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Dr. Joeran Beel

Ussher Assistant Professor (Computer Science)

 


Dr Joeran Beel is a tenure-track Ussher Assistant Professor in Intelligent Systems at the School of Computer Science and Statistics at Trinity College Dublin. He is also affiliated with the ADAPT Centre, an interdisciplinary research centre that closely cooperates with industry partners including Google, Deutsche Bank, Huawei, and Novartis. Joeran is further a Visiting Professor at the National Institute of Informatics in Tokyo, where he also completed his postdoctoral research. Joeran obtained a PhD in Computer Science from the Otto-von-Guericke University Magdeburg. During his PhD studies, he completed three research visits at the University of California, Berkeley and one at the University of Cyprus. Joeran has industry experience as a product manager at HRS.de / HRS Holidays. Joeran"s research focuses on machine learning, text mining, natural language processing, the blockchain and other technologies, in areas including recommender systems, search engines, news analysis, plagiarism detection, document engineering, and machine translation. Domains he is particularly interested in include digital libraries & digital humanities, eHealth, tourism, law, fintech, and mobility. Joeran published more than 60 peer-reviewed publications that have received over 1,500 citations. He acts as a reviewer for SIGIR, ECIR, RecSys, UMAP, ACM TiiS, and JASIST and he is serving as general co-chair of the upcoming 26th Irish Conference on Artificial Intelligence and Cognitive Science. He acquired more than 1 million Euro in funding for his research, prototype development, and two business start-ups, which both received several awards at business plan competitions such as start2grow and BPW. Joeran is currently preparing to spin out his third business start-up, this time in the field of recommender systems and machine learning. Please visit https://www.scss.tcd.ie/joeran.beel/ for more details
  ARTIFICIAL INTELLIGENCE   Bibliometrics   Bitcoin   Blockchain   computer-assisted language learning   Cross-Language Information Retrieval   Digital Humanities   Digital Libraries   FinTech   INFORMATION EXTRACTION   INFORMATION-RETRIEVAL   MACHINE LEARNING   Natural Language Processing   Personalisation   Personalisation and User-Centric Adaptivity   Personalised Information Retrieval   Plagiarism Detection   Recommender Systems   Scientometrics   Text Mining   TOURISM   User Modeling
 Darwin & Goliath: Meta-Learning Recommendations As-a-Service
 Domain-Independent Semantic Annotation of the Text
 SciPlore
 Mr. DLib and Recommender System Reproducibility
 Docear: Literature Management & Mind-Mapping Based User Modelling

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Details Date
Scientific advisor on the board of iris.ai 2018
Advisor on the board of Originstamp 2016
Language Skill Reading Skill Writing Skill Speaking
English Fluent Fluent Fluent
German Fluent Fluent Fluent
Collier M. and Beel J., EMANN: A Novel Extended-Memory-Augmented Neural Network for Machine Translation, ECIR, 2019, Conference Paper, SUBMITTED
Andrew Collins, Dominika Tkaczyk, Akiko Aizawa, and Joeran Beel, Position Bias in Recommender Systems for Digital Libraries, iConference , 2018, pp335-344 , Conference Paper, PUBLISHED  DOI
Dominika Tkaczyk, Andrew Collins, Paraic Sheridan and Joeran Beel, Machine Learning vs. Rules and Out-of-the-Box vs. Retrained: An Evaluation of Open-Source Bibliographic Reference and Citation Parsers, ACM Joint Conference on Digital Libraries (JCDL), 2018, pp99-108 , Conference Paper, PUBLISHED  DOI
Mark Collier and Joeran Beel, Implementing Neural Turing Machines, International Conference on Artificial Neural Networks, 2018-10-05, 2018, pp10-18 , Conference Paper, PUBLISHED  DOI
Andrew Collins, Dominika Tkaczyk, and Joeran Beel, A Novel Approach to Recommendation Algorithm Selection using Meta-Learning, 26th Irish Conference on Artificial Intelligence and Cognitive Science (AICS), 2018, pp162 - 173, Conference Paper, PUBLISHED
Mark Collier and Joeran Beel, An Empirical Comparison of Syllabuses for Curriculum Learning, 26th Irish Conference on Artificial Intelligence and Cognitive Science (AICS), 2018, pp150 - 161, Conference Paper, PUBLISHED
Joeran Beel, Andrew Collins, and Akiko Aizawa, The Architecture of Mr. DLib's Scientific Recommender-System API, 26th Irish Conference on Artificial Intelligence and Cognitive Science (AICS), Dublin, 2018, pp78 - 89, Conference Paper, PUBLISHED
Dominika Tkaczyk, Rohit Gupta, Riccardo Cinti and Joeran Beel, ParsRec: A Novel Meta-Learning Approach to Recommending Bibliographic Reference Parsers, 26th Irish Conference on Artificial Intelligence and Cognitive Science (AICS), 2018, pp162 - 173, Conference Paper, PUBLISHED
Dominika Tkaczyk, Andrew Collins and Joeran Beel, Who Did What? Identifying Author Contributions in Biomedical Publications using Naïve Bayes, ACM Joint Conference on Digital Libraries (JCDL), 2018, pp387-388 , Poster, PUBLISHED  DOI
Dominika Tkaczyk, Paraic Sheridan, Joeran Beel, ParsRec: A Meta-Learning Recommender System for Bibliographic Reference Parsing Tools, 12th ACM Conference on Recommender Systems, 2018, pp101 - 102, Poster, PUBLISHED
  

