Current students

N. Asokan, Department of Computer Science
Aalto University, Finland

All kinds of previously local services are being moved to cloud settings. While this is justified by the scalability and efficiency benefits of cloud-based services, it also raises new security and privacy challenges. Solving them by naive application of standard security/privacy techniques can conflict with other functional requirements. In this talk, I will outline some cloud-assisted services and the conflicts that arise while trying to secure these services.

Thomas Lidbetter, Master candidate
David R. Cheriton School of Computer Science

In this talk we consider two mostly disjoint topics in formal language theory that both involve the study and use of regular languages. The first topic lies in the intersection of automata theory and additive number theory. 

Verena Kantere
School of Electrical Engineering and Computer Science, University of Ottawa

Big Data analytics in science and industry are performed on a range of heterogeneous data stores, both traditional and modern, and on a diversity of query engines. Workflows are difficult to design and implement since they span a variety of systems. To reduce development time and processing costs, some automation is needed.

Panos K. Chrysanthis
Department of Computer Science, University of Pittsburgh

Li Liu, PhD candidate
David R. Cheriton School of Computer Science

Entanglement is a type of resource used in quantum information theory that gives correlations that cannot be simulated using classical probability theory. It is known that entanglement cannot be created locally. 

Andreas Stöckel, PhD candidate
David R. Cheriton School of Computer Science

The artificial neurons typically employed in machine learning and computational neuroscience bear little resemblance to biological neurons. They are often derived from the “leaky integrate and fire” (LIF) model, neglect spatial extent, and assume a linear combination of input variables. It is well known that these simplifications have a profound impact on the family of functions that can be computed in a single-layer neural network. 

Ahmed Alquraan, Master’s candidate
David R. Cheriton School of Computer Science

We present a comprehensive study of 136 system failures attributed to network-partitioning faults from 25 widely used distributed systems. We found that the majority of the failures led to catastrophic effects, such as data loss, reappearance of deleted data, broken locks, and system crashes. 

Nick Rollick, Graduate student
Department of Pure Mathematics

For this week's seminar, I invite you to join me for an informal chat about my experiences using "reflective responses" in my elementary number theory course. In these bi-weekly formal reflective assignments, my students were asked to set and monitor learning goals, identify gaps in understanding, and ponder the value and importance of their course material. Most importantly, I responded in detail to every student's reflection, creating a meaningful course-long conversation.

Jaemyung Kim, PhD candidate
David R. Cheriton School of Computer Science

Transaction durability guarantees the ability to recover committed transactions from failures. However, making every transaction durable impacts transaction processing performance. Some ad-hoc durability mechanisms (e.g., delayed durability) improve performance, but they risk transactions losing their effects due to failures. The current one-size-fits-all transaction durability model does not solve this problem.