During the day I'm a Data Scientist and Machine Learning Researcher in the making. I am passionate in solving real-world problems empirically especially exploring the synergy of SE development with Computational Science practice and understanding social network of researchers and how that tie mediate to a student’s performance and future scholar attainment. My prime areas of interest are Machine Learning, Data Science, and Algorithms specifically in Text Analytics and Graph Mining.
Beside daily learning and doing rocket sciences, I enjoy running, cooking, playing badminton, poetry, and playing board games.
PhD in Computer Science• August 2016 - Present
Graduate Merit Fellowship ($10,000+) for GPA 3.5+
Bachelor of Science in Computational Mathematics • 2011 - 2015
Minor in Computer Science
Graduated with Magna Cum Laude, 3.80/4.0. Top 5% of my graduated class.
Graduate Teaching and Research Assistant • January 2015 - Present
R&D Data Science Intern • May 2017 - August 2017
Web Developer Intern• May 2016 - August 2016
Head Resident Assistant • January 2013 - August 2015
Mined and investigated unstructured 25k Facebook users’ posts through Vietnamese language processing with traditional machine learning methods, convolutional neural networks, & LSTM to predict the user’s age. Achieved accuracy = 79.6%.
Developed a facial attractiveness rater based on the SCUT-FBP dataset, contains images of 500 Asian women and applying open-source OpenFace software to extract facial landmarks as features. With Pearson correlation of 0.86, convolutional neural networks outperform traditional machine learning method such as Random Forest (only achieved 0.64).
Built a recommendation system with Apache Spark and Alternative Least Square algorithm integrated users’ reviews sentiment analysis along with other attributes on the 4.5+ million reviews and 146k+ businesses Yelp dataset to suggest new businesses that are appropriate to the users’ interests.
Implemented DeepWalk as a graph-based technique to recommend the viewer-movie pair by evaluating and preference propagation algorithms (word2vec model) in heterogeneous information networks generated from user-item relationships.
Developed a bot on AWS that assigns & suggests suitable tasks for the developer along with recommending experienced developers in the team to help them if needed in real time through Slack interface and Github task tracking.