Operating Systems and Distributed Systems

Faculty active in the research areas of Operating Systems and Distributed Systems in the Computer Science Department investigate algorithms, design principles, and engineering techniques for developing the software necessary to run modern computer systems. Operating systems research focuses on system software targeting a single machine or physical computational device while distributed systems efforts study the use of multiple computers interconnected by a network to implement coherent, secure, scalable, and reliable systems. Current research foci include cloud computing, distributed database and "Big Data," operating system virtualization, programming languages and runtime environments for distributed systems, machine learning and statistical techniques for large-scale analytics, social networks, and data-center management systems. Researchers in these areas employ collaborative and multi-technological approaches often combining skills and research results from multiple disciplines in a team setting. Together, faculty and students develop solutions to complex problems that lead to a transformative impact on an increasingly information-centric and data-dependent society.

Affilated Labs: 
Distributed Systems Lab, RACELab, SAND Lab


Distributed Systems and Databases, Cloud Computing, Big Data, Social Network and Social Media Data Analytics.

He has investigated multi-processor scheduling, systolic arrays, and the relationship between algorithms and architectures for parallel processing.  Via Javelin, CX, and, the JICOS project, he is investigating distributed cloud computing. 

Big Data, Cloud Computing, Social Networks, Fault-tolerant Distributed Systems and Data Management at scale.

My research interests are in the area of computer systems, in particular, in building systems that provide strong security and privacy properties to users. An example system that I built hides the knowledge of a person's media diet from a Netflix-like media delivery service. Another example system that I built hides user emails from the email service provider while allowing the provider to run important functions (such as spam filtering) over email.

My research interests include programming support and adaptive optimization for cloud computing applications and systems, and the intersection of IoT, data analytics and machine learning, and cloud. Recently, my focus has been on using these technologies to faciliate sustainability science and engineering for the domains of agriculture (SmartFarm) and ecology (WTB). My other interests include projects that mentor, support, and encourage young people from underrepresented groups (especially women!) to consider and pursue computer science.

Much of Professor Singh’s research is around data-centric modeling of systems and he focuses on the development of new methods that can be applied to real-world applications.

The goal of my research is to explore ways in which the ubiquitous proliferation of high-performance network connectivity can be used to foster new distributed computing capabilities and systems. 

His recent research is in the fields  of web data mining and search, and cloud systems. His past research includes search engines, scalable web services and middleware, scheduling and runtime support for parallel irregular computation, and parallel sparse matrix algorithms.