Focuses on researching advanced topics in classical and quantum information systems and networks, and secure communications

Researches and develops innovative sensors, informatics methods, and systems toward personalized health care.

Researches and develops technologies that reinforce learning. 

Conducts research in all aspects of networked systems, including Internet protocols, peer-to-peer systems, wireless and mobile networks.

Seeks to improve the performance of computer systems through the synergistic enhancement of the compiler, run-time environment, and architecture

Focuses on both machine and biological learning including reinforcement learning, safe machine learning, and biologically inspired machine learning.

Does research in robotics to continually make robots more autonomous, accurate, robust, and efficient, in real-world unstructured environments.

Aims to apply techniques developed in computer science to problems in biology and neuroscience

Conducts research on information retrieval, machine learning, and natural language processing with a focus on biomedical applications.

Focuses on modeling of the real world, and simulation of physically based illumination phenomena.

Investigating the scientific principles underlying the construction of integrated vision systems and the application of vision to real-world problems. 

Supports the creation and use of systems that incorporate components from different sources

Supporting teacher-led, dyadic design teams to engage in collaborative design-based implementation research.

Focuses on building systems for efficiently and securely managing data.

Advances digital forensics science and technology, addressing the challenge of the protean nature of computer systems and the Internet

Aims to make robots that are practical tools for human life by advancing the systems faster, smarter, and robustly.

Revolutionizing the way we observe, detect, and predict atmospheric phenomena by creating distributed collaborative adaptive sensor networks.

Conducts fundamental and applied research at the intersection of HCI and visualization

Dedicated to cutting-edge research on lifelong collaborative autonomy, with the goal of enabling robots to operate and adapt over long periods of time.

Aims to dramatically increase our ability to mine actionable knowledge from unstructured text

Working on machine learning for multimodal data, including methods that support a wide range of biomedical applications.

Studies how to construct causal models of complex systems, a fundamental research challenge at the frontier of machine learning

Investigates techniques for reducing software development and maintenance costs while simultaneously improving the quality of the systems produced.

Investigates systems issues for distributed systems ranging from large server clusters to networks of small sensors

Studies foundational principles that enable Internet-based services to be reliable, scalable, secure, high-performance, energy-efficient, and low-cost.

Investigates planning and control methodologies for complex, multi-objective robotic systems,

Focuses on rigidity, flexibility, and motion for constrained structures like linkages or frameworks in mechanics or robotics.

Research spans a diverse range of topics, including computational social science, information extraction, neural language modeling, and representation learning.

Focuses on cooperative system support for robust and high-performing computing in the context of modern programming languages. 

Investigates how to most effectively use learning technologies to deliver lectures and course materials inside--and outside of--the classroom.

Studies the construction of intelligent systems that can operate in real-time environments under uncertainty and limited computational resources.

Analyzes security and privacy provided by existing network protocols, tools, and services; proposes design adjustments to regain users' security and privacy.

Conducts research on a variety of systems, networking, and data management issues in data-centric sensor networks.

Aims to build and apply computational methods to understand genetic variation.

Develops natural language processing and machine learning methods to help scientific investigation about political and social trends.

Investigates topics centered around carbon-intelligent computing (application) and data-driven online optimization (theory).

Uses mathematical techniques to study problems throughout computer science, focusing on network algorithms, coding theory, and combinatorial optimization.

Focuses on developing new algorithms and techniques in computer graphics and visual computing. 

Research interests and topics include: Internet of Medical Things, Internet of Living Things, Wireless Communication, Quantum Computing