ON GRAPHICS Yao, X., Fried, O., Fatahalian, K., Agrawala, M. 2021; 40 (3)

    View details for DOI 10.1145/3449063

    View details for Web of Science ID 000695551400001

  • EVALUATING FACIAL RECOGNITION TECHNOLOGY: A PROTOCOL FOR PERFORMANCE ASSESSMENT IN NEW DOMAINS DENVER LAW REVIEW Ho, D. E., Black, E., Agrawala, M., Li Fei-Fei 2021; 98 (4): 753-773

    View details for Web of Science ID 000686480300001

  • The Role of Working Memory in Program Tracing Crichton, W., Agrawala, M., Hanrahan, P., ASSOC COMP MACHINERY ASSOC COMPUTING MACHINERY. 2021

    View details for DOI 10.1145/3411764.3445257

    View details for Web of Science ID 000758168003011

  • Analysis of Faces in a Decade of US Cable TV News Hong, J., Crichton, W., Zhang, H., Fu, D. Y., Ritchie, J., Barenholtz, J., Hannel, B., Yao, X., Murray, M., Moriba, G., Agrawala, M., Fatahalia, K., ASSOC COMP MACHINERY ASSOC COMPUTING MACHINERY. 2021: 3011-3021

    View details for DOI 10.1145/3447548.3467134

    View details for Web of Science ID 000749556803005

  • AGQA: A Benchmark for Compositional Spatio-Temporal Reasoning Grunde-McLaughlin, M., Krishna, R., Agrawala, M., IEEE COMP SOC IEEE COMPUTER SOC. 2021: 11282-11292

    View details for DOI 10.1109/CVPR46437.2021.01113

    View details for Web of Science ID 000742075001047

  • Editing Self-Image COMMUNICATIONS OF THE ACM Fried, O., Jacobs, J., Finkelstein, A., Agrawala, M. 2020; 63 (3): 70–79

    View details for DOI 10.1145/3326601

    View details for Web of Science ID 000582584200023

  • Searching the Visual Style and Structure of D3 Visualizations IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS Hoque, E., Agrawala, M. 2020; 26 (1): 1236–45

    Abstract

    We present a search engine for D3 visualizations that allows queries based on their visual style and underlying structure. To build the engine we crawl a collection of 7860 D3 visualizations from the Web and deconstruct each one to recover its data, its data-encoding marks and the encodings describing how the data is mapped to visual attributes of the marks. We also extract axes and other non-data-encoding attributes of marks (e.g., typeface, background color). Our search engine indexes this style and structure information as well as metadata about the webpage containing the chart. We show how visualization developers can search the collection to find visualizations that exhibit specific design characteristics and thereby explore the space of possible designs. We also demonstrate how researchers can use the search engine to identify commonly used visual design patterns and we perform such a demographic design analysis across our collection of D3 charts. A user study reveals that visualization developers found our style and structure based search engine to be significantly more useful and satisfying for finding different designs of D3 charts, than a baseline search engine that only allows keyword search over the webpage containing a chart.

    View details for DOI 10.1109/TVCG.2019.2934431

    View details for Web of Science ID 000506166100114

    View details for PubMedID 31442980

  • Supporting Visual Artists in Programming through Direct Inspection and Control of Program Execution Li, J., Brandt, J., Mech, R., Agrawala, M., Jacobs, J., ACM ASSOC COMPUTING MACHINERY. 2020

    View details for DOI 10.1145/3313831.3376765

    View details for Web of Science ID 000696110400054

  • Answering Questions about Charts and Generating Visual Explanations Kim, D., Hoque, E., Agrawala, M., ACM ASSOC COMPUTING MACHINERY. 2020

    View details for DOI 10.1145/3313831.3376467

    View details for Web of Science ID 000695438100139

  • Generating Audio-Visual Slideshows from Text Articles Using Word Concreteness Leake, M., Shin, H., Kim, J. O., Agrawala, M., ACM ASSOC COMPUTING MACHINERY. 2020

