![\"ASSET](\"https:\/\/web.uri.edu\/cs\/wp-content\/uploads\/sites\/1531\/asset_logo_svg_png.jpg\"){kind=logo}
<\/div>ASSET Lab<\/h2>
The Accessible and Socially Aware Technologies (ASSET) lab explores the frontiers of research in computer science in our quest to build technologies for marginalized populations<\/strong>. The lab works in a multidisciplinary space at the intersection of accessibility, human-computer interaction, and applied machine learning, often taking inspiration from ideas, theories, and methodologies from the humanities and social sciences to understand and address technical problems.<\/p><\/div><\/div> My research group focuses on algorithms and data structures for \u201cbig data,\u201d with applications to computational biology and more recently astronomy, among other areas. We are particularly interested in the \u201cmanifold hypothesis\u201d and how interesting geometric and topological properties of data can enable more efficient algorithms for search and analysis. We are also interested in computational topology, and approaches for making topological data analysis tractable on large data sets.<\/p><\/div><\/div> Our research interests are centered on big data and applied AI with a focus on smart cities and smart health related applications. Our work has been recognized by a number of research awards and our research is sponsored by funds from NSF, TIDC, and USDA.<\/p><\/div><\/div> The Human-Centered Experiential Technologies (HAX) lab follows a user-centered design process to create and maintain public research systems to augment human information interactions. We are human-computer interaction system researchers applying methods from social computing and human-centered AI in the wild.<\/p><\/div><\/div> We study how ML works for science, technology, and society. This means we apply data science using ML models to understand the world with other scientists, study and evaluate those ML systems directly and build tools to help them intervene.\u00a0 Most of our work right now focuses on building more fair AI and some includes collaboration with other scientists.<\/p><\/div><\/div> The lab\u2019s current and past research are in the broad area of Machine Learning, with particular emphasis on graph-structured data. The lab\u2019s work has been applied to challenging problems arising in a variety of domains, including computer program optimization and analysis, computer vision, and computational biology.<\/p><\/div><\/div> A group that creates, applies, and improves new techniques for the analysis of data including, algorithmic and statistical techniques, as well as newly merged computational and statistical techniques.<\/p><\/div><\/div> Cryptology, the science of coding and decoding secret messages, is divided into cryptography, which concerns designing cryptosystems, and cryptanalysis, which is concerned with breaking cryptosystems. Our research has resulted in the creation of an educational website and a Maple\u00ae package for cryptography.<\/p><\/div><\/div> A special interest group of faculty, staff, and students, involved in the research, development, teaching, and cross-disciplinary utilization of 3-dimensional modeling, animation, and interactivity. We offer courses coordinated between the Art and Computer Science Departments. Our research projects are defined by interdisciplinary collaboration.<\/p><\/div><\/div> The NCIPHER team is applying the tools of causal inference and network science to address some of the most pressing public health and educational challenges, such as harm reduction measures among people who use drugs, increasing pre-exposure prophylaxis uptake among men who have sex with men, and improving learning in statistics education. We recognize in these contexts that shared influence between patients, students, and participants must be considered when evaluating interventions with possible dissemination.<\/p><\/div><\/div> Our faculty work on substantial research projects with undergraduate students. The undergraduate research page provides a samples student projects. As part of CSC477, many students collaborate on internships through IACR<\/a> with research efforts across diverse disciplines on campus.<\/p>\n\n\nundergraduate research<\/a><\/div>\n\n\n\n![\"Algorithms](\"https:\/\/web.uri.edu\/cs\/wp-content\/uploads\/sites\/1531\/abd_wht2024_sw_hifi_edit.jpg\")
<\/div>URI Algorithms for Big Data Research Group<\/h2>
AI Lab<\/h2>
![\"HAX](\"https:\/\/web.uri.edu\/cs\/wp-content\/uploads\/sites\/1531\/logo-2.jpg\"){kind=logo}
<\/div>HAX Lab<\/h2>
ml4sts Lab<\/h2>
Alvarez Lab<\/h2>
Computational Statistics and Machine Learning<\/h2>
Cryptography<\/h2>
Interactive 3D Graphics Partnership<\/h2>
NCIPHER Lab<\/h2>
\n\n\n\nUndergraduate Research<\/h2>\n\n\n\n