I am a fourth year Ph.D. student in the David R. Cheriton School of Computer Science at University of Waterloo, advised by Kimon Fountoulakis. I work on machine learning and optimization problems on graphs. Previously, I obtained a Master of Mathematics in the Department of Combinatorics & Optimization, where I worked with Ricardo Fukasawa and Laurent Poirrier.
01.16.2024. Our paper Local Graph Clustering with Noisy Labels was accepted to ICLR 2024.
12.26.2023. I started an applied scientist internship at Amazon again!
05.29.2023. Our paper Graph Attention Retrospective was accepted to JMLR. We theoretically study the advantages and limitations of graph attentional convolution for node classification in a contextual stochastic block model.
04.24.2023. Our paper Weighted Flow Diffusion for Local Graph Clustering with Node Attributes: an Algorithm and Statistical Guarantees was accepted for an oral presentation at ICML 2023!
07.05.2022. I started an applied scientist internship at Amazon in the Supply Chain Optimization Technologies group!
05.03.2022. I got Canada Graduate Scholarship. Thanks NSERC!
04.29.2022. Our paper Graph Attention Retrospective won the Best Paper Award at the GroundedML workshop.
03.14.2022. I gave a talk at INFORMS Optimization Society Conference (IOS 2022). Slides
02.18.2022. I was awarded a Cheriton Scholarship from the Cheriton School of Computer Science.
10.04.2021. A short feature story about me on the Faulty of Mathematics’ website.
09.28.2021. Our paper Local Hyper-Flow Diffusion was accepted to NeurIPS 2021. Many thanks to my wonderful mentors!
07.22.2021. My presentation on Hyper-Flow Diffusion was a finalist for the Best Student Presentation Price at SIAM ACDA21.
07.19.2021. I gave a talk at SIAM Conference on Applied and Computational Discrete Algorithms (SIAM ACDA21). Slides
05.31.2021. I was one of ten recipients to receive a Borealis AI 2021 Fellowship. Thank you Borealis AI!
05.17.2021. I gave a talk at SIAM Conference on Applied Linear Algebra (SIAM LA21), Minisymposium on Nonlinear Laplacians on Graphs and Manifolds with Applications to Data and Image Processing. Slides
05.03.2021. I started a research internship at Borealis AI in the Derivative Pricing Team.
09.23.2020. I gave a talk at Network Science Society Conference (NetSci 2020). Slides
07.07.2020. I gave a talk at SIAM Workshop on Network Science (SIAM NS20). Slides
06.22.2020. I gave a talk at SIAM Conference on Mathematics of Data Science (SIAM MDS20), Minisymposium on The Multiple Perspectives on Graph-Based Machine Learning. Slides
Local Graph Clustering with Noisy Labels
Artur Back de Luca, Kimon Fountoulakis, Shenghao Yang
International Conference on Learning Representations (ICLR) 2024
Weighted Flow Diffusion for Local Graph Clustering with Node Attributes: an Algorithm and Statistical Guarantees
Shenghao Yang, Kimon Fountoulakis
International Conference on Machine Learning (ICML) 2023
Graph Attention Retrospective
Kimon Fountoulakis*, Amit Levi*, Shenghao Yang*, Aseem Baranwal, Aukosh Jagannath
Journal of Machine Learning Research (JMLR) 2023
ICLR 2022 Workshop on Anchoring Machine Learning in Classical Algorithmic Theory. Best Paper Award.
Equivariant Hypergraph Diffusion Neural Operators
Peihao Wang, Shenghao Yang, Yunyu Liu, Zhangyang Wang, Pan Li
International Conference on Learning Representations (ICLR) 2023
On Classification Thresholds for Graph Attention with Edge Features
Kimon Fountoulakis, Dake He, Silvio Lattanzi, Bryan Perozzi, Anton Tsitsulin, Shenghao Yang
Local Hyper-Flow Diffusion
Kimon Fountoulakis, Pan Li, Shenghao Yang
Neural Information Processing Systems (NeurIPS) 2021
Targeted Pandemic Containment Through Identifying Local Contact Network Bottlenecks
Shenghao Yang, Priyabrata Senapati, Di Wang, Chris T. Bauch, Kimon Fountoulakis
PLOS Computational Biology. 2021
Parallel and Communication Avoiding Least Angle Regression
Swapnil Das, James Demmel, Kimon Fountoulakis, Laura Grigori, Michael W. Mahoney, Shenghao Yang
SIAM Journal on Scientific Computing. 2021
p-Norm Flow Diffusion for Local Graph Clustering
Kimon Fountoulakis, Di Wang, Shenghao Yang
International Conference on Machine Learning (ICML) 2020
Split Cuts from Sparse Disjunctions
Ricardo Fukasawa, Laurent Poirrier, Shenghao Yang
Mathematical Programming Computation. 2020