Multimodal Computing & Machine Intelligence

Prof. Dr. Christin Seifert

The MCMI research group headed by Prof. Dr. Christin Seifert focuses on the transfer of fundamental research in machine learning, information extraction, natural language processing and semantic technologies to applications in the medical domain, and to oncology in particular.

We address questions relevant, but not limited to understanding and transforming clinical documents, sensor data processing, predictive modelling, medical decision support, explaining decisions of complex machine learning models, and devising interpretable, yet accurate models to foster stakeholder acceptance and trust.

The MCMI research group is part of the Cancer Research Center Cologne Essen (CCCE), the Initiative Network of Excellence in Cancer Medicine NRW.

Contact

Girardethaus
Girardetstr. 2
House 2, 2nd floor
45131 Essen

Prof. Dr. Christin Seifert
Office

Projects

Recent Publications - see all...

  1. Stefan Haller, Adina Aldea, Christin Seifert, and Nicola Strisciuglio. Survey on Automated Short Answer Grading with Deep Learning: from Word Embeddings to Transformers. 2022. arXiv. [doi] [url]
    BibTeX
    @misc{Haller2022_preprints_short-answare-grading-survey,
      author = {Haller, Stefan and Aldea, Adina and Seifert, Christin and Strisciuglio, Nicola},
      title = {Survey on Automated Short Answer Grading with Deep Learning: from Word Embeddings to Transformers},
      year = {2022},
      copyright = {Creative Commons Attribution 4.0 International},
      doi = {10.48550/ARXIV.2204.03503},
      keywords = {Computation and Language (cs.CL), Artificial Intelligence (cs.AI), Machine Learning (cs.LG), FOS: Computer and information sciences},
      publisher = {arXiv},
      url = {https://arxiv.org/abs/2204.03503}
    }
    
  2. Van Bach Nguyen, Jörg Schlötterer, and Christin Seifert. Explaining Machine Learning Models in Natural Conversations: Towards a Conversational XAI Agent. 2022. arXiv. [doi] [url]
    BibTeX
    @misc{Nguyen2022_preprints_conversational-xai,
      author = {Nguyen, Van Bach and Schlötterer, Jörg and Seifert, Christin},
      title = {Explaining Machine Learning Models in Natural Conversations: Towards a Conversational XAI Agent},
      year = {2022},
      copyright = {Creative Commons Attribution Non Commercial No Derivatives 4.0 International},
      doi = {10.48550/ARXIV.2209.02552},
      keywords = {Artificial Intelligence (cs.AI), Computation and Language (cs.CL), FOS: Computer and information sciences},
      publisher = {arXiv},
      url = {https://arxiv.org/abs/2209.02552}
    }
    
  3. Meike Nauta, Jan Trienes, Shreyasi Pathak, Elisa Nguyen, Michelle Peters, Yasmin Schmitt, Jörg Schlötterer, Maurice van Keulen, and Christin Seifert. From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic Review on Evaluating Explainable AI. 2022. arXiv. [doi] [url]
    BibTeX
    @misc{Nauta2022_preprints_evaluating-xai,
      author = {Nauta, Meike and Trienes, Jan and Pathak, Shreyasi and Nguyen, Elisa and Peters, Michelle and Schmitt, Yasmin and Schlötterer, Jörg and van Keulen, Maurice and Seifert, Christin},
      title = {From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic Review on Evaluating Explainable AI},
      year = {2022},
      copyright = {arXiv.org perpetual, non-exclusive license},
      doi = {10.48550/ARXIV.2201.08164},
      keywords = {Artificial Intelligence (cs.AI), FOS: Computer and information sciences},
      publisher = {arXiv},
      url = {https://arxiv.org/abs/2201.08164}
    }
    
  4. Meike Nauta, Ricky Walsh, Adam Dubowski, and Christin Seifert. Uncovering and Correcting Shortcut Learning in Machine Learning Models for Skin Cancer Diagnosis. Diagnostics. 2022. [doi]
    BibTeX
    @article{nautaUncoveringCorrectingShortcut2022,
      title = {Uncovering and {{Correcting Shortcut Learning}} in {{Machine Learning Models}} for {{Skin Cancer Diagnosis}}},
      author = {Nauta, Meike and Walsh, Ricky and Dubowski, Adam and Seifert, Christin},
      year = {2022},
      journal = {Diagnostics},
      volume = {12},
      number = {1},
      issn = {2075-4418},
      doi = {10.3390/diagnostics12010040}
    }
    
