I am a PhD candidate and software engineer who is passionate about turning challenges into opportunities with inspired data. My research focuses on applying machine learning techniques to improve big data management systems, especially in spatial databases. Here is my CV
Spatial Partitioning using Deep Learning: utilize the power of deep learning to build a model that can predict the best partitioning technique for a given spatial dataset. Source Code.
Query Optimization using Deep Learning: explore the capabilities of deep learning in the context of query optimization.
Indexing Techniques for Big Spatial Data: build a big data management system which fully supports spatial data processing. Source Code.
CS 014 - Introduction to Data Structures and Algorithms (Fall 2017, Summer 2018): CS 014 introduces the students to the fundamental data structures and algorithmic analysis techniques such as lists, stacks, queues, search trees, sorting algorithms, hash tables, and graphs.
CS 141 - Intermediate Data Structures and Algorithms (Winter 2018, Spring 2018): CS 141 provides the basic background for a computer scientist in the area of data structures and algorithms. During this course, students will learn problem solving skills, how to compare them, and how to apply them in real problems.
CS 218 - Design and Analysis of Algorithms (Fall 2018): Study of efficient data structures and algorithms for solving problems from a variety of areas such as sorting, searching, selection, linear algebra, graph theory, and computational geometry. Worst-case and average-case analysis using recurrence relations, generating functions, upper and lower bounds, and other methods.
CS 167 - Introduction to Big Data (Spring 2020): CS 167 covers the data management and systems aspects of big data platforms such as Hadoop, Spark, and AsterixDB. In this course, you will learn how the data is stored in a distributed file system and how the queries run in parallel.
Map & GeoSpatial Group, Microsoft AI & Research: explore how to leverage machine learning, deep learning as well as geospatial technology to improve the quality of Bing Maps geocoding system.
ArcGIS GeoDatabase Group: applied parallel processing techniques to improve the performance and scalability of Utility Network operations; won the 2nd Place and Best Presentation Award at ESRI Intern Hackathon.
R&D Division: developed a database system for the largest online game service in Vietnam with 5 million customers.
Emotion recognition system: developed a machine learning system to identify human emotion based on EEG signal.
Please visit my Google Scholar profile for the most updated publications
Tin Vu, Alberto Belussi, Sara Migliorini and Ahmed Eldawy, "Using Deep Learning for Big Spatial Data Partitioning", ACM Transactions on Spatial Algorithms and Systems (TSAS), To Appear
Tin Vu and Ahmed Eldawy, "DeepSampling: Selectivity Estimation with Predicted Error and Response Time", DeepSpatial2020, 1st ACM SIGKDD Workshop on Deep Learning for Spatiotemporal Data, Applications, and Systems
Tin Vu and Ahmed Eldawy, "R*-Grove: Balanced Spatial Partitioning for Large-scale Datasets", Frontiers in Big Data, section Data Mining and Management.
Tin Vu, Ahmed Eldawy, Vagelis Hristidis and Vassilis Tsotras, "Incremental Indexing for Big Spatial Data", Under Submission
Saheli Ghosh, Tin Vu, Mehrad Amin Eskandari and Ahmed Eldawy, "UCR-STAR: the UCR spatio-temporal active repository", SIGSPATIAL Special 11, no. 2 (2019): 34-40.
Tin Vu, Sara Migliorini, Ahmed Eldawy and Alberto Belussi, "Spatial Data Generators", ACM SIGSPATIAL 2019 International Workshop on Spatial Gems, Best Paper Award
Tin Vu, "Deep Query Optimization", SIGMOD Student Research Competition 2019, sponsored by Microsoft, in Amsterdam, The Netherlands, June 30 - July 5, 2019
Tin Vu and Ahmed Eldawy, "R-Grove: Growing a Family of R-trees in the Big-Data Forest", in Proceedings of the 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL 2018), in Seattle, WA, November 6-9, 2018
Thanh Nguyen Trung, Tin Vu, Minh Nguyen, "BFC: High performance distributed big file cloud storage based on key value store", 16th IEEE/ ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/ Distributed Computing, Takamatsu, Japan, 06/2015