博士申请 | 美国弗吉尼亚理工大学Xuan Wang老师招收NLP/DM/ML方向博士生

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弗吉尼亚理工大学

弗吉尼亚理工（Virginia Tech）始建于 1872 年，是一所以工科为主的顶尖公立研究型大学，工程学科在世界范围内享有极高声誉。根据 2022 年 US News 全美大学排名，其工程学院本科项目居全美第 13 名，工程学院研究生项目居全美第 30 名，计算机专业居全美第 38 名。弗吉尼亚理工大学坐落于美国东海岸弗吉尼亚州的布莱克堡市（Blacksburg）。作为美国十大梦想小镇，全美最宜居小镇之一，布莱克堡以气候舒适、风景优美、治安良好而享誉全美。弗吉尼亚理工自 2019 年开展和 Amazon，Boeing 等公司的合作，CS department 开始了快速的扩张和学校重心的 focus 倾斜（很多很强的新 faculty 加入）同时 CS ranking 也在进一步上升。

导师简介

Dr. Xuan Wang will join Virginia Tech as an Assistant Professor in Spring 2023. Xuan received her Ph.D. in Computer Science (2022) from the University of Illinois at Urbana-Champaign (UIUC) under the supervision of Dr. Jiawei Han. She received M.S. in Statistics (2017) and M.S. in Biochemistry (2015) from UIUC. She received B.S. in Biological Science (2013) from Tsinghua University, China.

Website:

https://xuanwang91.github.io/

研究方向

Natural Language Processing (NLP) and Data Mining (DM):

1. Weakly-Supervised NLP and Text Mining:

Learning Paradigms: Distantly-Supervised, Semi-Supervised, Self-Supervised, Few-Shot, Zero-Shot Learning, …
Tasks: Information Extraction, Knowledge Graph Construction, Text Classification, Text Summarization, …

2. Multi-Modal Data Mining between Text and Graph

Text-Augmented Open Knowledge Graph Reasoning
Text-Graph Pre-Training for Multi-Modal Representation Learning

3. Interdisciplinary Applications

AI for Science
AI in Healthcare

招生信息

My lab at Virginia Tech has openings for PhD students and research internship opportunities for master/undergrad students. Prospective students satisfying the following criteria will be considered with a priority:

1. have publications in top NLP/DM/ML conferences;

2. have relevant research experiences in NLP/DM/ML;

3. have a strong background in CS/Math/Stats.

申请方式

Please email me if you’re interested in working with me: xwang174@illinois.edu

1. In your email, please include the following items:

2. Title as “Prospective Student: YourName - YourAffliation”

3. Briefly introduce what research problem you are interested in.

4. Briefly introduce yourself, including education background, research experiences, and programming skills.

5. Briefly explain your motivations and expectations of working with me.

6. Include a PDF version of your CV.