I am a PhD student in the Machine Reading Group at University College London, supervised by Sebastian Riedel, Pontus Stenetorp, and John Shawe-Taylor.

Research Interests

I work in the intersection of Machine Learning and Natural Language Processing, and specifically on Machine Comprehension and Knowledge Base Inference. My goal is to build agents that read, comprehend, and reason with factual texts.

Recently I created two multi-step reading comprehension datasets based on Wikipedia and PubMed. Together with the Allen Institute for Artificial Intelligence, I also gathered a dataset of 13K+ Questions for Science QA.

Previously I looked into different embedding methods for Inference in Knowledge Bases, like Complex Vector Embeddings and Factorization Machines.

I am generally interested in understanding theoretical bridges between different Machine Learning models, and in how language and intelligence are interrelated.

I co-organise the South England NLP meetup.

Publications

Google Scholar Profile
Jack the Reader - A Machine Reading Framework

Dirk Weissenborn, Pasquale Minervini, Tim Dettmers, Isabelle Augenstein, Johannes Welbl, Tim Rocktäschel, Matko Bošnjak, Jeff Mitchell, Thomas Demeester, Pontus Stenetorp, Sebastian Riedel - ACL, 2018 (demo)
Constructing Datasets for Multi-Hop Reading Comprehension Across Documents

Johannes Welbl, Pontus Stenetorp, Sebastian Riedel - TACL, 2018
Frustratingly Short Attention Spans in Neural Language Modeling

Michał Daniluk, Tim Rocktäschel, Johannes Welbl, Sebastian Riedel - ICLR, 2017
Crowdsourcing Multiple Choice Science Questions

Johannes Welbl, Nelson F. Liu, Matt Gardner - WNUT, 2017
Knowledge Graph Completion via Complex Tensor Factorization

Théo Trouillon, Christopher R Dance, Éric Gaussier, Johannes Welbl, Sebastian Riedel, Guillaume Bouchard - JMLR, 2017
A Factorization Machine Framework for Testing Bigram Embeddings in Knowledgebase Completion

Johannes Welbl, Guillaume Bouchard, Sebastian Riedel - AKBC, 2016
Neural Random Forests

Gérard Biau, Erwan Scornet, Johannes Welbl - Sankhya A, 2016
Complex Embeddings for Simple Link Prediction

Théo Trouillon, Johannes Welbl, Sebastian Riedel, Éric Gaussier, Guillaume Bouchard - ICML, 2016
Casting Random Forests as Artificial Neural Networks (and Profiting from it)

Johannes Welbl -- GCPR, 2014
Event Detection by Feature Unpredictability in Phase-Contrast Videos of Cell Cultures

Melih Kandemir, Jose C Rubio, Ute Schmidt, Christian Wojek, Johannes Welbl, Björn Ommer, Fred A Hamprecht -- MICCAI, 2014