  5. Van Bach Nguyen, Jan Trienes, Meike Nauta, Shreyasi Pathak, Paul Youssef, Sultan Imangaliyev, Jörg Schlötterer, and Christin Seifert. PPLM Revisited: Steering and Beaming a Lumbering Mammoth to Control Text Generation. ICLR Blog Track. 2022. [url]
    BibTeX
    @inproceedings{Nguyben2022_iclr-blog_pplmrevisiteds-mammoth,
      title = {{{PPLM}} Revisited: {{Steering}} and Beaming a Lumbering Mammoth to Control Text Generation},
      booktitle = {{{ICLR}} Blog Track},
      author = {Nguyen, Van Bach and Trienes, Jan and Nauta, Meike and Pathak, Shreyasi and Youssef, Paul and Imangaliyev, Sultan and Schl{\"o}tterer, J{\"o}rg and Seifert, Christin},
      year = {2022},
      url = {https://iclr-blog-track.github.io/2022/03/25/PPLM/}
    }
    

Team

Photo of Christin Seifert

Prof. Dr. Christin Seifert

christin.seifert@uni-due.de
Phone: +4920172377803
Interests: Machine Learning, Natural Language Processing, Explainable AI, and Medical Data Science

Head of Junior Research Group

Photo of Jörg Schlötterer

Dr. Jörg Schlötterer

joerg.schloetterer@uni-due.de
Interests: Multimodal & Representation Learning, Knowledge Extraction, Natural Language Processing, and Information Retrieval
Junior Research Group Knowledge Extraction & Integration

Administration

Photo of Andrea Tonk

Andrea Tonk

andrea.tonk@uk-essen.de
Phone: +4920172377825

Tech

Photo of Ryan Aydelott

Ryan Aydelott, Experimental/HPC Systems Specialist

ryan.aydelott@uk-essen.de

Researchers

Photo of Sultan Imangaliyev

Dr. Sultan Imangaliyev

sultan.imangaliyev@uni-due.de
Interests: deep learning on tabular data, explainable AI, biomarker selection, human microbiome, bioinformatics, systems biology, and computational biology

Research Assistants

Photo of Meike Nauta

M.Sc. Meike Nauta, Ph.D. Candidate

meike.nauta@uk-essen.de
Interests: Explainable AI and interpretable machine learning

Photo of Shreyasi Pathak

M.Sc. Shreyasi Pathak, Ph.D. Candidate

shreyasi.pathak@uk-essen.de
Interests: Explainable AI, Multimodal Deep Learning, and Clinical Decision Making (breast cancer diagnosis)

Photo of Jan Trienes

M.Sc. Jan Trienes, Ph.D. Candidate

jan.trienes@uni-due.de
Interests: Natural Language Processing and Information Retrieval

Photo of Paul Youssef

M.Sc. Paul Youssef, Ph.D. Candidate

paul.youssef@uni-due.de
Interests: Clinical Decision Making and Natural Language Processing

Photo of Osman Koras

M.Sc. Osman Koras, Ph.D. Candidate

osman.koras@uni-due.de
Interests: Natural Language Processing, Faithfulness in Natural Language Generation, Representation of Text Semantics and Machine Learning

Photo of Phuong Quynh Le

M.Sc. Phuong Quynh Le, Ph.D. Candidate

phuongquynh.le@uni-due.de
Interests: Explainable AI, Machine Learning

Photo of Meijie Li

M.Sc. Meijie Li, Ph.D. Candidate

meijie.li@uni-due.de

Photo of Van Bach Nguyen

M.Sc. Van Bach Nguyen, Ph.D. Candidate

vanbach.nguyen@uni-due.de
Interests: Natural Language Processing, Explainable AI, and Conversational Agents
Junior Research Group Knowledge Extraction & Integration