I am a first-year Ph.D. student at Cornell University. Before joining Cornell, I completed my M.Sc. in Computer Science at the University of British Columbia, where I had been very fortunate to be advised by Prof. Margo Seltzer. Before that, I received my B.Sc. in Computer Engineering with a minor in Mathematics at the Sharif University of Technology. My research interests generally lie in the areas of network science, graph representation learning, ML in healthcare, and computational neuroscience.

I am always open to collaboration!


Selected Publications


NeurIPS 2023CAT-Walk: Inductive Hypergraph Learning via Set Walks.
Ali Behrouz, Farnoosh Hashemi, Sadaf Sadeghian, Margo Seltzer
PDF GitHub Repository
ICML IMLH Workshop 2023ADMIRE++: Explainable Anomaly Detection in the Human Brain via Inductive Learning on Temporal Multiplex Networks. PDF Best Paper Award
Ali Behrouz, Margo Seltzer
PDF GitHub Repository
CIKM 2022CS-MLGCN: Multiplex Graph Convolutional Networks for Community Search in Multiplex Networks. PDF Best Paper Honorable Mention Award
Ali Behrouz, Farnoosh Hashemi
PDF
NeurIPS TGL Workshop 2022Anomaly Detection in Multiplex Dynamic Networks: from Blockchain Security to Brain Disease Prediction. PDF Best Paper Award Candidate
Ali Behrouz, Margo Seltzer
PDF GitHub Repository
WWW 2022FirmCore Decomposition of Multilayer Networks. PDF Selected For Oral Presentation
Farnoosh Hashemi*, Ali Behrouz*, Laks V.S. Lakshmanan
PDF GitHub Repository


News


Sep 2023Our paper "CAT-Walk: Inductive Hypergraph Learning via Set Walks" has been accepted to NeurIPS 2023.
Sep 2023Our paper "Generalized Densest Subgraph in Multiplex Networks" has been accepted to the Conference on Complex Networks 2023.
Aug 2023I completed my M.Sc. with the thesis "Anomaly Detection in Multiplex Networks: from Human Brain Activity to Financial Networks". Next, I will start my Ph.D. at Cornell University.
July 2023Our paper "ADMIRE++: Explainable Anomaly Detection in the Human Brain via Inductive Learning on Temporal Multiplex Networks" won the best paper award in the ICML IMLH workshop.
June 2023Our paper "Anomaly Detection in the Human Brain via Inductive Learning on Temporal Multiplex Networks" has been accepted to the Machine Learning for Healthcare Conference, MLHC 2023.


Service


Conference/Workshop Reviewer: ICLR 2023, NeurIPS 2023, NeurIPS TGL Workshop 2023, KDD 2022.

Journal Reviewer: TMLR 2023.

Other: Mentor in Talaria Summer Institute.


Collaboration with Master/Bachelor Students! I would be happy to collaborate with Master/Bachelor students who would like to work on graph learning, ML in healthcare, and/or network science. I also have some projects in these areas that we can discuss.