Jared Fernandez

Postdoc at Cornell Tech

About

I am a postdoctoral researcher at Cornell Tech with Udit Gupta. My research interests are in characterizing and evaluating the impact of machine learning workloads, with the goal of designing computationally and energy efficient systems for artificial intelligence. My research is generously supported by the Empire AI Postdoctoral Fellowship.

I completed my PhD at Carnegie Mellon University in the Language Technologies Institute where I was advised by Yonatan Bisk and Emma Strubell, and was supported by the NSF Graduate Research Fellowship. Previously, I received my B.S. in Computer Science and B.S. in Electrical Engineering at Northwestern University where I worked with Doug Downey and Thrasos Pappas. I’ve also spent time at Google, Meta FAIR, and the Allen Institute for Artificial Intelligence.

Email: jaredfern [at] cornell.edu

Out-of-Date News:
$\quad$ [Sept. 2026] $\quad$ I defended my PhD Thesis and am starting a postdoc at Cornell Tech!
$\quad$ [July 2026] $\quad$ Our work on Life Cycle Assessments for ML Models will be a position paper at ICML!
$\quad$ [Aug. 2025] $\quad$ Our work on the energy requirements of LLM inference was presented at ACL 2025!
$\quad$ [April 2025] $\quad$ Preliminary work won a Best Proposal Award at the CCAI Workshop at ICLR!

Selected Publications

Practical Evaluation of Machine Learning Efficiency Requires Model Life Cycle Assessment

International Conference on Machine Learning (ICML), 2026.

Jared Fernandez, Clara Na, Yonatan Bisk, Constantine Samaras, Emma Strubell

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Empirically-Calibrated H100 Node Power Models for Reducing Uncertainty in AI Training Energy Estimation

Environmental Research: Energy, 2025.

Alex C Newkirk, Jared Fernandez, Jonathan Koomey, Imran Latif, Emma Strubell, Arman Shehabi, Constantine Samaras

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Energy Considerations of Large Language Model Inference and Efficiency Optimizations

The 63rd Annual Meeting of the Association for Computational Linguistics (ACL), 2025.

Jared Fernandez*, Clara Na*, Vashsisth Tiwari*, Yonatan Bisk, Sasha Luccioni, Emma Strubell

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Efficient Hardware Scaling and Diminishing Returns in Large-Scale Training of Language Models

Transactions on Machine Learning Research, 2025.

Jared Fernandez, Luca Wehrstedt, Leonid Shamis, Mostafa Elhoushi, Kalyan Saladi, Yonatan Bisk, Emma Strubell, Jacob Kahn

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Holistically Evaluating the Environmental Impact of Creating Language Models

The Thirtheenth International Conference on Learning Representations (ICLR), 2025.

Jacob Morrison, Clara Na, Jared Fernandez, Tim Dettmers, Emma Strubell, Jesse Dodge

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The Framework Tax: Disparities Between Inference Efficiency in Research and Deployment

Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023.

Jared Fernandez, Jacob Kahn, Clara Na, Yonatan Bisk, Emma Strubell

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