Vietnamese Machine
Resume:
NGUYỄN DUY NHẬT
Computer Science
Male
*************@*****.***
Ho Chi Minh city, Vietnam
www.linkedin.com/in/nguyễn-duy-nh
ật-65323520a
ABOUT
I am a computer science student at the
University of Information Technology,
Vietnam National University, Ho Chi Minh
City. I have experience in Artificial
Intelligence with faculty at the school in
the field of Computer Science.
SKILL
Python
C++
SQL (MySQL)
Machine Learning, Deep Learning
Data Visualization (Python)
SOFT SKILLS
Problem solving
Time management
Quick learner
UNIVERSITY OF INFORMATION TECHNOLOGY OCT 2018 - PRESENT SENTENCE EXTRACTION-BASED MACHINE READING
COMPREHENSION FOR VIETNAMESE
2021 - 2022
XLMRQA: OPEN-DOMAIN QUESTION ANSWERING ON VIETNAMESE WIKIPEDIA-BASED TEXTUAL KNOWLEDGE SOURCE
2/2021 - 8/2021
VIREADER: A WIKIPEDIA-BASED VIETNAMESE READING
COMPREHENSION SYSTEM USING TRANSFER LEARNING
2020 - 2021
SQL(Basic) Certificate in HackerRank:
2022
Data Analysis Using Python – University of Pennsylvania: 2021
Top 5 in the VLSP 2021-ViMRC Challenge: Vietnamese Machine Reading Comprehension
2021
EDUCATION
Major: Computer Science
GPA: 8.02/10
ACHIEVEMENTS & EXPERIENCES
Co-author in a paper accepted at KSEM 2021
- Build the first dataset for evaluating sentence extraction-based machine reading comprehension for the Vietnamese.
- Analyze the dataset in terms of the question words for each question type in Vietnamese.
- Propose three types of approaches for the sentence extraction-based machine reading comprehension for Vietnamese.
Co-author in a paper accepted at ACIIDS 2022
- Introduce the XLMRQA Question Answering system for Vietnamese open-domain question answering on the UIT-ViQuAD dataset.
- Compare the performance of the XLMRQA Question Answering system with two complex and advanced question answering systems (DrQA, BERTSerini).
- Analysis of the performance of Question Answering systems (XLMRQA, DrQA, BERTSerini) was performed on different types of questions.
Co-author in a paper accepted at Journal of Intelligent & Fuzzy Systems 2021
- Propose a novel Vietnamese MRC system (ViReader) that implements multitask learning by combining a transformer-based sentence retriever with an XLM-R based answer extractor.
- Compare several sentence retrieval methods based on different information retrieval techniques, including TF-IDF, TextRank, BM25, and Sentence Transformer Retriever.
- Verify the performance of ViReader on the UIT-ViNewsQA and BiPaR datasets.
CERTIFICATIONS
HONORS & AWARDS
LANGUAGES
English
Vietnamese
https://www.hackerrank.com/certificates/971ab5f9345d https://coursera.org/share/d695ff47b2d58528f4d93b7e86517cf2
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