Farrokh Mehryary
PhD in Computer Science
farmeh@utu.fi Office: 451A ORCID identifier: https://orcid.org/0000-0002-5555-2828 |
Natural language processing (NLP), text mining, Information Extraction (IE), Bioinformatics, protein function prediction, deep learning, machine learning
Farrokh is a senior researcher at the Department of Computing, University of Turku, Finland and for the last 11 years, he has been part of the TurkuNLP group, developing different NLP and text mining pipelines for the biomedical domain, as well as taking part in various bioinformatics projects such as protein function prediction.
Farrokh has a doctoral degree certificate in Computer Science (University of Turku) and two master’s degree certificates, one in Computer Science (Master’s Degree Programme in Bioinformatics, University of Turku), and one in Computer Software Engineering (Iran University of Science and Technology).
With a strong track record in publication, achieving high ranks in several international text mining and machine learning competitions, and achieving the state-of-the-art results on several important datasets, Farrokh has been specializing in deep learning-based methods for Biomedical Natural Language Processing (BioNLP) and text mining. His research has focused on low-resource setups, where minimal training data is available.
During 2021, Farrokh has worked as an AI scientist for Silo AI, developing text mining systems for clients, and as a researcher for AI academy, helping in the development of Massive Open Online Courses (MOOC). In 2022, Farrokh received his PhD degree certificate in Computer Science from University of Turku, with his thesis on ‘Optimizing Text Mining Methods for Biomedical Natural Language Processing’. Currently, Farrokh has a senior researcher position in TurkuNLP group, working on biomedical natural language processing and text mining.
I have been the responsible teacher for the course Algorithms in Bioinformatics, University of Turku, 2015-2020. I have also helped in teaching other NLP courses including Text mining and Deep Learning in Language Technology at the Department of Computing, University of Turku.
- Overview of DrugProt task at BioCreative VII: data and methods for large-scale text mining and knowledge graph generation of heterogenous chemical-protein relations (2023)
- Database: The Journal of Biological Databases and Curation
(Refereed journal article or data article (A1)) - The STRING database in 2023: protein-protein association networks and functional enrichment analyses for any sequenced genome of interest (2023)
- Nucleic Acids Research
(Refereed journal article or data article (A1)) - Neural Network and Random Forest Models in Protein Function Prediction (2022)
- IEEE/ACM Transactions on Computational Biology and Bioinformatics
(Refereed journal article or data article (A1)) - Optimizing text mining methods for improving biomedical natural language processing (2022) Mehryary Farrokh
(Doctoral dissertation (article) (G5)) - Overview of DrugProt BioCreative VII track: quality evaluation and large scale text mining of drug-gene/protein relations (2021) Proceedings of the BioCreative VII Challenge Evaluation Workshop Miranda Antonio, Mehryary Farrokh, Luoma Jouni, Pyysalo Sampo, Valencia Alfonso, Krallinger Martin
(Unrefereed conference proceedings (B3)) - Entity-pair embeddings for improving relation extraction in the biomedical domain (2020)
- European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning
(Refereed article in conference proceedings (A4)) - The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens (2019)
- Genome Biology
(Refereed journal article or data article (A1)) - Combining support vector machines and LSTM networks for chemical-protein relation extraction (2018) Proceedings of the BioCreative VI Workshop Farrokh Mehryary, Jari Björne, Tapio Salakoski, Filip Ginter
(Refereed article in conference proceedings (A4)) - Data and systems for medication-related text classification and concept normalization from Twitter: insights from the Social Media Mining for Health (SMM4H)-2017 shared task (2018)
- Journal of the American Medical Informatics Association
(Refereed journal article or data article (A1)) - Potent pairing: ensemble of long short-term memory networks and support vector machine for chemical-protein relation extraction (2018)
- Database: The Journal of Biological Databases and Curation
(Refereed journal article or data article (A1)) - TurkuNLP Entry for Interactive Bio-ID Assignment (2018) Proceedings of the BioCreative VI Workshop Suwisa Kaewphan, Farrokh Mehryary, Kai Hakala, Tapio Salakoski, Filip Ginter
(Refereed article in conference proceedings (A4)) - Detecting mentions of pain and acute confusion in Finnish clinical text (2017) SIGBioMed Workshop on Biomedical Natural Language: Proceedings of the 16th BioNLP Workshop Hans Moen, Kai Hakala, Farrokh Mehryary, Laura-Maria Peltonen, Tapio Salakoski, Filip Ginter, Sanna Salanterä
(Refereed article in conference proceedings (A4)) - End-to-End System for Bacteria Habitat Extraction (2017) SIGBioMed Workshop on Biomedical Natural Language: Proceedings of the 16th BioNLP Workshop Farrokh Mehryary, Kai Hakala, Suwisa Kaewphan, Jari Björne, Tapio Salakoski, Filip Ginter
(Refereed article in conference proceedings (A4)) - Ensemble of Convolutional Neural Networks for Medicine Intake Recognition in Twitter (2017)
- CEUR Workshop Proceedings
(Refereed article in conference proceedings (A4)) - An expanded evaluation of protein function prediction methods shows an improvement in accuracy (2016)
- Genome Biology
(Refereed journal article or data article (A1)) - Deep Learning With Minimal Training Data: TurkuNLP Entry in the BioNLP Shared Task 2016 (2016) Proceedings of the 4th BioNLP Shared Task Workshop Farrokh Mehryary, Jari Bjorne, Sampo Pyysalo, Tapio Salakoski, Filip Ginter
(Refereed article in conference proceedings (A4)) - Filtering large-scale event collections using a combination of supervised and unsupervised learning for event trigger classification (2016)
- Journal of Biomedical Semantics
(Article or data-article in scientific journal (B1)) - Eliminating Incorrect Events from Large‐Scale Event Networks by Trigger Word Clustering and Pruning (2014) Proceedings of the 6th International Symposium on Semantic Mining in Biomedicine (SMBM 2014) Farrokh Mehryary, Suwisa Kaewphan, Kai Hakala, Filip Ginter
(Refereed article in conference proceedings (A4)) - Hypothesis Generation in Large-Scale Event Networks (2013) Proceedings of the 5th International Symposium on Languages in Biology and Medicine (LBM'13) Hakala Kai, Mehryary Farrokh, Kaewphan Suwisa, Ginter Filip
(Refereed article in conference proceedings (A4))