Loyola Marymount University's Carnegie Classification is R2 Doctoral University: High Research Activity. LMU Computer Science offers a variety of research programs with student researchers from all years (from first-years to seniors as well as graduate students) actively participating in various research activities. Students from several majors work alongside computer science students in research teams housed within LMU computer science, and computer science students participate in research programs affiliated with other departments.

Many undergraduate students work side-by-side with faculty members on major research projects. Students have the opportunity to present the results of their research at regional, national and international conferences. A few of the department's research activities are outlined below.


  • Gene Regulatory Mapping

    A strong research group made up of many majors from computer science and related fields has been active for years under the direction of Prof. John David Dionisio (Computer Science) and Prof. Kam Dahlquist (Biology). One of the notable activities of this group is GRNSight, an open source tool suite for automatically visualizing models of gene regulatory networks. GRNSight is a successor to GenMAPP (Gene Map Annotator and Pathway Profiler), software for viewing and analyzing DNA microarray and other genomic and proteomic data on biological pathways.

  • Applied Cognitive Technologies

    The Applied Cognitive Technologies Lab (ACT Lab) is a research group directed by Prof. Andrew Forney whose interests are found at the intersection of artificial intelligence, cognitive psychology, and experimental design. The bulk of the group's work focuses on formalizing the human analogs of causal and counterfactual reasoning and how those abilities shape our learning and decisions. Additionally, Dr. Forney sponsors a wide swath of student interests in undergraduate research projects, including: bias detection in online news articles, correcting for human biases in decision-making tasks, modeling learning from regret to make artificial agents more dynamic, and individualized difficulty adjustment in video games.

    For more on the ACT Lab and a list of student research projects, see Prof. Forney's ACT Lab page.

    Drawing of students in ACT Lab, by Christian Santander, '20
  • Collaborative Systems

    Dr. Freitas leads a team of students exploring the fundamental tension between data privacy and openness in research, and developing design principles for equitable, collaborative data management systems. Popular tools for data collection, cleaning, analysis, and sharing can benefit certain stakeholder groups over others depending on how they are designed and implemented. More accurate study of complex social issues depends on whether new tools enable differing perspectives to be reflected in the process and results of data analysis.

    Projects revolve around case studies where collaborative data management and analysis are central requirements, as well as contributions to existing open source data management tools. Current projects include:

    • Crowd-sourcing platform labels for EEG data
    • Mobile data collection for clinical trials, in collaboration with the PECET at University of Antioquia, Colombia
    • Extensions for adding new functionality to differential privacy libraries
  • Conversational Agents
    Conversational Agents

    The conversational agents group led by Professor Mandy Korpusik conducts research related to artificial intelligence, natural language processing, and speech recognition. In particular, they investigate machine learning methods such as deep neural networks and reinforcement learning for understanding spoken natural language.

    Many of the undergraduate research projects in this group contribute to the overarching Coco Nutritionist spoken dialogue system, which simplifies diet tracking by allowing users to describe their meal naturally. Current research projects include:

    • Building a nutrition-specific speech recognizer,
    • Spoken exercise logging,
    • Mapping user-described quantities to the USDA food database's standard units, and
    • Personalized food recommendations.
    The Virtual Engineering Sciences Learning Lab (VESLL) project is establishing an online interactive learning environment built around a functional laboratory designed to introduce students to engineering concepts through visualization and collaborative problem solving. Our long-term vision is to create a virtual version of a science museum such as the Exploratorium in San Francisco, the Pacific Science Center in Seattle, or the California Science Center in Los Angeles to provide virtual visitors the opportunity to delve into engineering concepts and maintain a sense of excitement about the concepts they experience. VESLL enhances student learning via multi-modal pedagogical strategies while increasing student engagement via a welcoming dynamic environment, designed to be conducive to women and other diverse audiences. As part of an initiative to move engineering education into the 21st Century, VESLL represents an exploration of the many benefits of virtual learning environments, including: enhanced opportunities for visualization, immediate feedback, student autonomy, increased access to resources without the demands of co-presence, multiple communication channels for student interaction with peers and instructors, and innovative ways to evaluate student learning.

    To explore VESLL, a student would create an avatar in Second Life and via the avatar visit VESLL as they might visit a brick-and-mortar science museum. They would begin by entering an orientation center, then proceed to the various work areas or visit virtual meeting areas within VESLL to discuss ideas or collaborate with other students, faculty, and visitors. Our long term vision is to create a virtual version of these institutions that delves more deeply into the engineering concepts they present to the general public without losing the sense of excitement they provide. The engineering modules would present virtual objects for demonstration and experimentation in a social environment while encouraging socially aware community problem solving of social problems, such as providing clean water to a rural community.

    VESLL enjoys support from the NSF via Award No. 0935100, obtained by Prof. Stephanie August (Computer Science) and Prof. Michelle Hammers (Communications).

  • Experimental Programming Languages
    The Experimental Languages Group (xlg) is an informal working group doing research and development on programming language design. Rather than asking questions about design patterns for solving problems, the group is interested in patterns of language design and questions about languages themselves, such as:
    • Is a language's syntax minimalistic (like Lisp) or sophisticated?
    • How are control structures specified?
    • Is the text word-oriented or does it make heavy use of symbols and punctuation?
    • Is the language extensible? Does it employ macros? Does it allow embeddings of other languages?
    • Are advanced control structures, such as concurrency, intrinsic to the language or does the language sport a small core with most functionality in (external) libraries?
    • What kind of paradigms are naturally expressed?
    • Does the language make it easy or hard to create immutable collections?
    • Is typing static or dynamic? Strong or weak? Manifest or implicit?
    • How are modules, with interfaces and information hiding, supported? Are there special structures to hold state? Does the language rely on closures?
    • Does the language allow introspection? Dynamic compilation? Can pieces of programs be generated at run time?

    In addition to studying, classifying, and suggesting improvements to existing languages, the group collaborates on the design and implementation of new research languages. The group is also looking into alternative methods for specifying syntax and semantics, novel approaches to compiler generation, machine-assisted program correctness proofs, and efficient implementations.

  • Identity Mapping
    The Identity Mapping Project (IMP) is an interdisciplinary collaboration between Psychology and Computer Science designed to empirically investigate the development of distributed forms of identity. Methodologically, it collects a large database of “identity maps”—computerized graphical representations of how active someone is online and how their identity is expressed and distributed across seven core digital domains: email, blogs/personal websites, social networks, online forums, online dating sites, character based digital games, and virtual worlds. Principal investigators include Drs. Forney, Dionisio and Dorin from Computer Science and Dr. Gilbert from Psychology.
  • Recourse
    A fair amount of our in-house computing facilities, and much of our hands-on, practical, open-source-based curriculum, has roots in an NSF grant (Award 0511732, Cultivating an Open Source Software Culture Among Computer Science Undergraduate Students ) obtained by several members of the Computer Science faculty. Profs. Dionisio and Toal were the principal investigators.

    The project was instrumental in creating a culture influenced by the values of the Open Source Initiative's Open Source Definition.