About

Brian Herman is a professor in the Department of Biomedical Engineering at the University of Minnesota. His research focuses on the role and regulation of caspase-2 (Casp2) in degenerative diseases associated with aging. His laboratory was the first to describe a role for Casp2 in aging, and his work has documented that Casp2 regulates cellular redox status and is necessary for mitochondrial ROS-induced apoptosis in neurons. In neuronal cells and tissue, his research demonstrated that Casp2 resides in the brain mitochondrial matrix, is activated in a mitochondrial ROS-dependent fashion, mediates apoptosis directly from the mitochondrial compartment, and that loss of Casp2 increases resistance of the nigrostriatal dopaminergic pathway to MPTP-induced toxicity. His studies suggest that Casp2 mediates damage to CNS neurons under stress conditions such as excitotoxicity, increased ROS, exposure to Aβ or MPTP, neonatal stroke, retinal ischemia, and transgenic expression of mutant proteins like APP, huntingtin, or tau, indicating that targeting Casp2 may benefit multiple neurological conditions. Additionally, he was the first to describe a novel role for Casp2 as a negative regulator of autophagy via downregulation of the MTOR pathway and upregulation of AMPK activation. His recent research has concentrated on the role of Casp2 in tauopathies. His significant contributions to the field have earned him multiple honors, including listings in American Men and Women of Science, awards from the American Cancer Society, the Presidential Distinguished Senior Scholar Award, the Dozer Fellowship from Ben Gurion University in Israel, and two NIH MERIT Awards, recognizing him as one of the top scientists in the United States.

Research topics

• Artificial Intelligence
• Computer Science
• Human–computer interaction
• Computer graphics (images)

Selected publications

• Hybrid data constructs: Interacting with biomedical data in augmented spaces

  2022-01-01

  other
  PublisherDOI

• Multi-Touch Querying on Data Physicalizations in Immersive AR

  Proceedings of the ACM on Human-Computer Interaction · 2021 · 15 citations

  1st authorCorresponding
  • Computer Science
  • Computer Science
  • Computer graphics (images)

  Data physicalizations (3D printed terrain models, anatomical scans, or even abstract data) can naturally engage both the visual and haptic senses in ways that are difficult or impossible to do with traditional planar touch screens and even immersive digital displays. Yet, the rigid 3D physicalizations produced with today's most common 3D printers are fundamentally limited for data exploration and querying tasks that require dynamic input (e.g., touch sensing) and output (e.g., animation), functions that are easily handled with digital displays. We introduce a novel style of hybrid virtual + physical visualization designed specifically to support interactive data exploration tasks. Working toward a "best of both worlds" solution, our approach fuses immersive AR, physical 3D data printouts, and touch sensing through the physicalization. We demonstrate that this solution can support three of the most common spatial data querying interactions used in scientific visualization (streamline seeding, dynamic cutting places, and world-in-miniature visualization). Finally, we present quantitative performance data and describe a first application to exploratory visualization of an actively studied supercomputer climate simulation data with feedback from domain scientists.

  PublisherOA PDFDOI

• Printmaking, Puzzles, and Studio Closets: Using Artistic Metaphors to Reimagine the User Interface for Designing Immersive Visualizations

  2020-10-01

  preprintOpen access1st authorCorresponding

  We, as a society, need artists to help us interpret and explain science, but what does an artist's studio look like when today's science is built upon the language of large, increasingly complex data? This paper presents a data visualization design interface that lifts the barriers for artists to engage with actively studied, 3D multivariate datasets. To accomplish this, the interface must weave together the need for creative artistic processes and the challenging constraints of real-time, data-driven 3D computer graphics. The result is an interface for a technical process, but technical in the way artistic printmaking is technical, not in the sense of computer scripting and programming. Using metaphor, computer graphics algorithms and shader program parameters are reimagined as tools in an artist's printmaking studio. These artistic metaphors and language are merged with a puzzle-piece approach to visual programming and matching iconography. Finally, artists access the interface using a web browser, making it possible to design immersive multivariate data visualizations that can be displayed in VR and AR environments using familiar drawing tablets and touch screens. We report on insights from the interdisciplinary design of the interface and early feedback from artists.

