Yiqiao Jin

Yiqiao Jin

Research Intern at Microsoft Research Asia (MSRA)

Georgia Institute of Technology

Biography

Yiqiao Jin (Ahren) is a Ph.D. student at Georgia Institute of Technology, advised by Professor Wei Xu.

He is working as a graduate research assistant at NLP X Lab.

Previously, he was working as a research intern at Microsoft Research Asia (MSRA), Social Computing Group, directed by Dr. Xing Xie. He is mentored by Dr. Xiting Wang and lead research projects on Fake News Detection, Explainable NLP, Low-Resource Machine Learning, and Recommendation.

Yiqiao also worked as an undergraduate research assistant at Scalable Analytics Institute (ScAi) under the mentorship of Prof. Yizhou Sun and Prof. Wei Wang.

Download my resumé.

Interests
  • Natural Language Processing
  • Graph Neural Networks
  • Data Mining
Education
  • PhD in Computer Science, 2022-2027

    Georgia Institute of Technology

  • BSc in Computer Science, 2018-2021

    University of California, Los Angeles (UCLA)

Experience

 
 
 
 
 
Georgia Institute of Technology
Graduate Research Assistant
Georgia Institute of Technology
Jul 2022 – Present Atlanta, GA, USA
Work on Extreme Classification and Social Media.
 
 
 
 
 
Microsoft Research Asia
Research Intern
Microsoft Research Asia
Dec 2020 – Jul 2022 Beijing, China

Publish two academic papers on Fake News Detection at top-tier conferences (AAAI'22 and KDD'22).

Conduct Research on Fake News Detection and Natural Language Processing for low-resource (limited data) scenarios.

 
 
 
 
 
UCLA Scalable Analytics Institute (ScAi)
Graduate Research Assistant
UCLA Scalable Analytics Institute (ScAi)
Jul 2021 – Jun 2022 Los Angeles, CA, USA

Work on Graph-based Recommendation.

Construct a multi-modal dataset for code recommendation that covers multiple topics in Computer Science.

 
 
 
 
 
Amazon.com
Software Engineer Intern
Amazon.com
Jun 2020 – Sep 2020 Seattle, WA, USA

Worked on the backend services of Amazon FBA Team

Created IAR Manual Analysis, an AWS Step Functions workflow that uses AWS Lambda to aggregate datapoints from various data sources (S3, DynamoDB) for SageMaker ML model training, and handles $\ge$ 16,000 requests per summary stage.

 
 
 
 
 
IBM
Software Engineer Intern
IBM
Jun 2019 – Sep 2019 Beijing, China

Worked on the backend services of IBM Cloud. Developed

Created IAR Manual Analysis, an AWS Step Functions workflow that uses AWS Lambda to aggregate datapoints from various data sources (S3, DynamoDB) for SageMaker ML model training, and handles $\ge$ 16,000 requests per summary stage.

Recent Publications

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(2022). Prototypical Fine-tuning: Towards Robust Performance Under Varying Data Sizes. Preprint.

(2022). Reinforcement Subgraph Reasoning for Fake News Detection. In KDD.

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(2022). Towards Fine-Grained Reasoning for Fake News Detection. In AAAI.

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