Academic and Professional Qualifications
Mr. Tran Hoang Loc possesses advanced degrees in Computer Science, culminating in a PhD, and demonstrates extensive expertise across multiple programming languages and cutting-edge data science methodologies. He is fluent in both English and Vietnamese
Education and Certifications
- Doctor of Philosophy (PhD) – Computer Science, completed at École Pratique des Hautes Études – PSL Research University, Paris, France. Defended March 25th, 2023
- Master of Science (MS) – Computer Science (with a Bioinformatics emphasis); GPA: 3.66/4.00. Completed at the University of Minnesota, Institute of Technology, Minneapolis, MN, USA (2012)
- Bachelor of Computer Science (BCS) – Graduated with distinction; GPA: 3.85/4.00. Completed at the University of Minnesota, Institute of Technology, Minneapolis, MN, USA (2003)
Technical Expertise and Core Skills
Mr. Loc’s expertise is heavily focused on data manipulation, algorithm implementation, and high-performance computing.
- Programming Languages: C, C++, assembly language for Intel-based computers, PLCs, high-performance computing using C and FORTRAN, PHP, and MapReduce. He has experience implementing login systems and shopping cart systems using PHP and mySQL.
- Software and Platforms: Proficient in Matlab, R, Python, and Microsoft Offices. He has experience using specialized tools like Neo4j and Cypher for Knowledge Graphs, and Gremlin, AWS Neptune, and Tom Sawyer for Supply Chain Knowledge Graphs.
- Methodological Familiarity: Familiar with linear algebra, data exploration theory, statistics, and probability. He is adept at dimensional reduction techniques (e.g., PCA, NMF, LLE, Laplacian Eigenmaps) and clustering techniques (e.g., k-mean, SOM, spectral clustering).
- Machine Learning Focus: Highly familiar with classification methods including ANN, SVM, (hyper-) graph-based semi-supervised learning, and graph (p-) Laplacian based semi-supervised learning. He is interested in learning MapReduce and Python, having studied them through independent projects like WordCount and PageRank.
Teaching Experience and Quality Management
Mr. Loc has experience in both formal lecturing and direct student support, coupled with professional skills related to curriculum planning.
- Lecturer: Currently serving as a Lecturer at Vietnam Aviation Academy (4/2024–now).
- Graduate Teaching Assistant: Served at the University of Minnesota (2003–2007), where responsibilities included grading papers and helping students solve homework problems in subjects such as number theory, college algebra, and pre-calculus.
- Planning and Management: Possesses the demonstrated ability to develop teaching and technical plans.
- Mathematical Proficiency: Has great skills in solving algebra, pre-calculus, and calculus problems.
Research and Achievements
Mr. Loc’s career blends extensive academic research, focused heavily on spectral (hyper)-graph theory and semi-supervised learning, with significant corporate experience as a Senior Data Scientist, applying these advanced techniques to challenging real-world problems.
Key Research Areas and Publications
His research interests include Data mining, Machine Learning, and Bioinformatics. His publications, which include papers indexed in Scopus and ESCI (ISI), center on novel applications of graph theory and machine learning to classification problems:
- Graph/Hypergraph Theory: Developed and applied graph Laplacian and hypergraph Laplacian based semi-supervised learning methods to problems like protein function prediction and cancer classification.
- Biological Networks: Explored applications of (SPARSE)-PCA and LAPLACIAN EIGENMAPS to the Biological Network Inference Problem using Gene Expression Data.
- Speech Recognition: Developed and applied un-normalized graph p-Laplacian based semi-supervised learning and combinations of PCA and Kernel Ridge Regression methods to the speech recognition problem.
- Neural Networks: Authored papers on Directed hypergraph neural networks and Noise-robust classification with hypergraph neural network.
Data Science and Technical Work Projects
His work history includes roles as a Senior Data Scientist/Engineer at various companies (Tenpoint7, TP&P, CREATORY), where he executed complex projects:
- Natural Language Processing (NLP) & Understanding (NLU): Worked on advanced NLP tasks, including Aspect based sentiment analysis (TP&P), Text Classification (sentiment/intent/genre), and Text Clustering (CREATORY).
- Knowledge Graphs: Developed Knowledge Graph systems for Questioning-Answering and Factual Checking. He also worked on a Supply Chain Knowledge Graph project, utilizing technologies like Gremlin, AWS Neptune, and Tom Sawyer (Tenpoint7-Capital One).
- Fraud Detection: Utilized unsupervised learning methods (k-mean, k-NN, LOF) to detect fraud transactions in big datasets (JVN – VNG Project).
- Face Recognition: Developed both PCA and Tensor sparse PCA based face recognition systems as part of a biometric security system, implementing the code in Matlab and C. This task involved learning the sparse optimization technique known as the Alternating Direction Method of Multipliers (ADMM).
- High-Performance Computing: Implemented parallel versions of code for tasks like Circuit partitioning (Spectral clustering) using C and MPI
