Group News

Undergraduate advisees Aditya Goyal, Helena Huang, and Joseph Zarling presenting at the 2025 Undergraduate Symposium on Friday, April 25, 2025: https://docs.google.com/spreadsheets/d/1ar5FSPxhS8y5QB1ZtITYrERUZvZp1mnJ0jda2SaQsQU/edit?gid=973963874#gid=973963874 https://ugradsymposium.wisc.edu/wp-content/uploads/sites/454/2025/04/2025-Undergraduate-Symposium-Abstract-Book.pdf GENERATING PYTHON SCRIPTS TO GAIN INSIGHTS INTO HOW NN LEARNS (Aditya Goyal) TOPOGRAPHNET: ENHANCING GRAPH LEARNING IN COSMOLOGY WITH PERSISTENT HOMOLOGY (Helena Huang) Computer, Data, and Information Sciences (Joseph Zarling)

New paper by Puxin Lin, Alessandro Mininno, and Gary Shiu on “Formulating the Weak Gravity Conjecture in AdS Space” posted on the arXiv: https://arxiv.org/abs/2503.05862.

Puxin Lin gave his first talk at the Worldline Seminars: https://sites.google.com/view/worldlineseminars/ based on his paper: https://arxiv.org/abs/2409.02197. Recording of the talk: https://plymouth.cloud.panopto.eu/Panopto/Pages/Viewer.aspx?id=4849ebb8-8123-4f3e-8299-b24201067a0c

Congratulations to Jacky Yip on passing the prelim exam. The title of his presentation is “Topological Data Analysis for Cosmology”: https://www.physics.wisc.edu/events/?id=9005

URS students in Shiu’s group presented at the Undergraduate Research Symposium on April 25, 2024: Manu Korupolu: “Topological Data Analysis and its Applications to Physics” Rachelle Lang: “Towards Quantiative Topological Statements about Neural Networks” Keiji Toriumi: “Using Topological Neural Networks for Cosmology”

Puxin Lin presented his work on black holes at the UW Physics Student Research Colloquium 2024: UW Physics Student Research Colloquium 2024

Congratulations to Jacky Yip for winning the 2023 Alan & Arline Paul Award! The list of 2023 Award Winners can be found here: https://www.physics.wisc.edu/department/awards/2022-23-scholarship-and-awards/

Our paper on “Learning from Topology: Cosmological Parameter Estimation from the Large-scale Structure” was accepted after peer-review at the 1st workshop on Synergy of Scientific and Machine Learning Modeling, ICML, Honolulu, Hawaii, USA. July, 2023: https://syns-ml.github.io/2023/contributions/ The arXiv version can be found here: https://arxiv.org/abs/2308.02636