Ho, Thi Thao Nguyen

I am a Postdoc Research Associate at Aalborg University where
I am a member of DAISY research group and work with Prof. Torben Bach Pedersen. My current research focuses on Big Data Analytics and Machine Learning methods for spatio-temporal multidimensional big data. Initially, we are interested in identifying the relationships among big spatio-temporal data sets, which we have developed an efficient and adaptive algorithm to search for correlations among big spatio-temporal data. Potentially, this knowledge can be used to find patterns in unstructured data, or optimize machine learning algorithms making them more efficient and accurate through reducing the search space. I am also interested in other research problems, including big text analytics, machine translation, deep intelligence, big data systems optimization from data perspective, data provenance and reproducible research. During my PhD, I studied energy efficiency solutions for cloud infrastructures and applications. 

I received the PhD in Computer Science at Politecnico di Milano in Feb 2017. From September 2015 to April 2016, I was visiting scholar at New York UniversityCenter of Urban Science and Progress (CUSP). Previously, I obtained my master degree in Computer Science with distinction (cum laude) from Politecnico di Milano, Italy and my bachelor degree in Computer Science from Ho Chi Minh University of Technology, Vietnam. 

About Daisy: The database researchers at Daisy conduct research in data-intensive systems, spatio-temporal data management, (big) data analytics and mining, and (semantic) web data management. International evaluations place Daisy in the global top tier. An independent study of publication performance in the top database outlets in the 10-year period 2001-2010 ranks Daisy second among all research groups in Europe.

Email: ntth@cs.aau.dk, thithao.ho@polimi.it

Research Interests: Probabilistic Inference, Knowledge Extraction, Machine Learning, Big Data Analytics, Artificial Intelligence


News

  • I serve as PC member of IEEE BigData 2019.
  • Our paper has been accepted to the next issue of IEEE Transactions on BigData 2019.
  • Our paper has been accepted to IEEE ICDE 2019.
  • I serve as PC member of IEEE BigData 2018.
  • I serve as Demo track PC member of SSDBM 2018.
  • I serve as TPC member of ICAI 2018
  • I won the prestigious research grant to join highly talented postdoc program at Aalborg University, Denmark. 

Teaching
Spring 2018: Data Science and Big Data (Master course)
Fall 2017:  Aspects of Advanced Analytics (PhD course) - Lecturer
Fall 2017: Machine Intelligent - Thesis and Projects supervisor


Publications
DBLP (An incomplete list of publications)

Theses

In Submission and Working Topics
  • N.T.T. Ho et al., Spatio-Temporal Rule Extraction, 2019.
  • N.T.T. Ho et al., An Efficient Feature Selection Algorithm for Spatio-Temporal Data Sets, 2019. 

Journals

Conferences and Workshops

Awards
  • Highly Talented International Postdoc Grant, Aalborg University, Denmark, 2017-2019
  • Full PhD Research Grant, Politecnico di Milano, Italy, 2013 - 2016
  • Research Training Grant, COST Action IC1304, Würzburg, Germany, April 2015
  • Travel Grant, ACM SIGMETRICS IFIP- Performance, Turin, Italy, Oct 2014
  • Research Training Grant, Next Generation Enterprise Modeling, University of Vienna, Austria, 2014
  • Gold Scholarship, Politecnico di Milano, 2011 - 2013

Skills

  • Programming languages: Python, R, Java, C++, C#, SQL, Matlab, HTML5, PHP
  • Framework and Platform: Apache Spark, Apache Hadoop, Microsoft Azure
  • Soft skills: Even a geek can speak (New York University, 2015), Presenting for Impact and Persuasive Writing (Politecnico di Milano, 2016)

Services
References