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John David N. Dionisio - Loyola Marymount University. Los Angeles, CA, US

John David N. Dionisio John David N. Dionisio

Chair and Professor of Computer Science | Loyola Marymount University


Seaver College of Science and Engineering



John David N. Dionisio Publication John David N. Dionisio Publication






Phone: 310.338.5782
Email: dondi@lmu.edu
Office: Doolan Hall 106

John Dionisio is a Professor in the Department of Electrical Engineering and Computer Science at LMU. He started teaching part-time at LMU in 2002, joining the faculty full-time in 2004. Prior to that, Dr. Dionisio was a part of the Medical Imaging Informatics group at UCLA, which he had joined shortly after receiving his Ph.D. in computer science from the same institution in December, 1996. Dr. Dionisio also works as a consultant and software developer in local industry (a.k.a. Silicon Beach). From 2002 to 2012 he helped develop health care information systems with Medaxis Corporation, a company he co-founded. Since then, he has done work for DataPop (now Criteo) in Culver City, Friendbuy in Los Angeles, and Toku Technologies in West LA. Dr. Dionisio is a member of the Association for Computing Machinery (ACM) with special interests in computer-human interaction (SIGCHI), computer graphics (SIGGRAPH), and computer science education (SIGCSE).

Education (3)

University of California at Los Angeles: Ph.D., Computer Science 1996

University of California at Los Angeles: M.A., Computer Science 1993

Loyola Marymount University: B.Sc., Computer Science 1991

Areas of Expertise (3)

Computer Science

Interaction Design

Computer Graphics

Industry Expertise (7)




Computer Software

Computer Networking


IT Services/Consulting

Affiliations (3)

  • Undivided
  • Zoodiker
  • Friendbuy

Languages (5)

  • JavaScript
  • Python
  • Swift
  • Java
  • C

Event Appearances (1)


Beyond Biology 2010  Washington, DC


Courses (7)

CMSI 1010: Computer Programming & Laboratory

This course introduces you to the art and craft of computer programming, and in so doing seeks to also expose you to the discipline of computer science and best practices of software development.

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CMSI 2022 Mobile Application Development

This is a two-unit practicum course, meaning you will receive training and gain experience building systems according to modern best practices. All computer science majors must complete this or Web Application Development (CMSI 2021) in order to experience full-stack development before undertaking the rigorous courses in the junior and senior years.

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CMSI 3520: Database Systems

This course introduces the computer science subfield of databases, which is concerned with the theory, design, and implementation of systems that manage large amounts of data.

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CMSI 3710: Computer Graphics

This course explores the computer science subfield of computer graphics the study and development of algorithms for synthesizing, manipulating, and displaying visual information.

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CMSI 370: Interaction Design

This course explores the computer science subfield of interaction design (IxD), a.k.a. computer-human (or human-computer) interaction (CHI/HCI). IxD seeks to understand human behavior when interacting with computing systems and studies metrics, techniques, and theories for achieving effective interaction.

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HNRS 2000: Research & Exhibition

This course introduces you to formal, mentored academic research and creative work.

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HNRS 2200: Cogitations on Computation (Honors Nature of Science, Technology, & Mathematics)

The course aims to introduce you to the theory and practice of computation as a scientific and engineering endeavor.

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Articles (10)

Impact of Late Policies on Submission Behavior and Grades in Computer Programming

American Society for Engineering Education

Korpusik M, Freitas J, Dionisio JDN


This paper investigates the effect of four different late policies on submission behavior and grades in an introductory Computer Programming Lab class taught in the Java programming language at Loyola Marymount University, a primarily undergraduate university. To ensure grading consistency across sections, every student was randomly assigned two labs per late policy, for a total of eight labs completed over the course of the semester. The four late policies consisted of: 1) No penalty for late submissions, 2) Early incentive (one extra credit point awarded per day early the lab was submitted, up to three points max), 3) Late penalty (25% off within 24 hours of the deadline, 50% off for 24-48 hours late, 75% off for 48-72 hours late, and zero credit after 72 hours), and 4) Combined (early incentive combined with a late penalty). For our quantitative and qualitative study, we measured, per policy (for a total of 248 submitted labs), the average lab grade and the average number of days the labs were submitted early or late, as well as the average student rankings (from 1 to 4, where 1 was their favorite and 4 their least favorite policy). We found that while students rated Early Incentive the highest, the policy with the highest lab grades and submitted the earliest on average was the Combined early incentive with a late penalty. The worst grades were for No penalty, which may suggest a late penalty is necessary to keep students on track.

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Immersion Trip

MIT Technology Review

Dionisio JDN


The metaverse might sound like an internet catchphrase, but the concept has potential to change how we think about pain management, grieving, and systemic prejudice.