    View details for DOI 10.1145/3313831.3376519

    View details for Web of Science ID 000695438100190

  • Text-based Editing of Talking-head Video ACM TRANSACTIONS ON GRAPHICS Fried, O., Tewari, A., Zollhofer, M., Finkelstein, A., Shechtman, E., Goldman, D. B., Genova, K., Jin, Z., Theobalt, C., Agrawala, M. 2019; 38 (4)

    View details for DOI 10.1145/3306346.3323028

    View details for Web of Science ID 000475740600042

  • VisiBlends: A Flexible Workflow for Visual Blends Chilton, L. B., Petridis, S., Agrawala, M., Assoc Comp Machinery ASSOC COMPUTING MACHINERY. 2019

    View details for DOI 10.1145/3290605.3300402

    View details for Web of Science ID 000474467902023

  • View-Dependent Video Textures for 360 degrees Video Liu, S. J., Agrawala, M., DiVerdi, S., Hertzmann, A., ACM ASSOC COMPUTING MACHINERY. 2019: 249–62

    View details for DOI 10.1145/3332165.3347887

    View details for Web of Science ID 000518189200022

  • Optimizing Portrait Lighting at Capture-Time Using a 360 Camera as a Light Probe Jane, L. E., Fried, O., Agrawala, M., ACM ASSOC COMPUTING MACHINERY. 2019: 221–32

    View details for DOI 10.1145/3332165.3347893

    View details for Web of Science ID 000518189200020

  • Editing Spatial Layouts through Tactile Templates for People with Visual Impairments Li, J., Kim, S., Miele, J. A., Agrawala, M., Follmer, S., Assoc Comp Machinery ASSOC COMPUTING MACHINERY. 2019

    View details for DOI 10.1145/3290605.3300436

    View details for Web of Science ID 000474467902057

  • How to Design Voice Based Navigation for How-To Videos Chang, M., Anh Truong, Wang, O., Agrawala, M., Kim, J., Assoc Comp Machinery ASSOC COMPUTING MACHINERY. 2019

    View details for DOI 10.1145/3290605.3300931

    View details for Web of Science ID 000474467909003

  • Pinpoint: A PCB Debugging Pipeline Using Interruptible Routing and Instrumentation Strasnick, E., Follmer, S., Agrawala, M., Assoc Comp Machinery ASSOC COMPUTING MACHINERY. 2019

    View details for DOI 10.1145/3290605.3300278

    View details for Web of Science ID 000474467900048

  • Visual Rhythm and Beat ACM TRANSACTIONS ON GRAPHICS Davis, A., Agrawala, M. 2018; 37 (4)

    View details for DOI 10.1145/3197517.3201371

    View details for Web of Science ID 000448185000083

  • Saliency in VR: How do people explore virtual environments? Sitzmann, V., Serrano, A., Pavel, A., Agrawala, M., Gutierrez, D., Masia, B., Wetzstein, G. IEEE COMPUTER SOC. 2018: 1633–42

    Abstract

    Understanding how people explore immersive virtual environments is crucial for many applications, such as designing virtual reality (VR) content, developing new compression algorithms, or learning computational models of saliency or visual attention. Whereas a body of recent work has focused on modeling saliency in desktop viewing conditions, VR is very different from these conditions in that viewing behavior is governed by stereoscopic vision and by the complex interaction of head orientation, gaze, and other kinematic constraints. To further our understanding of viewing behavior and saliency in VR, we capture and analyze gaze and head orientation data of 169 users exploring stereoscopic, static omni-directional panoramas, for a total of 1980 head and gaze trajectories for three different viewing conditions. We provide a thorough analysis of our data, which leads to several important insights, such as the existence of a particular fixation bias, which we then use to adapt existing saliency predictors to immersive VR conditions. In addition, we explore other applications of our data and analysis, including automatic alignment of VR video cuts, panorama thumbnails, panorama video synopsis, and saliency-basedcompression.

