diff --git a/_layouts/about.liquid b/_layouts/about.liquid index 66c898e..d5881fb 100644 --- a/_layouts/about.liquid +++ b/_layouts/about.liquid @@ -16,19 +16,17 @@ layout: default
{% if page.profile %} -
+
{% if page.profile.image %} {% assign profile_image_path = page.profile.image | prepend: 'assets/img/' %} - {% if page.profile.image_circular %} - Profile Image - {% else %} - Profile Image - {% endif %} + Profile Image {% endif %} +
{{ content }}
{% endif %} -
{{ content }}
diff --git a/_pages/about.md b/_pages/about.md index 6dbbb67..70234d9 100644 --- a/_pages/about.md +++ b/_pages/about.md @@ -20,7 +20,7 @@ jwang80 [at] wm.edu, jindongwang [at] outlook.com
Integrated Science Center 2273, Williamsburg, VA
[Google scholar](https://scholar.google.com/citations?&user=hBZ_tKsAAAAJ&view_op=list_works&sortby=pubdate) | [DBLP](https://dblp.org/pid/19/2969-1.html) | [Github](https://github.com/jindongwang) || [Twitter/X](https://twitter.com/jd92wang) | [Zhihu](https://www.zhihu.com/people/jindongwang) | [Wechat](http://jd92.wang/assets/img/wechat_public_account.jpg) | [Bilibili](https://space.bilibili.com/477087194) || [CV](https://go.jd92.wang/cv) [CV (Chinese)](https://go.jd92.wang/cvchinese) -Dr. Jindong Wang is a Tenure-Track Assistant Professor at William & Mary. Previously, he was a Senior Researcher in Microsoft Research Asia for over 5 years. His research interest includes machine learning, large language models, and AI for social science. He has published over 60 papers with 15000+ citations at leading conferences and journals such as ICML, ICLR, NeurIPS, TPAMI, IJCV etc. He serves as the associate editor of IEEE Transactions on Neural Networks and Learning Systems (TNNLS), guest editor for ACM Transactions on Intelligent Systems and Technology (TIST), area chair for ICML, NeurIPS, ICLR, KDD, ACMMM, and ACML, SPC of IJCAI and AAAI. His research is reported by [Forbes](https://www.forbes.com/sites/lanceeliot/2023/11/11/the-answer-to-why-emotionally-worded-prompts-can-goose-generative-ai-into-better-answers-and-how-to-spur-a-decidedly-positive-rise-out-of-ai/?sh=38038fb137e5) and other international media. In 2023 and 2024, he was selected by Stanford University as one of the [World's Top 2% Scientists](https://ecebm.com/2023/10/04/stanford-university-names-worlds-top-2-scientists-2023/) and one of the [AI Most Influential Scholars](https://www.aminer.cn/ai2000?domain_ids=5dc122672ebaa6faa962c2a4) by AMiner. He received the best paper award at ICCSE'18 and IJCAI'19 workshop. He published a book [Introduction to Transfer Learning](http://jd92.wang/tlbook). He gave tutorials at [IJCAI'22](https://dgresearch.github.io/), [WSDM'23](https://dgresearch.github.io/), [KDD'23](https://mltrust.github.io/), [AAAI'24](https://ood-timeseries.github.io/), and AAAI'25. He leads several impactful open-source projects, including [transferlearning](https://github.com/jindongwang/transferlearning), [PromptBench](https://github.com/microsoft/promptbench), [torchSSL](https://github.com/torchssl/torchssl), and [USB](https://github.com/microsoft/Semi-superised-learning), which received over 16K stars on Github. +Dr. Jindong Wang is a Tenure-Track Assistant Professor at William & Mary since 2025. Previously, he has been a Senior Researcher in Microsoft Research Asia for 5.5 years. His research interest includes machine learning, large language and foundation models, and AI for social science. He serves as the associate editor of IEEE Transactions on Neural Networks and Learning Systems (TNNLS), guest editor for ACM Transactions on Intelligent Systems and Technology (TIST), area chair for ICML, NeurIPS, ICLR, KDD, ACMMM, and ACML, SPC of IJCAI and AAAI. He has published over 60 papers with 15000+ citations at leading conferences and journals such as ICML, ICLR, NeurIPS, TPAMI, IJCV etc. His research is reported by [Forbes](https://www.forbes.com/sites/lanceeliot/2023/11/11/the-answer-to-why-emotionally-worded-prompts-can-goose-generative-ai-into-better-answers-and-how-to-spur-a-decidedly-positive-rise-out-of-ai/?sh=38038fb137e5), [MIT Technology Review](https://www.mittrchina.com/news/detail/13596), and other international media. Since 2022, he has been selected by Stanford University as one of the [World's Top 2% Scientists](https://ecebm.com/2023/10/04/stanford-university-names-worlds-top-2-scientists-2023/) and one of the [Most Influential AI Scholars](https://www.aminer.cn/ai2000?domain_ids=5dc122672ebaa6faa962c2a4) by AMiner. He received best and outstanding papers awards at several internation conferences and workshops. He published a book [Introduction to Transfer Learning](http://jd92.wang/tlbook). He gave tutorials at [IJCAI'22](https://dgresearch.github.io/), [WSDM'23](https://dgresearch.github.io/), [KDD'23](https://mltrust.github.io/), [AAAI'24](https://ood-timeseries.github.io/), and AAAI'25. He leads several impactful open-source projects, including [transferlearning](https://github.com/jindongwang/transferlearning), [PromptBench](https://github.com/microsoft/promptbench), [torchSSL](https://github.com/torchssl/torchssl), and [USB](https://github.com/microsoft/Semi-superised-learning), which received over 16K stars on Github. He obtained his Ph.D from University of Chinese Academy of Sciences in 2019 with the excellent PhD thesis award and a bachelor's degree from North China University of Technology in 2014. **PhD application in 25 Fall:** [[Visit this page](https://jd92wang.notion.site/Professor-Jindong-Wang-from-William-Mary-is-Recruiting-Fully-Funded-PhD-Students-Interns-for-Fall-12eb4ea70d8e803cadebd1a9b75fd739?pvs=4)] [[中文版](https://zhuanlan.zhihu.com/p/4827065042)] | [Internship or collaboration](https://forms.gle/zRcWP49qF9aR1VXW8)