Future students

Chunhao Wang, PhD candidate
David R. Cheriton School of Computer Science

We give a dissipative quantum search algorithm that is based on a novel dissipative query model. If there are $N$ items and $M$ of them are marked, this algorithm performs a fixed-point quantum search using $O(\sqrt{N/M}\log(1/\epsilon))$ queries with error bounded by $\epsilon$. In addition, we present a continuous-time version of this algorithm in terms of Lindblad evolution.

Magnus Madsen
Aalborg University, Denmark

Most software contains bugs, unintended behavior that causes the program to misbehave or crash. Developers wish to avoid bugs, but are easily led astray by the complexity of modern programming languages. How can we help them? A possible solution is to develop program analysis techniques that can automatically reason about the behavior of programs and pinpoint potential problems.

Dimitrios Skrepetos, PhD candidate
David R. Cheriton School of Computer Science

Lesley Istead, PhD candidate
David R. Cheriton School of Computer Science

Come support fellow colleague, Rina Wehbe (PhD Candidate, Computer Science) as she examines the effects of gamificiation and Games4Change on behaviour and motivation at the upcming GRADtalks event.  

Mohammad Zokaei Ashtiani, PhD candidate
David R. Cheriton School of Computer Science

Rina Wehbe, PhD candidate
David R. Cheriton School of Computer Science

Maryam Mehri Dehvani
Department of Electrical and Computer Engineering, Rutgers University

The emergence of stupendously large matrices in applications such as data mining and large-scale scientific simulations has rendered the classical software frameworks and numerical methods inadequate in many situations. In this talk, I will demonstrate how building domain-specific compilers and reformulating classical mathematical methods significantly improve the performance and scalability of large-scale applications on modern computing platforms.

Zhucheng Tu, Master’s candidate
David R. Cheriton School of Computer Science