    View details for DOI 10.1109/TVCG.2018.2793599

    View details for Web of Science ID 000427682500026

    View details for PubMedID 29553930

  • Converting Basic D3 Charts into Reusable Style Templates IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS Harper, J., Agrawala, M. 2018; 24 (3): 1274–86

    Abstract

    We present a technique for converting a basic D3 chart into a reusable style template. Then, given a new data source we can apply the style template to generate a chart that depicts the new data, but in the style of the template. To construct the style template we first deconstruct the input D3 chart to recover its underlying structure: the data, the marks and the mappings that describe how the marks encode the data. We then rank the perceptual effectiveness of the deconstructed mappings. To apply the resulting style template to a new data source we first obtain importance ranks for each new data field. We then adjust the template mappings to depict the source data by matching the most important data fields to the most perceptually effective mappings. We show how the style templates can be applied to source data in the form of either a data table or another D3 chart. While our implementation focuses on generating templates for basic chart types (e.g., variants of bar charts, line charts, dot plots, scatterplots, etc.), these are the most commonly used chart types today. Users can easily find such basic D3 charts on the Web, turn them into templates, and immediately see how their own data would look in the visual style (e.g., colors, shapes, fonts, etc.) of the templates. We demonstrate the effectiveness of our approach by applying a diverse set of style templates to a variety of source datasets.

    View details for DOI 10.1109/TVCG.2017.2659744

    View details for Web of Science ID 000423541200005

    View details for PubMedID 28186898

  • Mosaic: Designing Online Creative Communities for Sharing Works-in-Progress DESIGN THINKING RESEARCH: MAKING DISTINCTIONS: COLLABORATION VERSUS COOPERATION Kim, J., Agrawala, M., Bernstein, M. S., Plattner, H., Meinel, C., Leifer, L. 2018: 105–29

    View details for DOI 10.1007/978-3-319-60967-6_6

    View details for Web of Science ID 000432741300007

  • Improving Comprehension of Measurements Using Concrete Re-Expression Strategies Hullman, J., Kim, Y., Nguyen, F., Speers, L., Agrawala, M., ACM ASSOC COMPUTING MACHINERY. 2018

    View details for DOI 10.1145/3173574.3173608

    View details for Web of Science ID 000509673100034

  • RecipeScape: An Interactive Tool for Analyzing Cooking Instructions at Scale Chang, M., Guillain, L. V., Jung, H., Hare, V. M., Kim, J., Agrawala, M., ACM ASSOC COMPUTING MACHINERY. 2018

    View details for DOI 10.1145/3173574.3174025

    View details for Web of Science ID 000509673105052

  • An Interactive Pipeline for Creating Visual Blends Chilton, L. B., Petridis, S., Agrawala, M., ACM ASSOC COMPUTING MACHINERY. 2018: 188–90

    View details for DOI 10.1145/3266037.3271646

    View details for Web of Science ID 000494261200064

  • Facilitating Document Reading by Linking Text and Tables Kim, D., Hoque, E., Kim, J., Agrawala, M., Assoc Comp Machinery ASSOC COMPUTING MACHINERY. 2018: 423–34

    View details for DOI 10.1145/3242587.3242617

    View details for Web of Science ID 000494260500037

  • Computational Video Editing for Dialogue-Driven Scenes ACM TRANSACTIONS ON GRAPHICS Leake, M., Davis, A., Truong, A., Agrawala, M. 2017; 36 (4)

    View details for DOI 10.1145/3072959.3073653

    View details for Web of Science ID 000406432100098

  • Interactive Design and Stability Analysis of Decorative Joinery for Furniture ACM TRANSACTIONS ON GRAPHICS Yao, J., Kaufman, D. M., Gingold, Y., Agrawala, M. 2017; 36 (2)

    View details for DOI 10.1145/3054740

    View details for Web of Science ID 000400160000008

  • Mosaic: Designing Online Creative Communities for Sharing Works-in-Progress Kim, J., Agrawala, M., Bernstein, M. S., Assoc Comp Machinery ASSOC COMPUTING MACHINERY. 2017: 246–58

