Research

Algorithms, Combinatorics, and Graph Theory (ACG) is a laboratory whose goal is to improve the theoretical/practical efficiency of algorithms. We aim at developing new branches of Graph Theory/Combinatorics that can aid in modeling, and effectively solving (exactly or approximately), a wide range of computationally hard problems. For related conferences see Workshop on Algorithms, Combinatorics, and Geometry.

Uncertainty quantification lab develops computational methods for the main aspects of uncertainty quantification, including model correction, parametric uncertainty analysis, non-probabilistic uncertainty modeling, sensitivity analysis, and applies the uncertainty quantification techniques to various disciplines such as biology and engineering.

The Biocomputing Research Group focuses on developing Bioinformatics tools and applying revolutionary technologies to critical scientific and engineering applications related to biology and medical science.

The Biomedical AI Lab develops machine learning tools to predict or precisely measure the outcomes of medical interventions, collaborating extensively with hospitals and medical schools. Although artificial intelligence techniques and clinical populations are highly varied, a major theme is tailored wearable device analytics to assess therapies for individuals with impaired mobility, including past research populations with Parkinson's disease, lower-limb amputations, incomplete spinal cord injury, and cerebral palsy.

The Computer Vision and Intelligent Systems Laboratory (CoVIS) is to advance the understanding of the theories of machine learning for processing complex data and to develop applications in areas such as medicine, geo-information, etc. The research focuses on both algorithm innovation and hardware integration, which includes computer vision, pattern recognition, data mining, and artificial intelligence. The CoVIS lab is facilitated with the state-of-the-art computing resources and various imaging technologies. The lab provides both graduate and undergraduate students a unique, collaborative research cohort to further their career goals.

The Human Intelligence and Language Technologies (HiLT) lab focuses on research on natural language processing (NLP), machine learning (ML), and cognitive science, with an emphasis on Spoken-Dialogue Educational Health & Wellbeing Companion Robots (Companionbots), Educational Technology, Health & Clinical Informatics, and End-User Software Engineering.

The Information Retrieval and Text Mining Lab focuses on developing a variety of general techniques for representing, searching, filtering, organizing, and mining text information, with applications in multiple domains including the Web, homeland security, and biomedical and health informatics. The research draws on methods from information theory, natural language processing, and data mining to tackle problems in information retrieval and discovery, and emphasizes on both fundamental research and system development.

The Multimedia Information Laboratory conducts research on multimedia material (videos and images) processing, multimedia information extraction, and multimedia information modeling and retrieval, which include video and image segmentation, motion and color analysis, image quality analysis, and object recognition by region clustering and classification.

The Computer Systems Research Laboratory focuses its work on researching multithreaded and multicore architectures for both embedded and high-performance applications. Research includes work in processing architectures, memory systems, cache memories and software tools to utilize the special capabilities of underlying hardware systems, and in developing both hardware and software solutions to improve performance, reduce energy consumption and prevent security breaches.

The Dependable Computing Systems Laboratory conducts research on failure modeling, failure management, adaptive failure resilience, failure-aware resource management, and power-aware dependable computing. The lab conducts both fundamental and applied research to develop highly dependable and energy-efficient distributed and cloud computing systems.

The Energy-Efficient High Performance Computing Laboratory focuses on designing computer systems that achieve high performance with limited power budgets. Our research spans across multiple areas of micro architecture design, which includes embedded systems, multi-core processors, memory hierarchies, on-chip interconnections and accelerators.

The Smart Electronic Systems Laboratory (SESL) conducts research in Smart Electronics for the efficient realization of Internet-of-Things (IoT) based components for Smart Cities. The key aspects of the smart electronics are envisioned to be Energy-Smart, Security-Smart, and Response-Smart. Energy-Smart ensures that energy consumption of electronics is minimal for longer battery life. Security-Smart deals with the security/protection of electronics as well as that of the information/media that these systems capture, process, or store. Response-Smart refers to accurate sensing, intelligent processing, and fast actuation/response. Smart Electronics in the framework of IoT can provide 3Is (Instrumentation, Interconnection, and Intelligence) to the Smart Cities. Optimal combinations of hardware and software modules are explored for ESR-smartness of electronic systems.

Wireless Sensor Laboratory (WiSL) was established with the following mission: to increase general wireless communications awareness among computer science and engineering graduates, produce skilled wireless specialists, and conduct research and development activities to advance the state-of-the-art in wireless sensors.

The Network Security Laboratory was established to increase general wireline and wireless network security awareness of computer science and engineering graduates, to produce skilled security specialists, and to conduct research and development activities to advance the state-of-the-art in wireline and wireless network security and communication.

The Laboratory for Recreational Computing (LARC) serves as a center for research, education and development in the field of video game programming.

The Research Innovation in Software Engineering (RISE) laboratory explores advances in software engineering through the areas of compiler design, domain-specific programming languages, human-computer interaction, logic programming, model-driven engineering, and software testing.