During the day I'm a Data Scientist and Machine Learning Researcher in the making. I am passionate in solving real-world problems empirically. My prime areas of interest are Machine Learning, Data Science, and Algorithms specifically in Text Analytics, Computer Vision and Graph Mining.
Beside daily learning and researching, I love reading, running, cooking, playing badminton, and playing board games.
PhD in Computer Science• May 2016 - May 2019
I work with Dr Tim Menzies on real-time artificial intelligent for software engineering problems.
I work on estimating software effort, optimizing
requirements engineering problems and
analyzing trends in software engineering publications.
Bachelor of Science in Computational Mathematics • August 2011 - May 2015
Minor: 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 to recommend the viewer-movie pair.
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.