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Dennis Bromley

Researcher at University of Washington

Publications -  20
Citations -  566

Dennis Bromley is an academic researcher from University of Washington. The author has contributed to research in topics: Mutant & User interface. The author has an hindex of 12, co-authored 20 publications receiving 553 citations. Previous affiliations of Dennis Bromley include Mitsubishi Electric & Mitsubishi Electric Research Laboratories.

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Journal ArticleDOI

Dynameomics: A Comprehensive Database of Protein Dynamics

TL;DR: This work has performed molecular dynamics simulations of the native state and unfolding pathways of over 2000 protein/peptide systems representing the majority of folds in globular proteins, stored and organized using an innovative database approach.
Patent

Artificial intelligence platform

TL;DR: In this article, the authors present a new and unique platform for authoring and deploying interactive characters which are powered by artificial intelligence, which allows the creation of a virtual world populated by multiple characters and objects, interacting with one another so as to create a life-like virtual world and interacting with a user.
Proceedings ArticleDOI

Interactive storytelling environments: coping with cardiac illness at Boston's Children's Hospital

TL;DR: Preliminary analysis of young patients of the SAGE environment indicates that children used different modes of interaction-direct, mediated, and differed-, depending upon what personae the narrator chooses to take on, according to the mindset and health condition of the child.
Patent

Anonymous verifiable public key certificates

TL;DR: In this paper, the anonymity of a user at a client computer was preserved when authenticating with an on-line service or content provider through the use of an anonymous and verifiable (i.e., "blind") certificate set that is created by a certificate authority from a fixed-size set of PKI key pairs.
Journal ArticleDOI

DIVE: A Graph-Based Visual-Analytics Framework for Big Data

TL;DR: DIVE is a data-agnostic, ontologically expressive software framework that can stream large datasets at interactive speeds that makes novel contributions to structured-data-model manipulation and high-throughput streaming of large, structured datasets.