Update README.md

Author: hh4ts

README.md

@@ -58,10 +58,18 @@ This tutorial targets researchers, students, and practitioners interested in dee
 ### (Q&A - 10 min)
 
 
-## Short Bio of Tutors
+## Short Bio of Presenters
 
-<img align="left" src="figs/kunyi.jpeg" width="80" height="100" style="margin-right: 20px; object-fit: cover; border-radius: 50%;">**[Kun Yi](https://github.com/aikunyi)** is affiliated with the State Information Center and specializes in deep learning with a focus on big data analytics and
-frequency-based methods for time series. His current research explores the integration of multimodal large language models (LLMs) into time series analysis to advance macroeconomic governance.
+<img align="left" src="figs/qingsongwen.png" width="80" height="100" style="margin-right: 20px; object-fit: cover; border-radius: 50%;">**[Qingsong Wen](https://sites.google.com/site/qingsongwen8/)** is currently the Head of AI & Chief Scientist at Squirrel Ai Learning. Before that, he worked at Alibaba, Qualcomm, Marvell, etc., and received his M.S. and Ph.D. degrees in Electrical and Computer Engineering from Georgia Institute of Technology, USA. His research interests include machine learning, data mining, and signal processing, especially AI for Time Series (AI4TS), LLM & AI Agent. Currently, he serves as Co-Chair of Workshop on AI for Time Series (AI4TS @ KDD, ICDM, SDM, AAAI, IJCAI). He also serves as Area Chair of NeurIPS, ICML, KDD, IJCAI, etc.
+<br clear="left">
+
+<img align="left" src="figs/ruiliu.png" width="80" height="100" style="margin-right: 20px; object-fit: cover; border-radius: 50%;">**[Rui Liu](rayliu@ku.edu)** is currently a Ph.D. student in the Department of Electrical Engineering and Computer Science at the University of Kansas, USA, under the supervision of Dr. Dongjie Wang. His research focuses on tabular data mining and tabular foundation models. He is also dedicated to integrating LLMs, federated learning, and causal inference into tabular data learning, aiming to advance efficient, interpretable, and scalable data science systems.
+<br clear="left">
+
+
+## Short Bio of Contributors
+
+<img align="left" src="figs/kunyi.jpeg" width="80" height="100" style="margin-right: 20px; object-fit: cover; border-radius: 50%;">**[Kun Yi](https://github.com/aikunyi)** is affiliated with the State Information Center and specializes in deep learning with a focus on big data analytics and frequency-based methods for time series. His current research explores the integration of multimodal large language models (LLMs) into time series analysis to advance macroeconomic governance.
 <br clear="left">
 
 <img align="left" src="figs/qizhang.jpg" width="80" height="100" style="margin-right: 20px; object-fit: cover; border-radius: 50%;">**[Qi Zhang](https://sites.google.com/view/qizhang-bit-uts)** is currently a associate professor at Tongji University. His research focuses on time series analysis, frequency-domain neural network, and general AI. Qi Zhang has published 60+ top-rank papers. He has also delivered 4 tutorials on data mining, recommender systems. Additionally, he has experience as a teaching assistant, teaching courses on Machine Learning and the Frontier of Computer Science at Tongji University.
@@ -70,10 +78,10 @@ frequency-based methods for time series. His current research explores the integ
 <img align="left" src="figs/weifan.jpg" width="80" height="100" style="margin-right: 20px; object-fit: cover; border-radius: 50%;">**[Wei Fan](https://weifan.site)** is currently working as a Postdoctoral Researcher in the Medical Sciences Division at the University of Oxford, UK. His research focuses on data-centric AI, time series modeling, and spatial-temporal data mining. He is also dedicated to applying these methods to solve real-world data science applications, such as healthcare, transportation, and energy. 
 <br clear="left">
 
