Tai Le Quy

About

I am a Postdoctoral Researcher at the Institute for Web Science and Technologies, University of Koblenz. I hold a Bachelor degree in Education in Information Technology (2007) from the Thai Nguyen University of Education and a Master degree in Information Technology (2011) from the College of Technology , Vietnam National University, Ha Noi. I successfully defended my Ph.D. thesis, entitled "Fairness-aware Machine Learning in Educational Data Mining" (presentation, dissertation), at the L3S Research Center - Leibniz University Hannover (magna cum laude - very good) in 2023. My research interests are fairness-aware machine learning, educational data mining, responsible AI, clustering, and time series prediction. I have held a lecturer position with over nine years of experience teaching computer science at the Banking Academy of Vietnam and the Thai Nguyen University of Education in Vietnam and the IU International University of Applied Sciences (Berlin campus). I am teaching courses in Computer Science, Data Science, and Machine Learning for Bachelor and Master students.

Publications

Authors Title Venue Year Link
Tai Le Quy , Gunnar Friege, Eirini Ntoutsi Multi-fair capacitated students-topics grouping problem The 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2023) 2023
Tai Le Quy , Gunnar Friege, Eirini Ntoutsi A review of clustering models in educational data science towards fairness-aware learning Educational Data Science: Essentials, Approaches, and Tendencies – Proactive Education based on Empirical Big Data Evidence 2023
Tai Le Quy , Thi Huyen Nguyen, Gunnar Friege, Eirini Ntoutsi Evaluation of group fairness measures in student performance prediction problems SoGood 2022@ECML/PKDD 2022
Huyen Giang Thi Thu, Thuy Nguyen Thanh, Tai Le Quy Dynamic Sliding Window and Neighborhood LSTM-Based Model for Stock Price Prediction SN Computer Science 2022
Tai Le Quy, Arjun Roy, Vasileios Iosifidis, Wenbin Zhang, Eirini Ntoutsi A survey on datasets for fairness-aware machine learning WIREs Data Mining and Knowledge Discovery 2022
Tai Le Quy, Arjun Roy, Gunnar Friege, Eirini Ntoutsi Fair-Capacitated Clustering The 14th International Conference on Educational Data Mining (EDM 2021) 2021
Tai Le Quy, Eirini Ntoutsi Towards fair, explainable and actionable clustering for learning analytics The 14th International Conference on Educational Data Mining (EDM 2021) 2021
Huyen Giang Thi Thu, Thuy Nguyen Thanh, Tai Le Quy A Neighborhood Deep Neural Network Model using Sliding Window for Stock Price Prediction International Conference on Big Data and Smart Computing (BIGCOMP 2021) 2021
Bahman Askari, Tai Le Quy, Eirini Ntoutsi Taxi Demand Prediction using an LSTM-based Deep Sequence Model and Points of Interest 2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC) 2020
Tai Le Quy, Wolfgang Nejdl, Myra Spiliopoulou, Eirini Ntoutsi A Neighborhood-Augmented LSTM Model for Taxi-Passenger Demand Prediction International Workshop on Multiple-Aspect Analysis of Semantic Trajectories @ ECML-PKDD 2019 2019
Tai Le Quy, Sergej Zerr, Eirini Ntoutsiand, Wolfgang Nejdl Data augmentation for dealing with low sampling rates in NILM NILM 2018

Research Interests

Machine Learning
Data Mining
Fairness
Responsible AI
Learning Analytics
Educational Data Mining
Time series
Spatio - Temporal Data Mining

Research activities

Journal peer review

2021-Now ACM Transactions on Knowledge Discovery from Data (TKDD)
AI and Ethics (AIET)
Applied sciences
Complexity
Education and Information Technologies (EAIT)
Forecasting
Frontiers in Artificial Intelligence
Information Sciences (INS)
Information Systems (INFOSYS)
International Journal of Digital Earth - TJDE
Journal of Data Science and Analytics
Journal of Infrastructure Policy and Development (JIPD)
Knowledge and Information Systems (KAIS)
Mathematics
SN Computer Science
Scientific Report
The Journal of Supercomputing (SUPE)

