Email: irene [dot] wang [at] gatech [dot] edu
Hi, I’m Irene!
I am a third-year Ph.D. student at Georgia Tech, advised by Prof. Divya Mahajan. My current research interests broadly lie in Systems for Machine Learning and Computer Architecture, with a focus on optimizing distributed deep learning infrastructure.
I received my bachelor’s degree in Computer Engineering from the University of British Columbia, where I worked with Prof. Prashant Nair.
When I’m not in the lab, I enjoy traveling, exploring local restaurants, learning foreign languages, and keeping up with the latest happenings in football.
Feel free to reach out if you would like to chat!
News
[Sept 2025] Our paper CATransformers has been accepted to NeurIPS 2025.
[Aug 2025] I was awarded the Georgia Tech CRNCH Fellowship for Fall 2025!
[July 2025] uArch 2025@ISCA was a success! Catch my ACM SIGARCH Recap of it.
[Mar 2025] I was selected as part of the MLCommons ML and Systems Rising Stars 2025 Cohort!
[Nov 2024] The first-ever edition of the uArch workshop@MICRO is being held in Austin, Texas. I wrote a blog post on ACM SIGARCH about this edition of the uArch workshop!
[Sept 2024] I received the prestigious NSERC Canada Graduate Scholarship – Doctoral (CGS D) award
[Aug 2024] I wrote a blog post on ACM SIGARCH about this year’s uArch workshop at ISCA 2024!
[May 2024] Our paper Integrated Hardware Architecture and Device Placement Search has been accepted to ICML 2024
Recent Publications
CATransformers: Carbon Aware Transformers Through Joint Model-Hardware Optimization
Irene Wang, Mostafa Elhoushi, Ekin Sumbul, Samuel Hsia, Newsha Ardalani, Divya Mahajan, Carole-Jean Wu, Bilge Acun
NeurIPS 2025
Characterizing the Efficiency of Distributed Training: A Power, Performance, and Thermal Perspective
Seokjin Go, Joongun Park, Spandan More, Hanjiang Wu, Irene Wang, Aaron Jezghani, Tushar Krishna, Divya Mahajan
MICRO 2025
Integrated Hardware Architecture and Device Placement Search
Irene Wang, Jakub Tarnawski, Amar Phanishayee, and Divya Mahajan
ICML 2024
FLuID: Mitigating Stragglers in Federated Learning using Invariant Dropout
Irene Wang, Prashant Nair, and Divya Mahajan
NeurIPS 2023
Evaluation of gem5 for Performance Modeling of ARM Cortex-R Based Embedded SoCs
Irene Wang, Prasenjit Chakraborty, Zi Yu Xue, and Yen Fu Lin
Microprocessors and Microsystems. 2022