  PublisherOA PDFDOI

• Printmaking, Puzzles, and Studio Closets: Using Artistic Metaphors to\n Reimagine the User Interface for Designing Immersive Visualizations

  arXiv (Cornell University) · 2020-10-17

  preprintOpen access1st authorCorresponding

  We, as a society, need artists to help us interpret and explain science, but\nwhat does an artist's studio look like when today's science is built upon the\nlanguage of large, increasingly complex data? This paper presents a data\nvisualization design interface that lifts the barriers for artists to engage\nwith actively studied, 3D multivariate datasets. To accomplish this, the\ninterface must weave together the need for creative artistic processes and the\nchallenging constraints of real-time, data-driven 3D computer graphics. The\nresult is an interface for a technical process, but technical in the way\nartistic printmaking is technical, not in the sense of computer scripting and\nprogramming. Using metaphor, computer graphics algorithms and shader program\nparameters are reimagined as tools in an artist's printmaking studio. These\nartistic metaphors and language are merged with a puzzle-piece approach to\nvisual programming and matching iconography. Finally, artists access the\ninterface using a web browser, making it possible to design immersive\nmultivariate data visualizations that can be displayed in VR and AR\nenvironments using familiar drawing tablets and touch screens. We report on\ninsights from the interdisciplinary design of the interface and early feedback\nfrom artists.\n

  PublisherOA PDFDOI

• Poster: Automatic Generation of Data Legends for 3D Multi-Variate Artist Driven Visualizations

  IEEE Visualization · 2020-01-01

  article
  Publisher

• Human Fingerprints and Artistic Vocabulary; Rendering Data, Creating Engagement, Connection and Context to Earth System Models

  2020-12-08

  article

• Artifact-Based Rendering: Harnessing Natural and Traditional Visual Media for More Expressive and Engaging 3D Visualizations

  IEEE Transactions on Visualization and Computer Graphics · 2019-01-01 · 25 citations

  articleOpen access

  We introduce Artifact-Based Rendering (ABR), a framework of tools, algorithms, and processes that makes it possible to produce real, data-driven 3D scientific visualizations with a visual language derived entirely from colors, lines, textures, and forms created using traditional physical media or found in nature. A theory and process for ABR is presented to address three current needs: (i) designing better visualizations by making it possible for non-programmers to rapidly design and critique many alternative data-to-visual mappings; (ii) expanding the visual vocabulary used in scientific visualizations to depict increasingly complex multivariate data; (iii) bringing a more engaging, natural, and human-relatable handcrafted aesthetic to data visualization. New tools and algorithms to support ABR include front-end applets for constructing artifact-based colormaps, optimizing 3D scanned meshes for use in data visualization, and synthesizing textures from artifacts. These are complemented by an interactive rendering engine with custom algorithms and interfaces that demonstrate multiple new visual styles for depicting point, line, surface, and volume data. A within-the-research-team design study provides early evidence of the shift in visualization design processes that ABR is believed to enable when compared to traditional scientific visualization systems. Qualitative user feedback on applications to climate science and brain imaging support the utility of ABR for scientific discovery and public communication.

  PublisherOA PDFDOI

• [Clinician vs. the machine].

  PubMed · 1972-01-01

  article1st authorCorresponding
  Publisher

Frequent coauthors

• Daniel F. Keefe

  University of Minnesota

  16 shared

• Francesca Samsel

  Texas Advanced Computing Center

  10 shared

• Seth Johnson

  University of Mississippi Medical Center

  9 shared

• Greg Abram

  6 shared

• Annie Bares

  5 shared

• Stephanie Zeller

  2 shared

• Greg Abram

  2 shared

• Andrew Solis

  The University of Texas at Austin

  2 shared

Labs

• Tissue Mechanics LaboratoryPI

Awards & honors

• American Men and Women of Science
• American Cancer Society Faculty Research Award
• Presidential Distinguished Senior Scholar Award
• Dozer Fellowship from Ben Gurion University, Israel
• MERIT Award (10 year) from the National Institutes of Health