Conference peer review

2020 CIKM 2020
2022 AIES 2022, AICS 2022, ECML/PKDD 2022, PAKDD 2022, IJCAI 2022
2023 AIED 2023, ECML/PKDD 2023
2024 AIED 2024, ECML/PKDD 2024, EDM 2024, ECAI 2024, AAAI 2025

Award and Funding

2023

PAKDD 2023 Student Registration Award

2022

Top-cited articles of WIREs Data Mining and Knowledge Discovery published in 2021 and 2022, according to Web of Science

2022

KDD 2022 Student Volunteers (co-organized with Student Travel Award)

2021

IEEE BigData 2021 Student Travel Award

2020 - Present

The PhD programme "LernMINT: Data-assisted teaching in the MINT subjects" supported by the Ministry of Science and Culture of Lower Saxony, Germany

2016 - 2020

The project on training PhD lecturers for universities and colleges in the period from 2010 to 2020 (Project 911), supported by the Ministry of Education and Training of Vietnam


Education

Ph.D. in Computer Science

July 2016 - October 2023 L3S Research Center - Leibniz University Hannover | Germany

Topic: Fairness-aware machine learning in educational data mining

Supervisor: Prof. Dr. Eirini Ntoutsi, Prof. Dr. Gunnar Friege

M.Sc. in Information Technology

October 2007 – June 2011 College of Technology, Vietnam National University, Hanoi | Vietnam

Thesis title: Natural language processing in Vietnamese text summarization (written in Vietnamese)

Supervisors: Prof. Dr. Pham Bao Son

B.Sc. in Education in Information Technology

September 2003 – June 2007 Thai Nguyen University of Education, Vietnam

Thesis title: Data compression with error detection and correction (written in Vietnamese)

Supervisor: Dr. Nguyen Van Truong

Work Experience

University of Koblenz

October 2024 - Now

Teaching
▪ Introduction to Web Science (WS 2024/2025)
▪ Übung zu Recommender Systems (WS 2024/2025)
▪ Research Lab: Exploring Bias and Fairness in Large Language Models (WS 2024/2025)

IU International University of Applied Sciences

March 2023 - September 2024

Teaching
▪ Introduction to Computer Science (Q2, 2023)
▪ Artificial Intelligence (Q2, 2023)
▪ Introduction to Programming with Python (Q3, 2023)
▪ Artificial Intelligence - DLMAIAI01 (Q3, 2023)
▪ Machine Learning - Supervised learning (Q3, 2023; Q1, 2024)
▪ Machine Learning - Unsupervised learning and feature engineering (Q3, 2023; Q1, 2024)
▪ Programming with Python (Q4, 2023)
▪ Object Oriented and Functional Programming with Python (Q4, 2023)
▪ Algorithms, data structures and programming languages (Q1, 2024)
▪ Data Science (Q1, 2024)
▪ Introduction to Data Science (Q1, 2024)
▪ Introduction to Reinforcement learning (Q1, 2024)
▪ Seminar: Computer Science and Society (Q3, Q4, 2023; Q1, 2024)

Free University Berlin

April 2021 - September 2021

Teaching assisstant
▪ Seminar Advance Topic in Data Mining (SS 2021)

Leibniz University Hannover

October 2016 - March 2020

Teaching assisstant
▪ Data Mining Lab (WS19/20)
▪ Seminar Data Mining (SS19)
▪ Data Mining I (SS17, SS18, SS19 )
▪ Seminar Advance Topic in Data Mining(WS17/18)
Student supervision
▪ B.Sc Thi Tu Nguyen, “Analysis of energy consumption data stream with deep learning”, WS 17/18
▪ M.Sc Bahman Askari, “Prediction of Taxi-Passenger Demand using Recurrent Neural Network", SS19

