PhD Candidate in Computer Science
Developing the theory and system of scalable streaming systems for computer vision applications.
This course is about problem solving and computation via algorithms. We will cover a number of known algorithms (sorting, hashing, search, indexing) and their applications. We will discuss methods for analyzing existing algorithms and designing new algorithms. Finally, the students will be introduced to complexity classes, in particular the class of NP-completeness.
The topic of this course is the theory and practice of programming languages. We will be focused on the design principles and programming patterns of several programming languages from different programming paradigms. We will pay particular attention to the program techniques in functional programming, and why they are gaining greater importance in modern programming.
Open Data is the hottest addition to the Web. Back by various nations and governments, millions of open data sets are being released by authoritative sources. This is a vastly valuable opportunity for data scientists to gain greater insights into a multitude of social and economic issues.
In collaboration with Toronto, we are building an Internet scale data integration system specifically designed for finding linkages in Open Data.
If computers can play Go brilliantly, why can’t we use our mobile phones to solve general puzzles?
The reason is that we don’t have a great algebra (and an interface) to enable user access to the powerful constraint solvers. This project is to investigate the design and feasibility of such constraint solving interfaces (either as an application, or a special purpose programming language).