Explore Systems research areas at Duke Computer Science.
Designing computer systems—from single cores to multicore chips to data centers—that can execute software with high performance and low power consumption is a continuing challenge as software changes and new hardware substrates emerge. Research at Duke includes parallel and distributed systems, special-purpose architectures, machine learning and algorithmic economics for systems, memory systems, architectures for emerging technologies, and fault tolerant and reliable computing.
In computer networks, individual devices (nodes) exchange data over connections (links) established over cable or wireless media. At Duke, research in computer networks focuses on building reliable networks, next generation networking technology, network security, and content delivery networks.
In the world of big data, people are collecting, storing, processing, and analyzing data on a regular basis. At Duke, we use data to solve many real-world problems with an emphasis on problems that impact social good, as well as aim to make this process as simple, efficient, robust, and secure as possible. Research in Duke data science, data management, databases, and systems covers a wide range of topics:
- Data Science, which includes analyzing data in healthcare, criminal justice, fake news, sports data analysis, and other areas. Duke is particularly strong in methodology related to data science, including model interpretability, causal inference, and computer vision.
- (Mis-)Information Management, which includes automated fact checking, computational journalism, uncertain data management and probabilistic databases, data provenance, and explanations for query answers.
- Secure and Private Data Management, which includes differentially private data analysis with applications in areas like census, social networks, location tracking, and search logs.
- Data Processing, which includes query optimization, use of sampling and machine learning methods, and debugging and interactive exploration of query answers.
In distributed systems, networked computers exchange data and control information by message passing to collectively perform computational tasks. At Duke, research in distributed systems has focused on security in distributed environments, network storage, data center design, etc.
High performance computing
High performance computing refers to creating and using systems that aggregate computing power from a large number of computing devices to deliver performance at a level that significantly exceeds the capabilities of any single device. At Duke, research has focused on areas such as cloud infrastructure and biomedical applications.
Operating systems is a collective name for system software that manages computer resources and provides a set of common services to individual programs. Operating systems research at Duke has focused on areas such as management of cloud resources.
The concept of utilizing quantum resources for computational tasks has opened up a new area of intellectual and practical frontier in computing, ranging from computational complexities, quantum algorithms, quantum computing architectures to construction of commercially viable quantum computers. Duke has been a pioneer in this exciting frontier of a fast-developing field, in quantum error correction, quantum computer architectures and trapped-ion quantum computing hardware development. The research opportunities at Duke are on a rapid growth path, and we will form an epicenter of research and development effort for practical realization of quantum computers.
Security and privacy
In this era of big data, the privacy of individuals and security of computing systems that handle sensitive data has come to be a central challenge in computer science. At Duke, research in this area has focused on four broad directions:
- Differentially Private Data Science, where researchers at Duke have made fundamental contributions to the theory, algorithms, programming frameworks and systems, and social implications of differential privacy.
- Privacy in Mobile Systems, where the focus at Duke is to study novel architectures for enabling privacy in mobile and smart devices as well as privacy enhancing techniques for sharing sensor data (e.g., camera and location) with potentially malicious applications.
- Oblivious and Secure Computation, where at Duke the goal is to advance the theory and application of cryptographic primitives with the aim of building efficient and practical systems for specific problem domains like graph computation and differentially private analytics.
- Blockchains, where Duke researchers are making foundational contributions to the field of distributed consensus to scale blockchains in a way that achieves robustness without sacrificing low latency and high throughput.