-<img align="left" src="figs/qingsongwen.png" width="80" height="100" style="margin-right: 20px; object-fit: cover; border-radius: 50%;">**[Qingsong Wen](qingsongedu@gmail.com)** is currently the Head of AI & Chief Scientist at Squirrel Ai Learning. Before that, he worked at Alibaba, Qualcomm, Marvell, etc., and received his M.S. and Ph.D. degrees in Electrical and Computer Engineering from Georgia Institute of Technology,  USA. His research interests include machine learning, data mining, and signal processing, especially AI for Time Series (AI4TS), LLM & AI Agent. Currently, he serves as Co-Chair of Workshop on AI for Time Series (AI4TS @ KDD, ICDM, SDM, AAAI, IJCAI). He also serves as Area Chair of NeurIPS, ICML, KDD, IJCAI, etc.
+<img align="left" src="figs/huihe.png" width="80" height="100" style="margin-right: 20px; object-fit: cover; border-radius: 50%;">**[Hui He](https://scholar.google.com/citations?user=1IqAdRwAAAAJ&hl=zh-CN)** is currently a Ph.D. student in the School of Medical Technology at the Beijing Institute of Technology. Her research focuses on time series forecasting, time series anomaly detection, and foundation model pretrained on time series. She is also dedicated to integrating LLMs, frequency-domain learning, debiasing techniques, and probabilistic inference into time series analysis, thereby advancing efficient, interpretable, and scalable AI systems.
 <br clear="left">
 
-<img align="left" src="figs/huixiong.png" width="80" height="100" style="margin-right: 20px; object-fit: cover; border-radius: 50%;">**[Hui Xiong]( https://www.hkust-gz.edu.cn/people/hui-xiong/)** is a Chair Professor at Hong Kong University of Science and Technology (Guangzhou) and Associate Vice President for Knowledge Transfer. He have had the privilege of contributing extensively to the fields of artificial intelligence, machine learning, and data science, and he is recognized as an IEEE Fellow, AAAS Fellow, AAAI Fellow and ACM Distinguished Scientist for his work in advancing knowledge in these domains. Before his time at the Hong Kong University of Science and Technology, he was a distinguished professor at Rutgers, the State University of New Jersey, from 2007 to 2021. His accolades include the AAAI-2021 Best Paper Award, the 2018 Ram Charan Management Practice Award, as the Grand Prix winner from the Harvard Business Review, the 2017 IEEE ICDM Outstanding Service Award, the 2016 RBS Dean’s Research Professorship, the 2009 Rutgers University Board of Trustees Research Fellowship for Scholarly Excellence, the ICDM-2011 Best Research Paper Award.
+<img align="left" src="figs/huixiong.png" width="80" height="100" style="margin-right: 20px; object-fit: cover; border-radius: 50%;">**[Hui Xiong](https://www.hkust-gz.edu.cn/people/hui-xiong/)** is a Chair Professor at Hong Kong University of Science and Technology (Guangzhou) and Associate Vice President for Knowledge Transfer. He have had the privilege of contributing extensively to the fields of artificial intelligence, machine learning, and data science, and he is recognized as an IEEE Fellow, AAAS Fellow, AAAI Fellow and ACM Distinguished Scientist for his work in advancing knowledge in these domains. Before his time at the Hong Kong University of Science and Technology, he was a distinguished professor at Rutgers, the State University of New Jersey, from 2007 to 2021. His accolades include the AAAI-2021 Best Paper Award, the 2018 Ram Charan Management Practice Award, as the Grand Prix winner from the Harvard Business Review, the 2017 IEEE ICDM Outstanding Service Award, the 2016 RBS Dean’s Research Professorship, the 2009 Rutgers University Board of Trustees Research Fellowship for Scholarly Excellence, the ICDM-2011 Best Research Paper Award.
 <br clear="left">
 
 
@@ -83,6 +91,19 @@ frequency-based methods for time series. His current research explores the integ
   > - [Qingsong Wen, Linxiao Yang, Tian Zhou, Liang Sun, Robust Time Series Analysis and Applications: An Industrial Perspective. In SIGKDD 2022.](https://qingsongedu.github.io/timeseries-tutorial-kdd-2022/)
 
 
+## Cite Our Work 
+
+If you find our work useful, please cite our work:
+- Survey paper (A Survey on Deep Learning based Time Series Analysis with Frequency Transformation)
+```
+@inproceedings{10.1145/3711896.3736571,
+author = {Yi, Kun and Zhang, Qi and Fan, Wei and Cao, Longbing and Wang, Shoujin and He, Hui and Long, Guodong and Hu, Liang and Wen, Qingsong and Xiong, Hui},
+title = {A Survey on Deep Learning based Time Series Analysis with Frequency Transformation},
+year = {2025},
+series = {KDD '25}
+}
+```
+
 
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