Member info update

_members/anastasia_koloskova.md

@@ -1,7 +1,7 @@
 ---
 name: Anastasia Koloskova
 image: images/anastasia_koloskova.jpeg
-role: postdocs
+role: alu_post
 links:
   home-page: https://koloskova.github.io/
 ---

_members/angelina_wang.md

@@ -1,7 +1,7 @@
 ---
 name: Angelina Wang
 image: images/angelina_wang.jpeg
-role: postdocs
+role: alu_post
 links:
   home-page: https://angelina-wang.github.io/
 ---

_members/hejie_cui.md

@@ -1,9 +1,9 @@
 ---
 name: Hejie Cui
 image: images/hejie_cui.jpg
-role: postdocs
+role: alu_post
 links:
   home-page: https://hejiecui.com/
 ---
 
-Interested in LLM Post-training and Trustworthy Evaluation for Healthcare and Multimodal Foundation Models
+Interested in LLM Post-training and Trustworthy Evaluation for Healthcare and Multimodal Foundation Models

_members/zeyu_tang.md

@@ -1,10 +1,12 @@
 ---
 name: Zeyu Tang
-image: images/zeyu_tang.png
-role: visiting
+image: images/zeyu_tang.jpg
+role: postdocs
 links:
+  email: [email protected]
   home-page: https://zeyu.one/
+  linkedin: zeyu-tang-trustworthy-ai
+  twitter: zeyu1tang
 ---
 
-Zeyu Tang is a Ph.D. student at Carnegie Mellon University working on <b>trustworthy and responsible AI</b>. He conducts research on <b>causal learning and reasoning</b> to further enhance the capacity of intelligent systems, and <b>machine learning fairness / computational justice</b> to model and understand the social impact of computational technologies. His ultimate goal is to cultivate intelligence that is both safe and principled with the help of causality, so that technology can improve our lives with transparent responsibility and clear purpose. Tang is supported by the National Institute of Justice Graduate Research Fellowship, and the K&L Gates Presidential Fellowship in Ethics and Computational Technologies. 
-
+Zeyu Tang is a postdoctoral scholar working on <b>trustworthy and responsible AI</b>. He conducts research on <b>causal learning and reasoning</b> to further enhance the capacity of intelligent systems, and <b>machine learning fairness / computational justice</b> to model and understand the social impact of computational technologies. His ultimate goal is to cultivate intelligence that is both safe and principled with the help of causality, so that technology can improve our lives with transparent responsibility and clear purpose.