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Seoul Urban Data Science
In this project, we researched factors that impact on air quality levels. First, we collect millions of records of historical data including weather data and air pollutant data from 2010 to 2018 of many cities in China and South Korea. We evaluated the accuracy of different deep learning methods on air quality forecasting for these cities. We published three papers in this project, which present many valuable findings.
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2020, Spring Semester, GSDS Machine Learning and Deep Learning for Data Science
Workshop, Seoul National University, Graduate School of Data Science, 1900
2020, Autumn Semester, GSDS Distributed Machine Learning
Workshop, Seoul National University, Graduate School of Data Science, 1900
2021, Spring Semester, GSDS Machine Learning and Deep Learning for Data Science
Workshop, Seoul National University, Graduate School of Data Science, 1900
2021, Autumn Semester, GSDS Explainable AI
Workshop, Seoul National University, Graduate School of Data Science, 1900
timeline
Grad from HUST
Published:
Software Engineer, Olbius Vietnam
Published:
Internship at Big Data Institute, SNU
Published:
Start Master’s Program in ECE
Published:
Top 5 ZhongAn Hackathon (AI Track)
Published:
Complete Master’s Program
Published:
Start Ph.D. Program in ECE
Published:
Present My Paper at 23rd IEEE ICDM
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Present Two Papers at PAKDD 2024
Published:
Complete Ph.D. Dissertation Defense, SNU
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Senior Researcher at Arontier
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Complete Ph.D. Program, SNU
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