Internal and external MSc Projects supervised by the DM group

Available assignments

Please check for uptodate possibilities with the faculty members of DM group. The best way to get an overview of projects to be offered in 2018 is to join 2IMM00 Data Mining Seminar.

Ongoing projects

  • Pieter Gijsbers Automatic construction of machine learning pipelines, expected by August 2017
  • Jeroen van Hoof Automatic model selection and optimization on OpenML, expected by August 2017
  • Hugo Spee Deep reinforcement learning for algorithm selection, expected by November 2017
  • Joana Iljazi Predicting plant growth in City Farms based on video analysis (Philips, supervised together with Marc Aoun and Marcel Krijn), expected by August 2017
  • Aditya Bhadoria Predicting plant growth in City Farms based on simulation data (Philips, supervised together with Marc Aoun and Marcel Krijn), expected by August 2017
  • Shefali Chand Anomaly detection in IoT sensor data (Philips, supervised together with Pierluigi Casale), expected by August 2017
  • Jun Lin Recommender systems for course recommendation (StudyPortals, supervised together with Tara Farzami), August 2017
  • Siqi Li User profiling and quality verification for automatic light script creation (Philips Lighting, supervised together with Dzmitry Aliakseyeu)
  • Marc van Meel Violence classification in text, expected by October 2017
  • Vincent van Bergen Realtime bidding (Targetcircle, supervised together with dr. Heiko Hildebrandt), expected by October 2017
  • Sander Breukink Health care insurance cost modelling , expected by September 2017
  • Jeroen van de Ven Daily activity modelling with recurrent neural networks, expected by August 2017
  • Chrsitopher Ankomah Image Analysis with Deep Learning for quality assurance , expected by August 2017
  • Yue Wang Document Summarization , expected October 2017
  • Rodrigo Mendoza Generative models for lung cancer detection from CT , expected by August 2017
  • Boshen Lyu Semi-supervised Semantic Segmentation of Images , expected by September 2017
  • Marijn van Knippenberg Evolutionary optimization for Deep Learning , expected by November 2017 (Philips, supervised together with Sergio Consolli)
  • Christoforos Boukouvalas Modelling EEG responses with Deep Learning , expected by November 2017
  • Sako Arts Deep Autoencoders for subtyping Glioblastoma using gene-expression data , expected by December 2017
  • Puck Mulders Neuro-language and linguistic models for sentence generation , expected October 2017

Completed in 2016 - 2017

  • Loek Tonnaer Active Learning in VAE Latent Space, August 2017
  • Tom Vrijdag False alarm reduction in fraud detection (Rabobank, supervised together with Werner van Ipenburg), August 2017
  • Zhanjie Zhu Anomaly detection in imbalanced, high-dimensional, evolving data streams (Rabobank, supervised together with Werner van Ipenburg), August 2017
  • Ming Zhang Automated event labeling for workflow analysis in hospitals (Philips Research, supervised together with dr. Supriyo Chatterjea), August 2017
  • Erik van der Burgt Real estate price prediction (Royal@Works), June 2017 link
  • Adrian Ampt Data driven insurance policy predictor (C-Profile), June 2017
  • Sjoerd van Bavel Machine learning applied to predicting heat usage in greenhouses (CQM, supervised together with Pleuni Naus and Judith van Rijswick), April 2017
  • Wouter Ligtenberg Tink, a temporal graph analytics library for Apache Flink (supervised together with G. Fletcher and Y. Pei) link
  • Junquan Xi Extraction from Unstructured data with Bi-directional stacked LSTMs (Rabobank, supervised together with dr. Vlado Menkovski and Jan Veldsink), April 2017 link
  • Robbert Raats Water usage profiling with pattern matching, (Betabit and LevenIsWater, supervised together with Auke van Balen) expected by December 2016
  • Roy Haanen Predicting aircraft time to fly profile on final approach, (Aerospace Operations Safety Institute (AOSI) of the Netherlands Aerospace Centre (NLR), supervised together with G.B. van Baren), October 2016 link
  • Hao Zhang User behaviour analysis and prediction based on device logs (Philips Research, supervised together with dr. Qi Gao and Mark Graus), October 2016 link
  • Adam Zika Identification of lead users on social media (Coosto.nl, supervised together with dr. Sarah Gelper and dr. Jorn Bakker), October 2016
  • Edward Brinkmann Improving the search engine user experience, October 2016 link
  • Rosa Sicilia Information diffusion in social media, (external MSc from U. Rome, supervised together with Yulong Pei and Paolo Soda), October 2016
  • Stella Lo Giudice Information diffusion in social media, (external MSc from U. Rome, supervised together with Yulong Pei and Paolo Soda), October 2016
  • Bob Giesbers Association rule mining of student grades, a Grammar Guided Genetic Programming approach, September 2016
  • Simon van der Zon Predictive Performance and Discrimination in Unbalanced Classification, September 2016 link
  • Dennis Eikelenboom Enterprise resource demand prediction through mining of sales data, (Microsoft), September 2016 link
  • Cas Hariri Data mining for understanding and optimizing building energy efficiency, (COFELY GDF-SUEZ), September 2016
  • Yangfengfan Zhang Philips Hue data analytics, (Philips Research, supervised together with dr. Pierluigi Casale), August 2016 link
  • Daniel Duwaer Self-learning adaptive traffic regulation and management, (LD Software), August 2016 link
  • Laavanyaa Balasubramanian Hospital workflow data analytics (Philips Research, supervised together with dr. Supriyo Chatterjea), July 2016
  • Fengjun Wang Analyzing machine data for predictive maintenance of electro chemical machining electrodes (Philips Research, supervised together with dr. Kees Wouters and dr. Qi Gao), July 2016 link
  • Harm Eggels Expected Goals in Soccer: Explaining Match Results using Predictive Analytics (PSV, supervised together with Ruud van Elk), August 2016 link
  • Koen Vrijdag Auction Price Prediction: Real Estate Value Prediction: An Instance-Transfer Learning approach, July 2016 link
  • Stijn Hoogervorst Inferring Demographics of Website Visitors with Supervised Learning, Adversitement BV, July 2016
  • Fangjing Wu Intelligent strategies to learn and recognise lifestyle patterns, (IMEC, supervised together with dr. Giuseppina Schiavone), June 2016
  • Simon Nouwens Hyperlink Perfume: Helping users with different goals to find the right content (MastersPortal.eu, supervised together with dr. Martijn Willemsen), May 2016
  • Xu Wang Deep reinforcement learning: case study with standard RL testing domains, (Philips Research, supervised together with dr. Vlado Menkovski), January 2016 link
  • Chung-Kit Lee Burglary Prediction Model, August 2016
  • Hilda F. Bernard Enhanced Sleepiness Prediction with Improved Algorithm Selection and Hyperparameter optimization, August 2016
  • Mikhail Evchenko Frugal Learning: Applying Machine Learning with Minimal Resources, August 2016
  • Kris van Tienhoven Gamification for OpenML, July 2016

Publicly available thesis reports are available through TU/e Library website