Welcome to the OpAL Lab

The Optimization, Analytics and Learning (OpAL) Lab is a research group at the Cheriton School of Computer Science. Our work is focused on machine learning on graphs, which is about making predictions using multi-modal datasets that combine features and relational information among entities. Our work involves stronger control on optimization formulations and algorithms, as well as their parallel and communication efficient implementations. We are equally interested in theory and in practice.

We are located at the University of Waterloo, a vibrant technological hub with Concept, Velocity and Google around the block. We are also part of the Scientific Computation Group.

We are looking for passionate new PhD students, Postdocs, and Master students to join the team (more info) !

We are grateful for funding from the University of Waterloo and NSERC


14 October 2020

Aseem Baranwal has been nominated by the CS department for the PhD Google Fellowship.

28 September 2021

Our paper Local Hyper-flow Diffusion was accepted at NeurIPS 2021.

13 August 2021

Our paper Targeted Pandemic Containment Through Identifying Local Contact Network Bottlenecks was accepted at PLOS Computational Biology.

22 July 2021

Shenghao was a finalist for the best student presentation prize at SIAM ACDA. His talk was on Local Hyper-flow Diffusion. You can find the video here.

26 June 2021

Shenghao will present his work on Local Hyper-flow Diffusion at SIAM ACDA.

31 May 2021

Shenghao Yang is one of the 10 fellows to the Borealis AI Global Fellowship.

16 May 2021

Our paper Graph Convolution for Semi-Supervised Classification: Improved Linear Separability and Out-of-Distribution Generalization was accepted at ICML 21.

23 February 2021

Our paper Statistical guarantees for local graph clustering was accepted at JMLR.

17 February 2021

New paper: Local Hyper-flow Diffusion.

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