add aboutme

_bibliography/papers.bib

@@ -9,11 +9,11 @@ @article{zhao2023performative
   selected={true}
 }
 
-@article{zhao2023pinnsformer,
+@inproceedings{zhao2023pinnsformer,
   title={PINNsFormer: A Transformer-Based Framework For Physics-Informed Neural Networks},
   author={Zhao, Zhiyuan and Ding, Xueying and Prakash, B Aditya},
-  journal={arXiv preprint arXiv:2307.11833},
-  year={2023},
+  journal={International Conference on Learning Representations},
+  year={2024},
   selected={true}
 }
 

_pages/about.md

@@ -19,7 +19,14 @@ selected_papers: true # includes a list of papers marked as "selected={true}"
 social: true  # includes social icons at the bottom of the page
 ---
 
-I am a second year Ph.D. student at GeorgiaTech
+I’m a second-year [Machine Learning Ph.D. student](https://ml.gatech.edu/) in [Department of Computational Science and Engineering](https://cse.gatech.edu/) at [Georgia Institute of Technology](https://www.gatech.edu/). I am affiliated with AdityaLab and advised by [Dr. B Aditya Prakash](https://faculty.cc.gatech.edu/~badityap/). My research focuses on time-series forecasting with various techniques, such as attention, causality, physics-regularization, and LLMs. These research results have made real-world influences such as Flu and COVID-19 forecasting challenges organized by CDC.
+
+I am also interested in pre-trained foundation models and applications of LLMs in time series tasks. Previously, my research spanned physics-informed neural networks with the advice of Prof. Aarti Singh and federated learning under the advice of Prof. Gauri Joshi at Carnegie Mellon University.
+
+My current research focus includes:
+1. Learning performativity and causality representations for time-series forecasting;
+2. Zero-shot time-series forecasting using LLMs and multi-modality large models;
+3. Out-of-distribution (OOD) generalization for time series.
 
 <!-- Write your biography here. Tell the world about yourself. Link to your favorite [subreddit](http://reddit.com). You can put a picture in, too. The code is already in, just name your picture `prof_pic.jpg` and put it in the `img/` folder.