伊利诺伊理工招收多名CS博士生-数据挖掘/机器学习/自然语言处理/AI-2023 Spring/Fall
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伊利诺伊理工(Illinois Institute of Technology)计算机科学系助理教授Dr. Kai Shu招收计算机博士生多名 (提供全额奖学金，2023 Spring/Fall 入学) 。研究方向为数据挖掘，机器学习，社交计算，自然语言处理等领域。
Dr. Kai Shu于2020年入职伊利诺伊理工计算机科学系助理教授。Dr. Shu在2020年在亚利桑那州立大学 (Arizona State University) 获得计算机博士学位，师从Dr. Huan Liu(ACM/IEEE/AAAI/AAAS Fellow)。Dr. Shu在KDD, WWW, SIGIR, WSDM, AAAI, JICAI, NACCL, TKDE等数据挖掘./机器学习/自然语言处理领域顶级会议和期刊发表80余篇，曾担任ASONAM 2021的PC Chair。Dr. Shu博士期间获得2020 ASU Engineering Dean's Dissertation Award, Finalist of the 2021 BenchCouncil Distinguished Doctoral Dissertation Award等奖项。Dr. Shu博士期间出版了多个关于Fake News的书籍。Dr. Shu教职期间获得Google Cloud Research Credits Award, Finalist of Facebook (Meta) Research Faculty Award, Cisco Research Award等奖项。Dr. Shu入选百度发布的首份全球高潜力AI华人青年学者百强榜单和Aminer发布的2022年AI 2000人工智能最具影响力学者。Dr. Shu的Google Scholar引用（since 2017）为6114，h-index=28，i10-index=44，单篇最高引用2153（到2022年7月20日）。
关于Dr. Kai Shu的更多信息，请访问他的个人主页和Google Scholar主页
个人主页：cs.iit.edu
Google Scholar主页：scholar.google.com
舒老师研究经费充足，来源广泛，除了启动科研基金，还有美国政府机构(NSF, DARPA, IARPA)和工业界(Google, Cisco, DPI)的多项经费支持。现在可以招多个博士生，大家不要错过机会。感兴趣的学生请发送简历+成绩单至1point3acres.com
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Kai Shu is a Gladwin Development Chair Assistant Professor in the Department of Computer Science at Illinois Institute of Technology since Fall 2020. His research lies in machine learning, data mining, social computing with applications such as disinformation, education, and healthcare. He obtained his PhD in Computer Science at Arizona State University in July 2020, under the supervision of Professor Huan Liu. He was the recipients of 2022 Cisco Faculty Research Award, 2020 ASU Engineering Dean's Dissertation Award, 2020/2015 ASU CIDSE Doctoral Fellowship, 2018 SBP Disinformation Challenge Winner. He interned at Microsoft Research AI, Yahoo Research and HP Labs. His research is supported by the U.S. federal agencies (DARPA, IARPA, NSF) and industry organizations (Cisco, Google, DPI).
I am *ACTIVELY* looking for multiple self-motivated PhD students to conduct research in the area of data mining, machine learning, social media mining, and natural language processing. Interested students please feel free to drop me an email with your CV and transcript (and I can not reply to every individual email).
Dr. Kai Shu于2020年入职伊利诺伊理工计算机科学系助理教授。Dr. Shu在2020年在亚利桑那州立大学 (Arizona State University) 获得计算机博士学位，师从Dr. Huan Liu(ACM/IEEE/AAAI/AAAS Fellow)。Dr. Shu在KDD, WWW, SIGIR, WSDM, AAAI, JICAI, NACCL, TKDE等数据挖掘./机器学习/自然语言处理领域顶级会议和期刊发表80余篇，曾担任ASONAM 2021的PC Chair。Dr. Shu博士期间获得2020 ASU Engineering Dean's Dissertation Award, Finalist of the 2021 BenchCouncil Distinguished Doctoral Dissertation Award等奖项。Dr. Shu博士期间出版了多个关于Fake News的书籍。Dr. Shu教职期间获得Google Cloud Research Credits Award, Finalist of Facebook (Meta) Research Faculty Award, Cisco Research Award等奖项。Dr. Shu入选百度发布的首份全球高潜力AI华人青年学者百强榜单和Aminer发布的2022年AI 2000人工智能最具影响力学者。Dr. Shu的Google Scholar引用（since 2017）为6114，h-index=28，i10-index=44，单篇最高引用2153（到2022年7月20日）。
关于Dr. Kai Shu的更多信息，请访问他的个人主页和Google Scholar主页
个人主页：cs.iit.edu
Google Scholar主页：scholar.google.com
舒老师研究经费充足，来源广泛，除了启动科研基金，还有美国政府机构(NSF, DARPA, IARPA)和工业界(Google, Cisco, DPI)的多项经费支持。现在可以招多个博士生，大家不要错过机会。感兴趣的学生请发送简历+成绩单至1point3acres.com
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Kai Shu is a Gladwin Development Chair Assistant Professor in the Department of Computer Science at Illinois Institute of Technology since Fall 2020. His research lies in machine learning, data mining, social computing with applications such as disinformation, education, and healthcare. He obtained his PhD in Computer Science at Arizona State University in July 2020, under the supervision of Professor Huan Liu. He was the recipients of 2022 Cisco Faculty Research Award, 2020 ASU Engineering Dean's Dissertation Award, 2020/2015 ASU CIDSE Doctoral Fellowship, 2018 SBP Disinformation Challenge Winner. He interned at Microsoft Research AI, Yahoo Research and HP Labs. His research is supported by the U.S. federal agencies (DARPA, IARPA, NSF) and industry organizations (Cisco, Google, DPI).
I am *ACTIVELY* looking for multiple self-motivated PhD students to conduct research in the area of data mining, machine learning, social media mining, and natural language processing. Interested students please feel free to drop me an email with your CV and transcript (and I can not reply to every individual email).
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