Banking Academy of Vietnam

August 2010 - June 2016

Teaching
▪ Programming fundamentals with C/C++
▪ Windows Programming with C#
▪ Data Structure and Algorithm
▪ Introduction to Informatics
Student supervision
▪ B.Sc Huong Nguyen Thu, “Decision trees in internal credit ratings”, 2012
▪ B.Sc Tinh Nguyen Thi, “Analysis and design of personal loan management system at Military Bank – West Hanoi Branch”, 2013
▪ B.Sc Huong Nguyen Thi, “ Analysis and design of cash accounting software for small and medium enterprises in Vietnam”, 2014
▪ B.Sc Trang Ngo Thi, “Analysis and design of warehouse management software at Tam Phuc Co., Ltd”, 2014
▪ B.Sc Van Bui Quynh, “ Developing the system of valuable paper depository at the State Bank of Vietnam”, 2015
▪ B.Sc Huyen Le Thi Thanh, “ Developing the one-stop administrative procedures software at the Department of Natural Resources and Environment of Bac Giang Province”, 2015


University of Koblenz

WS 2024/2025

Introduction to Web Science
Übung zu Recommender Systems
Research Lab: Exploring Bias and Fairness in Large Language Models (kick-off meeting)

IU International University of Applied Sciences

2023

Artificial Intelligence - DLBDSEAIS1(Q2, 2023)
Introduction to Computer Science (Q2, Q4 2023)
Introduction to Programming with Python (Q3, 2023)
Artificial Intelligence - DLMAIAI01 (Q3, 2023)
Machine Learning - Supervised learning (Q3, 2023)
Machine Learning - Unsupervised learning and feature engineering (Q3, 2023)
Programming with Python (Q4, 2023)
Object Oriented and Functional Programming with Python (Q4, 2023)

2024

Machine Learning - Supervised learning (Q1, 2024)
Machine Learning - Unsupervised learning and feature engineering (Q1, 2024)
Algorithms, data structures and programming languages (Q1, 2024)
Introduction to Data Science (Q1, 2024)
Data Science (DLMBDSA01) (Q1, 2024)
Introduction to Reinforcement Learning (Q1, 2024)
Programming with Python (Q2, 2024)
Artificial Intelligence - DLBDSEAIS1(Q2, 2024)
Artificial Intelligence - DLMAIAI01 (Q2 + Q3, 2024)
Analytical software and frameworks (Q2 + Q3, 2024)
Introduction to Programming with Python (Q3, 2024)

News

October 2024

I have joined the Institute for Web Science and Technologies , University of Koblenz as a Postdoctoral Researcher.

October 16th 2023

I successfully defended my PhD thesis, entitled "Fairness-aware Machine Learning in Educational Data Mining", at the L3S Research Center - Leibniz University Hannover, with magna cum laude (presentation, dissertation).

May 27th 2023

Our paper "Multi-fair Capacitated Students-Topics Grouping Problem" has been published in the proceedings of the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2023).

May 24th 2023

I got the student registration award of the PAKDD 2023 conference.

April 29th 2023

Our book chapter "A Review of Clustering Models in Educational Data Science Toward Fairness-Aware Learning" (a part of the book "Educational Data Science: Essentials, Approaches, and Tendencies") is now available on SpringerLink. A preprint version of this book chpater could be found here.

February 22st 2023

Our paper "Multi-fair Capacitated Students-Topics Grouping Problem" has been accepted to The Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2023).

February 21st 2023

Our article "A survey on datasets for fairness-aware machine learning" received enough citations to be a top cite darticle in WIREs Data Mining and Knowledge Discovery journal in 2021-2022.

January 13rd 2023

Our article "A survey on datasets for fairness-aware machine learning" in the WIREs Data Mining and Knowledge Discovery was one of the top 10 downloaded in 2022.

July 20th 2022

Our paper "Evaluation of group fairness measures in student performance prediction problems" has been accepted at SoGood 2022 workshop, held in conjunction with ECML/PKDD 2022

June 20th 2022

I got the KDD 2022 Student Volunteers (co-organized with Student Travel Award)

March 3rd 2022

Our article A survey on datasets for fairness-aware machine learning has been published in Wiley Online Library.

December 2021

I got the IEEE BigData 2021 Student Travel Award

April 10th 2021

Our research paper Fair-capacitated clustering has been accepted in the 14th International Conference on Educational Data Mining 2021.

Institute for Web Science and Technologies   |   University of Koblenz