    View details for DOI 10.1145/2998181.2998195

    View details for Web of Science ID 000455087800019

  • Shot Orientation Controls for Interactive Cinematography with 360 degrees Video Pavel, A., Hartmann, B., Agrawala, M., ACM ASSOC COMPUTING MACHINERY. 2017: 289-297

    View details for DOI 10.1145/3126594.3126636

    View details for Web of Science ID 000455360100025

  • Scanalog: Interactive Design and Debugging of Analog Circuits with Programmable Hardware Strasnick, E., Agrawala, M., Follmer, S., ACM ASSOC COMPUTING MACHINERY. 2017: 321-330

    View details for DOI 10.1145/3126594.3126618

    View details for Web of Science ID 000455360100028

  • Automatically Visualizing Audio Travel Podcasts Lee, J., Gordon, M., Agrawala, M., Assoc Comp Machinery ASSOC COMPUTING MACHINERY. 2017: 165-167

    View details for DOI 10.1145/3131785.3131818

    View details for Web of Science ID 000494270500048

  • Generating Personalized Spatial Analogies for Distances and Areas Kim, Y., Hullman, J., Agrawala, M., ACM ASSOC COMPUTING MACHINERY. 2016: 38-48

    View details for DOI 10.1145/2858036.2858440

    View details for Web of Science ID 000380532900004

  • Data-driven Adaptive History for Image Editing Chen, H., Wei, L., Hartmann, B., Agrawala, M., Spencer, S. N. ASSOC COMPUTING MACHINERY. 2016: 103-111

    View details for DOI 10.1145/2856400.2856417

    View details for Web of Science ID 000382213700013

  • QuickCut: An Interactive Tool for Editing Narrated Video Anh Truong, Berthouzoz, F., Li, W., Agrawala, M., ACM ASSOC COMPUTING MACHINERY. 2016: 497-507

    View details for DOI 10.1145/2984511.2984569

    View details for Web of Science ID 000387605000046

  • VidCrit: Video-Based Asynchronous Video Review Pavel, A., Goldman, D. B., Hartmann, B., Agrawala, M., ACM ASSOC COMPUTING MACHINERY. 2016: 517-528

    View details for DOI 10.1145/2984511.2984552

    View details for Web of Science ID 000387605000048

  • Capture-Time Feedback for Recording Scripted Narration Rubin, S., Berthouzoz, F., Mysore, G. J., Agrawala, M., ACM ASSOC COMPUTING MACHINERY. 2015: 191-199

    View details for DOI 10.1145/2807442.2807464

    View details for Web of Science ID 000381012500023

  • SceneSkim: Searching and Browsing Movies Using Synchronized Captions, Scripts and Plot Summaries Pavel, A., Goldman, D. B., Hartmann, B., Agrawala, M., ACM ASSOC COMPUTING MACHINERY. 2015: 181-190

    View details for DOI 10.1145/2807442.2807502

    View details for Web of Science ID 000381012500022

  • Interactive Furniture Layout Using Interior Design Guidelines ACM TRANSACTIONS ON GRAPHICS Merrell, P., Schkufza, E., Li, Z., Agrawala, M., Koltun, V. 2011; 30 (4)

    View details for DOI 10.1145/1964921.1964982

    View details for Web of Science ID 000297216400061

  • CommentSpace: Structured Support for Collaborative Visual Analysis Willett, W., Heer, J., Hellerstein, J. M., Agrawala, M., ACM ASSOC COMPUTING MACHINERY. 2011: 3131-3140

    View details for Web of Science ID 000395171603024

  • Perceptual Guidelines for Creating Rectangular Treemaps IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS Kong, N., Heer, J., Agrawala, M. 2010; 16 (6): 990-998