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Joeran Beel, Please visit my Google Scholar profile for a complete list of publications, https://scholar.google.de/citations?user=jyXACVcAAAAJ&hl=en, 2020, Journal Article, SUBMITTED
Rob Brennan, Joeran Beel, Ruth Byrne and Jeremy Debattista, Preface: The 26th AIAI Irish Conference on Artificial Intelligence and Cognitive Science (AICS 2018), 26th Irish Conference on Artificial Intelligence and Cognitive Science (AICS, 2018, pp1 - 7, Conference Paper, PUBLISHED
Joeran Beel, Darwin & Goliath: Micro & Macro Recommendations as-a-Service, Machine Learning Meetup Dublin, Dublin, 2018-04, 2018, Invited Talk, PRESENTED
Joeran Beel, Reference Parsing, Author Role Extraction, and Micro Recommendations, NII Weekly Seminar, Media Devision, Tokyo, 2018-03-30, 2018, Invited Talk, PUBLISHED
Joeran Beel, The Potential of Meta Recommender-Systems at Macro- and Micro Level, Machine Learning Dublin Meetup, Ireland, Dublin, 2018, Invited Talk, PUBLISHED
Joeran Beel, Machine Learning und die Bibliothek - Chancen und Grenzen, 18. BVB-Verbundkonferenz, Weiden, Germany, 2018, Invited Talk, PRESENTED
Joeran Beel, Real-World Recommender Systems for Academia The Pain and Gain in Building, Operating and Researching them, UCD Recommender System Seminar, Dublin, 2017-11-21, 2017, Invited Talk, PRESENTED
Joeran Beel, My Life as a PhD Student and Researcher, Research Methods Seminar, Dublin, 2017-10-18, 2017, School of Computer Science, TCD, Invited Talk, PRESENTED
Joeran Beel, Keynote: Real-World Recommender Systems for Academia: The Pain and Gain in Building, Operating, and Researching them, BIR Workshop, co-located with ECIR, UK, 2017, Invited Talk, PRESENTED
Joeran Beel, Virtual Citation Proximity (VCP): Calculating Co-Citation-Proximity-Based Document Relatedness for Uncited Documents with Machine Learning, 2017, Working Paper, PUBLISHED

  

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Award Date
Best-paper award for the paper "Implementing Neural Turing Machines" at the 27th International Conference on Artificial Neural Networks. 7th of October 2018
Best-Reviewer Nominee at 12th ACM Conference on Recommender Systems 5th of October 2018
5th prize in B-P-W business plan contest 2013
Award for exceptional achievements in the field of technology by the Heinz and Gisela Friederichs Foundation 2002
2nd winner at Jugend-forscht, Germany's national wide research contest 2002
Honoring for outstanding research work by German's Chancellor Gerhard Schröder 2002
4th prize in nationwide business plan contest start2grow 2003
4th winner of the business plan contest futureSAX in Saxony 2003
2nd prize in nationwide business plan contest B-P-W 2003
1st / prize in ego.BUSINESS business plan contest 2012
Best Master's graduate of the computer science department 2008
Award for an outstanding microelectronic equipment development by the Association of German Electrical Engineers 2001
Recommender Systems, User Modelling, Information Retrieval, Machine Learning, Artificial Intelligence, Information Extraction, Natural Language Processing, Text Mining, Citation Analysis, Bibliometrics, Altmetrics, Scientometrics, Plagiarism Detection, Blockchain, Digital Libraries, Digital Humanities, Finance (FinTech), Legal, Tourism, Medical