Ya-Wei Eileen Lin

Ya-Wei Eileen Lin

I am a PhD student in the Electrical and Computer Engineering Faculty at the Technion , supervised by Prof. Ronen Talmon.

My research interests are geometric learning, optimal transport, Riemannian geometry, and graph neural networks.

Email / CV / Google Scholar / LinkedIn / Github

News

[02/2024] I received the Schmidt Postdoc Award for Women in Mathematical and Computing Sciences

[12/2023] Our Hyperbolic Diffusion Procrustes Analysis for Intrinsic Representation of Hierarchical Data Sets paper was accepted to ICASSP 2024

[09/2023] I gave a talk on my recent research Hyperbolic Diffusion Embedding and Distance for Hierarchical Representation Learning in the Department of Mathematics and Institute of Applied Mathematical Sciences at National Taiwan University

[06/2023] I presented my recent research Hyperbolic Diffusion Embedding and Distance for Hierarchical Representation Learning in the Modern Applied and Computational Analysis workshop

[04/2023] Our Hyperbolic Diffusion Embedding and Distance for Hierarchical Representation Learning paper was accepted to ICML 2023

Publications

	Hyperbolic Diffusion Procrustes Analysis for Intrinsic Representation of Hierarchical Data Sets Ya-Wei Eileen Lin, Yuval Kluger, Ronen Talmon ICASSP, 2024
	Spatial Analysis Reveals Impaired Immune Cell Function within the Tumor Microenvironment of HIV-associated Non-small Cell Lung Cancer Shruti Desai, Syim Salahuddin, Ramsey Yusuf, Kishu Ranjan, Jianlei Gu, Ya-Wei Eileen Lin, Ronen Talmon, Yuval Kluger, Hongyu Zhao, Kurt Schalper, Brinda Emu medRxiv, 2023
	Hyperbolic Diffusion Embedding and Distance for Hierarchical Representation Learning Ya-Wei Eileen Lin, Ronald R. Coifman, Gal Mishne, Ronen Talmon ICML, 2023
	Hyperbolic Procrustes Analysis Using Riemannian Geometry Ya-Wei Eileen Lin, Yuval Kluger, Ronen Talmon NeurIPS, 2021
	Graph of graphs analysis for multiplexed data with application to imaging mass cytometry Ya-Wei Eileen Lin, Tal Shnitzer, Ronen Talmon, Franz Villarroel-Espindola, Shruti Desai, Kurt Schalper, Yuval Kluger PLoS computational biology, 2021

Divers

I'm invited as a reviewer of JMLR, ICML, and ECCV.

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