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Events

Monday, April 30, 2018 — 1:30 PM EDT

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

Monday, April 30, 2018 — 10:00 AM EDT

Bahareh Sarrafzadeh, PhD candidate
David R. Cheriton School of Computer Science

Friday, April 27, 2018 — 1:30 PM EDT

Milan Jain, PhD Scholar in Computer Science
Indraprastha Institute of Information Technology Delhi

Friday, April 27, 2018 — 11:30 AM EDT

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. 

Friday, April 27, 2018 — 9:30 AM EDT

Lisa Elkin, Master’s candidate
David R. Cheriton School of Computer Science

Thursday, April 26, 2018 — 10:30 AM EDT

Rachel Pottinger, Department of Computer Science
University of British Columbia

Users are faced with an increasing onslaught of data, whether it's in their choices of movies to watch, assimilating data from multiple sources, or finding information relevant to their lives on open data registries. In this talk I discuss some of the recent and ongoing work about how to improve understanding and exploration of such data, particularly by users with little database background.

Thursday, April 26, 2018 — 10:00 AM EDT

Amir-Hossein Karimi, Master’s candidate
David R. Cheriton School of Computer Science

Tuesday, April 24, 2018 — 2:00 PM EDT

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. 

Tuesday, April 24, 2018 — 1:00 PM EDT

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.

Monday, April 23, 2018 — 1:00 PM EDT

Weicong Ma, Master’s candidate
David R. Cheriton School of Computer Science

Monday, April 23, 2018 — 10:30 AM EDT

Barzan Mozafari, Department of Computer Science and Engineering
University of Michigan

Friday, April 20, 2018 — 10:30 AM EDT

Lei Zou, Institute of Computer Science and Technology
Peking University

Friday, April 20, 2018 — 9:30 AM EDT

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

Thursday, April 19, 2018 — 2:30 PM EDT

Joel Reardon, Assistant Professor
Department of Computer Science, University of Calgary

Wednesday, April 18, 2018 — 11:00 AM EDT

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. 

Wednesday, April 18, 2018 — 10:00 AM EDT

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. 

Wednesday, April 18, 2018 — 9:00 AM EDT

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

Tuesday, April 17, 2018 — 10:30 AM EDT

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.

Monday, April 16, 2018 — 10:00 AM EDT

Hicham El-Zein, PhD candidate
David R. Cheriton School of Computer Science

Thursday, April 12, 2018 — 4:00 PM to 6:00 PM EDT

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.  

Thursday, April 12, 2018 — 10:30 AM EDT

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.

Wednesday, April 11, 2018 — 1:30 PM EDT

Aayush Rajasekaran, Master's candidate
David R. Cheriton School of Computer Science

Monday, April 9, 2018 — 1:00 PM EDT

William Callaghan, Master’s candidate
David R. Cheriton School of Computer Science

Monday, April 9, 2018 — 1:00 PM EDT

Ahmed El-Roby, PhD candidate
David R. Cheriton School of Computer Science

Today, there is an abundance of structured data available on the web in the form of RDF graphs and relational (i.e., tabular) data. This data comes from heterogeneous sources, and realizing its full value requires integrating these sources so that they can be queried together. Due to the scale and heterogeneity of the data sources on the web, integrating them is typically an automatic process.

Monday, April 9, 2018 — 10:30 AM EDT

Thomas Steinke, Postdoctoral researcher
IBM Almaden Research Center

As data is being more widely collected and used, privacy and statistical validity are becoming increasingly difficult to protect. Sound solutions are needed, as ad hoc approaches have resulted in several high-profile failures.

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