Machine Learning Research Scientist
NEC Labs Europe
Heidelberg, Germany
I am a senior research scientist in the Machine Learning group of NEC Labs Europe. I work on natural language processing (NLP), graph structured data and making machine-learnt models more interpretable.
From 2014-2018 I was graduate research assistant and PhD student at the Statistical NLP group at the Heidelberg University, supervised by Prof. Dr. Stefan Riezler. During my PhD I worked on Natural Language Processing (NLP) problems, such as machine translation and question-answering, and I explored how reinforcement learning can be applied to these problems.
Research Interests
- Machine Learning, particularly for graph-structured data and using reinforcement learning
- Explainable AI: AI should enrich our lives and for this we should work on interpretable, trustworthy and inclusive AI
- Natural Language Processing, particularly Question-Answering and Information Extraction
Recently, colleagues and I have developed a method to explain the prediction of neural matrix factorization models, which are used for knowledge base completion and recommender systems. You can check out a related talk here:
News
2021
- Outstanding Paper Award at AKBC, thanks to my co-authors for all the great discussions and work!
- November 18: I will give a half-day workshop on scientific communication for a PhD course at the University of Copenhagen
- October 8: Invited talk at the Explaining Graph-Based Machine Learning Workshop, co-located with AKBC
- August 6: Invited talk at the 5th Workshop on Structured Prediction for NLP, co-located with ACL 21
- April 8: Talk at Python for ML and AI Summit
- February 9: GCLR Workshop Presentation of Gradient Rollback
- February 4 & 5: AAAI 21 Presentation of our paper Explaining Neural Matrix Factorization with Gradient Rollback
- January 19: [YouTube Video] Talk at the Zurich NLP Meetup on “From Text & Graphs to Explainable New Knowledge”
- Area Chair for EMNLP
- Reviewer for: NeurIPS, ACL, NAACL, RepL4NLP, DeeLIO