Update about.md

shaoleiren · Aug 9, 2024 · e964d39 · e964d39
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@@ -23,11 +23,11 @@ I am an Associate Professor of [Electrical and Computer Engineering](https://www
 for building a **resilient, sustainable and equitable** future. Towards this goal, I study both algorithmic foundations and empirical methodologies, including:
 
 
-- **Sustainable AI:** Measuring and minimizing the environmental footprint of AI (**[Communications of the ACM](https://arxiv.org/abs/2304.03271), [e-Energy'24a](https://arxiv.org/abs/2405.17469), [e-Energy'24b](https://arxiv.org/abs/2311.03615), [ASPLOS'24](https://dl.acm.org/doi/abs/10.1145/3620665.3640374), [SIGMETRICS'22a](https://arxiv.org/abs/2111.01203)**)
+- **Sustainable AI:** Developing principled methodoogies to measure and minimize AI's environmental footprint (**[Communications of the ACM](https://arxiv.org/abs/2304.03271), [e-Energy'24a](https://arxiv.org/abs/2405.17469), [e-Energy'24b](https://arxiv.org/abs/2311.03615), [ASPLOS'24](https://dl.acm.org/doi/abs/10.1145/3620665.3640374), [SIGMETRICS'22a](https://arxiv.org/abs/2111.01203)**)
 
-- **Learning-augmented decision-making:** Robustifying machine learning predictions in highly dyanmic, uncertain, and/or adversarial environments (**[SIGEMETRICS'24](https://arxiv.org/abs/2401.04340), [NeurIPS'23a](https://arxiv.org/abs/2311.01568), [NeurIPS'23b](https://arxiv.org/abs/2310.20098), [ICML'23](https://arxiv.org/abs/2306.00172), [SIGMETRICS'22b](https://arxiv.org/abs/2204.08572)**) 
+- **Learning-augmented decision-making:** Robustifying and safeguarding machine learning predictions in highly dyanmic, uncertain, and/or adversarial environments (**[SIGEMETRICS'24](https://arxiv.org/abs/2401.04340), [NeurIPS'23a](https://arxiv.org/abs/2311.01568), [NeurIPS'23b](https://arxiv.org/abs/2310.20098), [ICML'23](https://arxiv.org/abs/2306.00172), [SIGMETRICS'22b](https://arxiv.org/abs/2204.08572)**) 
 
-- **Algorithmic fairness:** Building socially and environmentally equitable AI (**[ICML'24](https://arxiv.org/abs/2406.02790), [e-Energy'24c](https://arxiv.org/abs/2307.05494), [Harvard Business Review](https://hbr.org/2024/07/the-uneven-distribution-of-ais-environmental-impacts)**)
+- **Algorithmic fairness:** Building equitable AI to tackle societal challenges such as climage change (**[ICML'24](https://arxiv.org/abs/2406.02790), [e-Energy'24c](https://arxiv.org/abs/2307.05494), [Harvard Business Review](https://hbr.org/2024/07/the-uneven-distribution-of-ais-environmental-impacts)**)