Vasileios Iosifidis

About Me

Hi my name is Vasileios (Bill) Iosifidis. I'm a researcher at the Faculty of Electrical Engineering and Computer Science, Leibniz University Hannover. My interests are: Fairness-Aware Machine Learning, Stream Learning, Semi-supervised Learning, Deep learning, Class-imbalance learning, Coding, Data Structures and new technologies. A recent curriculum vitae can be found here


PhD Thesis

I defended my thesis in July, 2020. The thesis was evaluated with the highest grade (summa cum laude) by all three members of the evaluation comittee (Prof. Dr. Eirini Ntoutsi, Prof. Dr. Salvatore Ruggieri, Prof. Dr. Ujwal Gadiraju). The electronic copy of my thesis can be accessed here, and the slide deck of my presentation is accessible here.

Research Interests

Fairness-Aware Machine Learning

Data Stream Mining

Semi-Supervised Learning

Data Augmentation

Ensemble Learning

Previous Experience

T.A, Seminar: Data Mining, Leibniz University of Hannover

SS19

T.A, Data Mining 1, Leibniz University of Hannover

SS17-19

T.A, Data Mining 2, Leibniz University of Hannover

WS16-19

T.A, Artificial Intelligence, Leibniz University of Hannover

SS18

T.A, Seminar: Advanced Topics in Data Mining, Leibniz University of Hannover

SS17-18

Researcher, Computer Technology Institute

February 2015 - April 2016

T.A., JAVA/C++ LAB, University of Patras

February 2015 - June 2015

T.A., ANSI C LAB, University of Patras

October 2014 - February 2015 / November 2016 - January 2016

Python Tutor, University of Patras

September 2014 - December 2014

Intern Software Engineer, SAMSUNG NANORADIO

May 2014 - August 2014

Intern IT, HELLENIC PETROLEUM GROUP OF COMPANIES

February 2015 - April 2016

Education

Ph.D. in Machine Learning

June 2016 - July 2020 Leibniz University Hannover & L3S Research Center | Hannover

Thesis title: Semi-supervised learning and fairness-aware learning under class imbalance

Supervisor: Prof. Eirini Ntoutsi

M.Sc. in Software Engineering

2014 - 2016 Computer Engineering and Informatics Department, University of Patras | Greece

Thesis title: A Fully Persistent Encryption Binary Tree For Range Queries

Supervisors: Prof. Christos Makris

Diploma (M.Sc.) in Computer Engineering

2009 - 2014 Computer Engineering and Informatics Department, University of Patras | Greece

Thesis title: Compressing Inverted Files using Modified LZW

Supervisor: Prof. Christos Makris

Nerdy Skills

Java

Python

C/C++

Matlab

Linux OS

Apache Hadoop

Apache Spark

Apache Storm

MySql

NOSQL(MONGO/REDIS/KAIROS/INFLUX)


Other Certificates

Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization, [link]

Coursera Jun 2019

Neural Networks and Deep Learning, [link]

Coursera Jun 2019

Structuring Machine Learning Projects, [link]

Coursera Jun 2019

Supervised Students

Discrimination-Aware Learning in Data Streams

Master Thesis: Thi Ngoc Han Tran SS18

Generator for Discriminatory Streams

Research project: Stefanos Stagakis SS18

Sentiment Analysis with Deep Learning

Master Thesis: Alvaro Alvaro Veizaga Campero SS18

Lexicon-based Approaches for Sentiment Analysis in Twitter

Research project: Alvaro Alvaro Veizaga Campero SS17

Publications

Hu, H. et al., "FairNN-Conjoint Learning of Fair Representations for Fair Decisions, International Conference on Discovery Science (DS 2020). [local copy]

V. Iosifidis, E. Ntoutsi, "FABBOO - Online Fairness-aware Learning under Class Imbalance", International Conference on Discovery Science (DS 2020). [local copy]

Ntoutsi, Eirini, et al., "Bias in data‐driven artificial intelligence systems—An introductory survey., Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 10.3 (2020): e1356. [local copy]

V. Iosifidis, B. Fetahu, E. Ntoutsi, "FAE: A Fairness-Aware Ensemble Framework", IEEE International Conference on Big Data (IEEE BigData 2019). [local copy]

V. Iosifidis, E. Ntoutsi, "AdaFair: Cumulative Fairness Adaptive Boosting", ACM International Conference on Information and Knowledge Management (CIKM 2019). [local copy]

V. Iosifidis, E. Ntoutsi, "Sentiment Analysis on Big Sparse Data Streams with Limited Labels", Knowledge and Information Systems (KAIS) journal. [local copy]

V. Iosifidis, H. Tran, E. Ntoutsi, ``Fairness-enhancing interventions in stream classification'', 30th International Conference on Databases and Expert Systems Applications (DEXA 2019) [local copy]

P. Fafalios, V. Iosifidis, K. Stefanidis, E. Ntoutsi, "Tracking the History and Evolution of Entities: Entity-centric Temporal Analysis of Large Social Media Archives.", Springer International Journal on Digital Libraries (IJDL). [local copy]

D. Melidis, A. Veizaga Campero, V. Iosifidis, E. Ntoutsi, M. Spiliopoulou, "Enriching Lexicons with Ephemeral Words for Sentiment Analysis in Social Streams", WIMS 2018. [local copy]

V. Iosifidis, E. Ntoutsi, "Dealing with Bias via Data Augmentation in Supervised Learning Scenarios", BIAS workshop in conjunction with iConference 2018. [local copy]

P. Fafalios, V. Iosifidis, E. Ntoutsi, S. Dietze, "TweetsKB: A Public and Large-Scale RDF Corpus of Annotated Tweets", ESWC, 2018. [local copy]

Mohapatra, N., Iosifidis, V., Ekbal, A., Dietze, S., & Fafalios, P. " Time-aware and corpus-specific entity relatedness", ESWC, 2018. [local copy]

V. Iosifidis, E. Ntoutsi, "Large scale sentiment annotation with limited labels",KDD, Halifax, Canada, 2017. [local copy]

V. Iosifidis, E. Ntoutsi, "Sentiment Classification over Opinionated Data Streams through Informed Model Adaptation", TPDL, Thessaloniki, Greece, 2017. [local copy]

P. Fafalios, V. Iosifidis, K. Stefanidis, E. Ntoutsi, "Multi-aspect Entity-centric Analysis of Big Social Media Archives", TPDL, Thessaloniki, Greece, 2017. [local copy]

V. Iosifidis, and C. Makris, "Compressing Inverted Files using Modified LZW." WEBIST 2016. [local copy]

Ispoglou, K., Makris, C., Stamatiou, Y. C., Stavropoulos, E. C., Tsakalidis, A. K., & Iosifidis, V., "Partial order preserving encryption search trees" In Database and Expert Systems Applications (pp. 49-56). Springer, Cham. [local copy]


Data Mining Group   |   L3S Research Center