Data Mining Group

PhD students

  • MSc Vasileios Iosifidis
    Topics: fairness-aware machine learning & learning under limited labels. (semi-supervised learning, data augmentation), since June 2016.
  • MSc Amir Abolfazli
    Topics: Adaptive machine learning, since April 2019.
  • MSc Arjun Roy
    Topics: Fairness-aware machine learning, since September 2019.
  • MSc Le Quy Tai (with Prof. Wolfgang Nejdl)
    Topics: temporal data mining for energy dissaggregation and spatiotemporal data.
  • MSc Felipe Reis (with Prof. Wolfgang Nejdl)
    Topics: mining of re-occuring concepts and model merging.
  • Old PhDs

  • Damianos Melidis
    Damianos was working on ensemble learning over heterogeneous streams.(2017-2018)
  • HiWis

  • Alvaro Alvaro Veizaga Campero, Sentiment analysis.
  • Cai Yi, Semi-supervised learning.
  • Lijun Li, Ensemble learning.
  • Visiting students

  • Srijanani Saiegiridar,WS19/20-SS120, Sastra Deemed University, India.
  • Bahman Askari (Erasmus MSc student), WS18/19-SS19, University of Camerino, Italy. Working on his MSc thesis``The LSTM Deep Sequence Model and Points of Interests for Taxi-Passenger Demand Prediction''
  • Wenbin Zhang (Visiting PhD student), WS17/18-SS18, University of Maryland, USA. Working on fairness in an online learning setting. Related publication IJCAI 2019.
  • MSc/ BSc students

    Leibniz University Hannover (LUH), Germany

  • Philipp Naumann, MSc, ``Instance tweaking'', ongoing.
  • Leonard Zucht, MSc, ``Fair group recommendations'', ongoing.
  • Philip Ossenkopp, BSc, Memory in NNs, ongoing.
  • Niels Nuthmann, BSc, ``Detecting tendon failure from acoustic emission data with machine learning methods'' - in cooperation with Prof. Marx (Institut für Massivbau), SS19.
  • Wazed Ali, MSc, ``Sentiment Analysis using Deep Learning'', WS18/19.
  • Christopher Blake, MSc, ``Knowledge Production and Control of a Black Box Using Machine Learning'', WS18/19. Related publication
  • Theresa Tholsti, BSc, ``Stability of high dimensional stream clustering'', SS18.
  • Kersten Nicksch, BSc, ``Multicriteria recommendations with implicit criteria'', SS18.
  • Simon Wingert, MSc, ``Augmentation on image data for deep learning'', SS18.
  • Alvaro Alvaro Veizaga Campero, MSc, ``Sentiment Analysis with Deep Learning'', SS18.
  • Ruben Hohndorf, MSc, ``Data stream clustering", SS18.
  • Bin Li, MSc, ``Anomaly detection in sensor streams'', SS18.
  • Monseh Haghaieghshenasfard, Research project, Taxi Fare Prediction, SS18.
  • Al Kafi Khan, Research project, ``Predictive Maintenance'', SS 17
  • Amit Tyagi, MSc project, “Outlier detection in data streams", SS 17.
  • Rajib Das, MSc, “Mining opinionated product features from Amazon reviews", SS 17.
  • Alvaro Alvaro Veizaga Campero, Research project, “Lexicon-based approaches for sentiment analysis in Twitter", SS 17. Related publication
  • Lijun Lyu, Research project, “Wikipedia Entity Enrichment from News Streams", SS 17.
  • Nrithya Muniswamy & Nidhi Chachra, Research project, “Implicit network mining from archive collections", SS 17.
  • Sudhir Kumar Sah, MSc, “Topic extraction from archive collections", WS 16/17.
  • Ludwig Maximilians University (LMU) Munich, Germany

  • Omar Backhoff, MSc, “Scalable Online-Offline Stream Clustering in Apache Spark”, TUM Munich, 2017. Related publication
  • Daniel Basaran, MSc, “On the effect of duplicated reviews on performance statistics of recommender systems”, LMU Munich, 2016. Related publication
  • Benedikt Böhm, Project work, “Building blocks for multicriteria recommendation systems”, LMU Munich, 2016.
  • Yulia Bobkova, BSc, Interaktive Bestimmung charakterstischer Punktmengen durch Kombination von Clusterings”, LMU Munich, 2016. Related publication
  • Hossain Mahmud, MSc, “Ensemble Learning in Data Streams”, TUM Munich, 2016.
  • Sebastian Wagner,BSc, “Ageing-based Multinomial Naive Bayes Classifiers over Data Streams”, LMU Munich, 2015. Related publication
  • Annina Oelschläger, BSc, “Adaptive Ageing of Multinomial Naive Bayes Classifiers over Opinionated Data Streams”, LMU Munich, 2015.
  • Tabea Schmidt, “High Dimensional Stream Clustering”, LMU Munich, 2015.
  • Michael Stockerl, MSc, "Find Templates for Scans and Pictures of Paper Documents", LMU Munich, 2014. Related publication
  • Michael Stockerl, Project work, "Distributed Computation of User Similarities", LMU Munich, 2014.
  • Claudia Lauschke, MSc, "Topic extraction and evolution monitoring in social streams", LMU Munich, 2014. Related publication
  • Katharina Rausch, MSc, "Exploring Subspace Clustering for Recommendations", LMU Munich, 2013. Related publication
  • Michalis Petropoulos, BSc, “gRecs: A Group Recommendation System”, LMU Munich, 2013. Related publication
  • Charlotte Prieß, BSc, “Domain-specific sentiment analysis in Twitter using Bayesian classifiers”, LMU Munich, 2012.
  • Alina Sinelnikova, BSc, “Sentiment analysis in the Twitter stream”, LMU Munich, 2012. Related publication
  • Alexander Velkov, Diploma thesis, "Incremental Data Bubbles for Non-Vector Data in Arbitrary Metric Space", LMU Munich, 2011.
  • Kumar Subramanim, Diploma thesis, "Community Detection in Social Networks using Density Based Clustering Algorithms", LMU Munich, 2011. Related publication
  • Claudia Lauschke, BSc, "User Profile Monitoring in Twitter", LMU Munich, 2011.
  • Veselin Georgiev, Project work, "Web Profile Monitoring", Projektarbeit, LMU Munich, 2011.
  • University of Piraeus, Greece

  • Georgios Tzoumis, MSc, “Data warehousing for news portals”, University of Piraeus, 2006.
  • Marios Mpartzokas, BSc, "Comparing complex patterns: a study on collections of documents", University of Piraeus, 2006.
  • Anastasia Tzeveleka, BSc, "Duck-miner: A Tool for Discovering and Handling Knowledge from Large DBs", University of Piraeus, 2005.