Edward Cheung, PhD candidate
David R. Cheriton School of Computer Science
Rafael Olaechea Velazco, PhD candidate
David R. Cheriton School of Computer Science
Software behavioural models, such as finite state machines, are used as an input to model checking tools to verify that software satisfies its requirements. As constructing such models by hand is time-consuming and error-prone, researchers have developed tools to automatically extract such models from systems’ execution traces.
Chunhao Wang, PhD candidate
David R. Cheriton School of Computer Science
We present a quantum algorithm for simulating the dynamics of Hamiltonians that are not necessarily sparse. Our algorithm is based on the assumption that the entries of the Hamiltonian are stored in a data structure that allows for the efficient preparation of states that encode the rows of the Hamiltonian. We use a linear combination of quantum walks to achieve a poly-logarithmic dependence on the precision.
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.
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.
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.
Anastasia Kuzminykh, PhD candidate
David R. Cheriton School of Computer Science
While technologies exist that are either marketed for or can be adapted to the monitoring of toddlers and school-age children, parents' perspectives on these technologies have received only limited attention.
Jeff Avery, PhD candidate
David R. Cheriton School of Computer Science
Despite the ubiquity of touch-based input and the availability of increasingly computationally powerful touchscreen devices, there has been comparatively little work on enhancing basic canonical gestures such as swipe-to-pan and pinch-to-zoom.