CV
Education
- Ph.D. in Computer Science, Northeastern University, 2023 – Present
- Advised by Prof. Dakuo Wang
- B.S. in Computer Science, Beijing University of Technology, 2019 – 2023
- Principle of Compiling 96, Formal Language 96, Principle of Operating System 95, Operations Research 97, Probability Theory 97, Design and Analysis of Algorithms 99
- GPA 3.84, Major GPA 3.96
- Graduated with Honor
- High School, Beijing National Day School
- Always be proud of this experience.
Awards
- Bronze Medal, 2021 ICPC Asia Regional Contest Shenyang Site
- Bronze Medal, 2020 ICPC Asia Regional Contest Yichuan Site
- Bronze Medal, 2019 ICPC Asia Regional Contest Yichuan Site
- Global Rank 42 (top 2%), IEEE Xtreme 14.0 (2020)
- Global Rank 85 (top 3.5%), IEEE Xtreme 14.0 (2021)
Preprints
2025
- In SubmissionUXAgent: A System for Simulating Usability Testing of Web Design with LLM AgentsApr 2025In Submission to UIST 2025
- In SubmissionAgentA/B: Automated and Scalable Web A/BTesting with Interactive LLM AgentsApr 2025In Submission to UIST 2025
- In SubmissionMoS-EVAL: A Mixture-of-Stakeholders Evaluation Framework for Multi-Dimensional Real-World Text Generation AssessmentFeb 2025In Submission to EMNLP 2025
- In SubmissionOPeRA: A Dataset of Observation, Persona, Rationale, and Action for Evaluating LLMs on Human Online Shopping Behavior SimulationFeb 2025In Submission to EMNLP 2025
2023
Publications
2025
2024
2023
- TCBB 2023Improving Biomedical Question Answering by Data Augmentation and Model WeightingIEEE/ACM Transactions on Computational Biology and Bioinformatics, Dec 2023
2022
2021
- BIBM 2021Dual Model Weighting Strategy and Data Augmentation in Biomedical Question AnsweringIn 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Dec 2021
Work experience
- Sep. 2024 – Present: Applied Scientist Intern @ Amazon
- Search team
- Jul. 2022 – May 2023: Machine Learning Researcher @ LinkedIN & Microsoft Research Asia
- Contextual Summary for User Profile Regarding Job Description
- Contextual summarization research on LinkedIn data. Generate a summary for each candidate profile regarding each job description to help HR to know the candidates faster.
- As the main contributor to this project, I’m responsible for collecting data, designing and evaluating the method, and designing experiments.
- Heterogeneous Knowledge-based Person-Job Fit
- Person-Job Fit research using heterogeneous GNN pre-training.
- We are the first work to leverage social knowledge among members to help enhance the performance of Person-Job Fit.
- Participated in method designing and I’m responsible for collecting data and running baseline experiments.
- This work is accepted to WSDM 2024.
- Contextual Summary for User Profile Regarding Job Description
- Dec. 2021 – Jun. 2022: Intern Research Assistant @ Tsinghua University, Natural Language Processing Lab
- Big Model for Knowledge Graph (BMKG)
- Develop a toolkit to help train large Knowledge Embedding models on large KGs and run various downstream tasks.
- Supports 4 levels of parallel during the training process of translation-based or context-based Knowledge Embedding models.
- I’m responsible for designing the framework and writing code that need high performance.
- Design / Develop / Maintain multiple demos for NLP models
- I designed and maintain multiple demos for NLP models to show their performance to non-specialists.
- Big Model for Knowledge Graph (BMKG)
- Dec. 2020 – Jun. 2021: Research Assistant @ Beijing University of Technology
- Machine Reading Comprehension research in Biomedical Domain.
- Supported by a National-level undergraduate research program.
- Designed a contextual embedding and model weighting strategy to learn domain knowledge ** in Biomedical Question Answering task. **Outforms SOTA models by a large margin
- Published in ACM BCB 2022. I’m the leader of this project, and I’m responsible for designing the model, conducting experiments and writing the paper.
Teaching Assistant Experiences
- Advanced Language & Programming Design – 2019
- Advanced Language & Programming Design Course Design – 2020
- Data Structure & Algorithm – 2021
- Operating System Course Design – 2021
Projext Experiences
- Apr. 2020 – Jun. 2022 Course Grading and Feedback System based on Fault-Cause analysis
- An autograding system that can help daily teaching and give accurate scores and feedback based our automatic fault-cause clustering method.
- Supported by a National-level undergraduate research program.
- Capable of handling 500+ QPS while other similar systems can only do 20+.
- 72% of the 60k+ line is covered by unit tests.
- Found a bug in the go compiler (see golang/go#44614).
- Check project introduction to learn more.
- I’m the leader of this project, and I’m responsible for designing the system architecture, code reviewing, and full stack developing.
Skills
- Programming: Multilingual. Fluent in python, rust, go, c++, php, JavaScript, etc.
- English: Fluent (TOEFL 105, best scores 30/29/24/25)
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