    Abstract

    Treemaps are space-filling visualizations that make efficient use of limited display space to depict large amounts of hierarchical data. Creating perceptually effective treemaps requires carefully managing a number of design parameters including the aspect ratio and luminance of rectangles. Moreover, treemaps encode values using area, which has been found to be less accurate than judgments of other visual encodings, such as length. We conduct a series of controlled experiments aimed at producing a set of design guidelines for creating effective rectangular treemaps. We find no evidence that luminance affects area judgments, but observe that aspect ratio does have an effect. Specifically, we find that the accuracy of area comparisons suffers when the compared rectangles have extreme aspect ratios or when both are squares. Contrary to common assumptions, the optimal distribution of rectangle aspect ratios within a treemap should include non-squares, but should avoid extremes. We then compare treemaps with hierarchical bar chart displays to identify the data densities at which length-encoded bar charts become less effective than area-encoded treemaps. We report the transition points at which treemaps exhibit judgment accuracy on par with bar charts for both leaf and non-leaf tree nodes. We also find that even at relatively low data densities treemaps result in faster comparisons than bar charts. Based on these results, we present a set of guidelines for the effective use of treemaps and suggest alternate approaches for treemap layout.

    View details for Web of Science ID 000283758600016

    View details for PubMedID 20975136

  • Sizing the Horizon: The Effects of Chart Size and Layering on the Graphical Perception of Time Series Visualizations 27th Annual CHI Conference on Human Factors in Computing Systems Heer, J., Kong, N., Agrawala, M. ASSOC COMPUTING MACHINERY. 2009: 1303–1312

    View details for Web of Science ID 000265679301014

  • Visualizing dynamic architectural environments COMMUNICATIONS OF THE ACM Houston, M., Niederauer, C., Agrawala, M., Humphreys, G. 2004; 47 (8): 54-59

    View details for Web of Science ID 000222905900015

  • Non-invasive interactive visualization of dynamic architectural environments Annual Symposium of the ACM SIGGRAPH Niederauer, C., Houston, M., Agrawala, M., Humphreys, G. ASSOC COMPUTING MACHINERY. 2003: 700–700

    View details for Web of Science ID 000184291700058

  • Designing effective step-by-step assembly instructions Annual Symposium of the ACM SIGGRAPH Agrawala, M., Phan, D., Heiser, J., Hayrnaker, J., Klingner, J., Hanrahan, P., Tversky, B. ASSOC COMPUTING MACHINERY. 2003: 828–37

    View details for Web of Science ID 000184291700075

  • Cognitive design principles for visualizations: Revealing and instantiating 25th Annual Conference of the Cognitive-Science-Society Heiser, J., Tversky, B., Agrawala, M., Hanrahan, P. LAWRENCE ERLBAUM ASSOC PUBL. 2003: 545–550

    View details for Web of Science ID 000232001900111

  • Sketches for design and design of sketches Conference on Human Behaviour in Design Tversky, B., Suwa, M., Agrawala, M., Heiser, J., Stolte, C., Hanrahan, P., Phan, D., Klingner, J., Daniel, M. P., Lee, P., Haymaker, J. SPRINGER-VERLAG BERLIN. 2003: 79–86

    View details for Web of Science ID 000185894200007

  • Conveying shape and features with image-based relighting IEEE Visualization 2003 Conference Akers, D., Losasso, F., Klingner, J., Agrawala, M., Rick, J., Hanrahan, P. IEEE. 2003: 349–354

    View details for Web of Science ID 000189041100042

  • Rendering effective route maps: Improving usability through generalization SIGGRAPH 2001 Agrawala, M., Stolte, C. ASSOC COMPUTING MACHINERY. 2001: 241–250

    View details for Web of Science ID 000173048800025

  • Efficient image-based methods for rendering soft shadows Computer Graphics Annual Conference Agrawala, M., Ramamoorthi, R., Heirich, A., Moll, L. ASSOC COMPUTING MACHINERY. 2000: 375–384

    View details for Web of Science ID 000165991100042

  • Artistic multiprojection rendering 11th Eurographics Workshop on Rendering Agrawala, M., Zorin, D., Munzner, T. SPRINGER-VERLAG WIEN. 2000: 125-?

    View details for Web of Science ID 000166978600012

  • Model-based compression for synthetic animations International Conference on Image Processing (ICIP-96) Chaddha, N., Agrawala, M., Beers, A. IEEE. 1996: 417–420

    View details for Web of Science ID A1996BG63F00105

https://orcid.org/0000-0002-8996-7327