Kristofer Siy, Graduate student
Combinatorics and Optimization
Ankit Vadehra, Master’s candidate
David R. Cheriton School of Computer Science
Yaron Minsky, Technology Group Head
Jane Street
Trading in financial markets is a data-driven affair, and as such, it requires applications that can efficiently filter, transform and present data to users in real time.
But there's a difficult problem at the heart of building such applications: finding a way of expressing the necessary transformations of the data in a way that is simultaneously easy to understand and efficient to execute over large streams of data.
Woojung Kim, Master’s candidate
David R. Cheriton School of Computer Science
Yaron Minsky, Technology Group Head
Jane Street
Electronic exchanges play an important role in the world’s financial system, acting as focal points where actors from across the world meet to trade with each other.
But building an exchange is a difficult technical challenge, requiring high transaction rates, low, deterministic response times, and serious reliability.
Mohammad Sadoghi
University of California, Davis
Peiyuan Liu, Master’s candidate
David R. Cheriton School of Computer Science
Anna Lubiw
David R. Cheriton School of Computer Science
In this talk I will look at geometric graph representations from the perspective of three issues: the algorithmic complexity of finding a representation; the bit complexity of the representation; and whether there is a morph between any two combinatorially equivalent representations.
Emily Kozlowski
Department of Statistics and Actuarial Science
A flipped classroom moves the traditional lecture component of teaching outside the classroom, so that it can be replaced with active learning during class time.
In this talk, I present a brief overview of flipped classrooms, followed by a discussion of the details of its implementation for two lectures during the Spring 2018 offering of ACTSC 331. Students’ responses to the technique are also provided in the form of data from anonymous post-activity surveys.
The next Waterloo-local ACM-style programming contest will be held on Sunday, September 30 in MC 3003.
All members of the University of Waterloo community are invited to try their programming skill in Racket, C, C++, Java, Pascal, Python, or Scala.
Join us
On Friday, September 28 we will launch the new Cybersecurity and Privacy Institute.
The Institute brings together under one umbrella Waterloo’s 40 security researchers from across the University. These renowned experts are collaborating to uncover new approaches to security and privacy while also partnering with corporations and government to advance the application and implementation of cybersecurity and privacy technologies.
Mohamed Malek Naouach, Master’s candidate
David R. Cheriton School of Computer Science
Adam Molnar, Deakin University
Daniel Recoskie, PhD candidate
David R. Cheriton School of Computer Science
Hamid Tizhoosh, SDE
University of Waterloo
The history of artificial intelligence (AI) contains several ebbs and flows and is marked by many colorful personalities. We review major milestones in the development of machine learning, starting from principal component analysis to deep networks, and point to a multitude of pivotal developments that have strongly contributed to drawing the historical path of AI.
Nicole McNabb, Master’s candidate
David R. Cheriton School of Computer Science
Omar Zia Khan, Senior Applied Scientist
Microsoft
Ahmed Khan, Master’s candidate
David R. Cheriton School of Computer Science
Neurobiologically-plausible learning algorithms for recurrent neural networks that can perform supervised learning are a neglected area of study. Equilibrium propagation is a recent synthesis of several ideas in biological and artificial neural network research that uses a continuous-time, energy-based neural model with a local learning rule. However, despite dealing with recurrent networks, equilibrium propagation has only been applied to discriminative categorization tasks.
The David R. Cheriton School of Computer Science invites you to attend the 2018 Cheriton Research Symposium, held on Friday, September 21, 2018 in the Davis Centre.
Ifaz Kabir, Master’s candidate
David R. Cheriton School of Computer Science
Md Faizul Bari, PhD candidate
David R. Cheriton School of Computer Science
Elaheh Jalalpour, Master’s candidate
David R. Cheriton School of Computer Science
Steven Wang, Master’s candidate
David R. Cheriton School of Computer Science
Pirathayini Srikantha, Department of Electrical and Computer Engineering
Western University
Yossef Musleh, Master’s candidate
David R. Cheriton School of Computer Science
We introduce a Monte Carlo randomized algorithm for computing the characteristic polynomial of a rank 2 Drinfeld module than runs in $O(n^2 \log n \log \log n \log q)$ field operations. We also introduce a deterministic algorithm that runs in $O(n^{2.6258} \log n + n^2 \log n \log log n \log q)$ field operations. Both approaches are a significant improvement over the current literature.