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GRNsight: a web application and service for visualizing models of small- to medium-scale gene regulatory networks

PeerJ Computer Science

Dahlquist KD, Dionisio JDN, Fitzpatrick BG, Anguiano NA, Varshneya A, Southwick BJ, Samdarshi M


GRNsight is a web application and service for visualizing models of gene regulatory networks (GRNs). A gene regulatory network (GRN) consists of genes, transcription factors, and the regulatory connections between them which govern the level of expression of mRNA and protein from genes. The original motivation came from our efforts to perform parameter estimation and forward simulation of the dynamics of a differential equations model of a small GRN with 21 nodes and 31 edges. We wanted a quick and easy way to visualize the weight parameters from the model which represent the direction and magnitude of the influence of a transcription factor on its target gene, so we created GRNsight. GRNsight automatically lays out either an unweighted or weighted network graph based on an Excel spreadsheet containing an adjacency matrix where regulators are named in the columns and target genes in the rows, a Simple Interaction Format (SIF) text file, or a GraphML XML file. When a user uploads an input file specifying an unweighted network, GRNsight automatically lays out the graph using black lines and pointed arrowheads. For a weighted network, GRNsight uses pointed and blunt arrowheads, and colors the edges and adjusts their thicknesses based on the sign (positive for activation or negative for repression) and magnitude of the weight parameter. GRNsight is written in JavaScript, with diagrams facilitated by D3.js, a data visualization library. Node.js and the Express framework handle server-side functions. GRNsight’s diagrams are based on D3.js’s force graph layout algorithm, which was then extensively customized to support the specific needs of GRNs. Nodes are rectangular and support gene labels of up to 12 characters. The edges are arcs, which become straight lines when the nodes are close together. Self-regulatory edges are indicated by a loop. When a user mouses over an edge, the numerical value of the weight parameter is displayed. Visualizations can be modified by sliders that adjust the force graph layout parameters and through manual node dragging. GRNsight is best-suited for visualizing networks of fewer than 35 nodes and 70 edges, although it accepts networks of up to 75 nodes or 150 edges. GRNsight has general applicability for displaying any small, unweighted or weighted network with directed edges for systems biology or other application domains.

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3D Virtual worlds and the metaverse: Current status and future possibilities

ACM Computing Surveys (CSUR)

Dionisio JDN, Burns WG, Gilbert R


Moving from a set of independent virtual worlds to an integrated network of 3D virtual worlds or Metaverse rests on progress in four areas: immersive realism, ubiquity of access and identity, interoperability, and scalability. For each area, the current status and needed developments in order to achieve a functional Metaverse are described.

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Standards-based grading: Preliminary studies to quantify changes in student affective and cognitive behaviors

Proceedings of IEEE Frontiers in Education (FIE) 2012

Carberry AR, Siniawski MT, Dionisio JDN


Assessing student learning is a key component to education. Most institutions assess learning using a score-based grading system. Such systems use multiple individual assignment scores to produce a cumulative final course grade, which may or may not represent what a student has learned.

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Improving the computer science in bioinformatics through open source pedagogy


Dionisio JDN, Dahlquist KD


Bioinformatics relies more than ever on information technologies. This pressures scientists to keep up with software development best practices. However, traditional computer science curricula do not necessarily expose students to collaborative and long-lived software development.

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An open source software culture in the undergraduate computer science curriculum


Dionisio JDN, Dickson CL, August SE, Dorin PM, Toal R


Open source software has made inroads into mainstream computing where it was once the territory of software altruists, and the open source culture of technological collegiality and accountability may benefit education as well as industry. This paper describes the Recourse project, which seeks to transform the computer science undergraduate curriculum through teaching methods based on open source principles, values, ethics, and tools.

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StructConsult: Structured Real-Time Wet Read Consultation Infrastructure to Support Patient Care

Studies in Health Technology and Informatics

Morioka C, Dionisio JDN, Bui AA, El-Saden S, Kangarloo H


Our research addresses how to improve physician to physician communication of patient information, and how to prevent lapses of patient care as they are referred to other clinicians within the healthcare system. The wet read consultation is defined as a rapid response to a clinical question posed by a referring physician to a clinical specialist.

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A Unified Data Model for Representing Multimedia, Timeline, and Simulation Data

IEEE Transactions on Knowledge and Data Engineering

Dionisio JDN, Cárdenas AF


This paper describes a unified data model that represents multimedia, timeline, and simulation data utilizing a single set of related data modeling constructs. A uniform model for multimedia types structures image, sound, video, and long text data in a consistent way, giving multimedia schemas and queries a degree of data independence even for these complex data types. Information that possesses an intrinsic temporal element can all be represented using a construct called a stream. Streams can be aggregated into parallel multistreams, thus providing a structure for viewing multiple sets of time-based information. The unified stream construct permits real-time measurements, numerical simulation data, and visualizations of that data to be aggregated and manipulated using the same set of operators. Prototypes based on the model have been implemented for two medical application domains: thoracic oncology and thermal ablation therapy of brain tumors. Sample schemas, queries, and screenshots from these domains are provided. Finally, a set of examples is included for an accompanying visual query language discussed in detail in another document.

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MQuery: A Visual Query Language for Multimedia, Timeline, and Simulation Data

Journal of Visual Languages and Computing

Dionisio JDN, Cárdenas AF


This paper describes a visual query language that can express questions over multimedia, timeline and simulation data using a single set of related query constructs. A uniform model for multimedia types organizes image, sound, video and long text data in a consistent manner, giving multimedia schemas and queries a degree of data independence even for these complex data types. Information that possesses an intrinsic temporal element can be queried using a construct called a stream. Streams can be aggregated into parallel multistreams, thus providing a structure for querying and retrieving multiple sets of time-based information. The unified stream construct permits real-time measurements, numerical simulation data and visualizations of that data to be aggregated and manipulated using the same set of operators.

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