Computer Science

Research Laboratories

Financial Engineering Research Laboratory

Financial engineering is a multidisciplinary field that involves different financial aspects such as financial theory, the methods of financing, mathematical tools, computation and the practice of programming to achieve the desired end results. The financial engineering methodologies apply engineering methodologies, social theories and quantitative methods to finance. It is normally used in the stock market, securities, banking, and financial management and consulting industries, or as quantitative analysts in corporate treasury and finance departments of general manufacturing and service firms. Financial Engineering Research Lab is basically concerned and working on three different approaches to forecast stock market.


Distributed Computing Laboratory

The Distributed Computing Laboratory focuses on different aspects of distributed systems. These include Cloud Computing, Distributed Security, Distributed Databases and Distributed Sensor Networks. Other research areas being investigated include applications that require distributed processing, for example big data.


Robotic Cognition Laboratory

The Robotic Cognition Laboratory is devoted to two overarching, complementary goals: to ground models of developmental psychology and cognitive science in realized, embodied computational systems; and to use models of human cognition and social development to improve robot control and learning, human-robot interaction and artificial intelligence.

Learning from negotiation. Traditional learning from demonstration develops policies which can never be better than those demonstrated by human teachers. However, humans are not especially good at describing or implementing optimal behaviors. Demonstrations can bootstrap computational searches of policy spaces, while ongoing human interaction refines and directs the search process.

Shared autonomy. Humans and robots should be able to work together in flexible teams at varying levels of autonomy and interaction. We are developing a coordination framework for human-robot teams which will allow humans to supply direction and decisionmaking at whatever level of detail is possible and appropriate. Robots can act autonomously when there are insufficient human decisionmaking resources available, and will cooperate with one another to share information and reasonable courses of action.