Research in Computer Science


code on screen

Security and Privacy

A stable, safe, and resilient cyberspace is vital for our economic and societal wellbeing. This concentration helps students learn how to fortify cyber networks, combat threats, and foster “white hat” hacking. Researching systems allows for students to improve real-world systems to make them stronger and securer. This also includes data-driven analysis of privacy and social networks. After graduation, our students often work either in private corporations or in governments.

Labs: OSIRISCCS

Sample research projects:

Screenshot of Damon McCoy's PharmaLeaks presentation

Damon McCoy, one of the department's newest faculty members, researched counterfeit pharmacy affiliate networks. Online sales of counterfeit or unauthorized products drive a robust underground advertising industry that includes email spam, “black hat” search engine optimization, forum abuse and so on. Virtually everyone has encountered enticements to purchase drugs, prescription-free, from an online “Canadian Pharmacy.” However, even though such sites are clearly economically motivated, the shape of the underlying business enterprise is not well understood precisely because it is “underground.”

Learn more about the business of online pharmaceutical affiliate programs here

Example of Digital Assembly technology.Working in digital forensics and recovery, Nasir Memon, CSE department professor, with a team of PhD students, founded the Digital Assembly company. This company works in products that recover digital photos that are fragmented or deleted.

Learn more about Digital Assembly here

Seattle skylineJustin Cappos has been developing an open peer-to-peer computing system, Seattle. Nearly 100 students participated in its creation. The purpose of this project is to make cloud computing available to everyone. It's free and provides access to computers worldwide. This project was funded by the National Science Foundation.

Learn more about Seattle Open Peer-to-Peer Computing here

 

Retirement portfolio simulatorPeople increasingly make important life decisions based on large amounts of data, using online tools. Professor Oded Nov works with students and collaborators to explore how novel computational tools and user interface design informed by social science can help people make sense and reason better about such data and their personal implications. In a series of studies, Nov and his doctoral student Junius Gunaratne showed how design informed by research in psychology and economics can help consumers make informed decisions and outperform users of traditional financial user interfaces. In another series of studies, Nov and his doctoral student Martina Balestra and their collaborators showed how design interventions affect users' understanding of and level of engagement with their personal genomic data. In another line of research, Nov and Professor Maurizio Porfiri study how design interventions help impact the behavior of contributors to citizen science projects.


Big Data Management, Analysis, and Visualization

The organization and governance of large volumes of data. This concentration allows for retaining data obtained from a large number of sources—from a large city, to individuals, and anywhere in between—and ensures a high level of data quality for analytical purposes. The visualization of such data elegantly brings structure and simplicity to it.

Labs: CUSP

Sample research projects:

Screenshot of RevExEnrico Bertini, in conjunction with PhD students Christian Felix Da Silva and Anshul Pandey, developed RevEx. A collaboration with ProPublica, this tool visualizes Yelp data and has the ability to single out reviews under specific parameters or keywords. The tool can sort through millions of reviews at one time and visualize trends.

Learn more about RevEx and download the demo here

Example of neuroimagingGuido Gerig, department chair, focuses on clinical neuroimaging to assist in studying such areas as early childhood brain development, children with autism, and infants at risk of schizophrenia. His methodology includes image processing, registration, atlas building, segmentation, shape analysis, and statistical analysis.

In this related paper, Gerig studies the early developing brain by displaying the longitudinal MRI scans of the same subject's brain at various ages, from two weeks to two years.

See more of the study here

Figure graphing the prevalence of activity-related interests and obesity in the US. Figure graphing the prevalence of activity-related interests and obesity in the USAssistant Professor Rumi Chunara works at the intersection of Big Data and Public Health, using information gleaned from social media sites like Facebook and Twitter to predict epidemics, track obesity rates on a local level, and much more.

In Prof. Chunara's research on US obesity rates, for example, Facebook is used to cross-measure user interests and obesity prevalence within certain metroplitan populations. Activity-related interests across the US and sedentary-related interests across NYC were significantly associated with obesity prevalence.

Learn more about Prof. Chunara's study here

Graph exemplifying building data analysisSemiha Ergan, an affiliate professor of the Computer Science and Engineering Department, is responsible for a project that performs data analysis on highly sensed buildings for understanding patterns in building performance. The data deals with HVAC systems and energy use in such buildings to assist in building management strategies.

Prof. Ergan is also the head of the Future Building Informatics and Visualization Lab (biLab).

Learn more about the project here


Game Engineering and Computational Intelligence

For students who are interested in learning game programming and taking part in game development and design. Computer graphics, human-computer interaction, artificial intelligence, and allied computational fields all play a role in this burgeoning industry. Art and engineering intersect to create innovative game environments that captivate players.

Labs: Game Innovation LabMAGNET

Sample research projects:

 

Best without Domain Knowledge: MCTS Modifications in Mario

Professor Julian Togelius specializes in artificial intelligence, and has programmed AI agents that play several existing video games. In the clip above, an AI agent plays through Super Mario Bros.

Learn more about Professor Julian Togelius's project here

RigMesh

Professor Andy Nealen, working in conjunction with PhD student Ming Jin, is perfecting RigMesh, a 3-D modeling and rigging program that, when completed, will be very intuitive to use. Compared to other modeling programs that require a great deal of time and effort to create a 3-D model of an object as well as the rig—the underlying skeleton that gives the model its articulation points and allows it to move—a user can simply "draw" the model using the mouse within minutes. The rig is then automatically placed and articulation points can be added or removed easily where needed.

Animating the model is simplified under RigMesh, as well. Instead of setting up key frames and moving the rigs, as in traditional 3-D animation, RigMesh utilizes digital cameras. A user can key a model's rig to a person standing in front of a camera and that person's movements will in turn animate the model. This method of animating is more time-efficient and inexpensive.

Learn more about RigMesh here


Algorithms and Theoretical Computer Science

The theories of computer science are what make computers possible. Algorithms include computational calculation and automated reasoning, while theoretical computer science deals with the mathematical aspects of computing. These theories help engineers build on our current knowledge of computers in order to invent breakthroughs, paving the way to better and newer solutions.

Sample research projects:

John Iacono is the co-author of "Cache-Oblivious Persistence." Partial persistence is a general transformation that takes a data structure and allows queries to be executed on any past state of the structure. The cache-oblivious model is the leading model of a modern multi-level memory hierarchy. This paper presents the first general transformation for making cache-oblivious model data structures partially persistent.

Read the paper here (pdf)

Boris Aronov co-wrote a paper titled "Improved Bounds for the Union of Locally Fat Objects in the Plane." In this paper, they obtain sharper upper bounds on the complexity of the union of n locally γ-fat objects of constant complexity in the plane, and of n γ-fat triangles in the plane.

Read the paper here (pdf)