Thomas Vakili

PhD student at Stockholm University

Picture of Thomas at the Bendery Fortress.

Thomas Vakili is a PhD student at the Department of Computer and Systems Sciences at Stockholm University. The focus of his research is Natural Language Processing. He is part of the DataLEASH project and his supervisor is Professor Hercules Dalianis.

He has a M.Sc. in computer science and engineering ( i datateknik) from KTH Royal Institute of Technology. He also has industry experience from working as a IT consultant, primarily as a back-end developer and data engineer.


Evaluation of LIME and SHAP in Explaining Automatic ICD-10 Classifications of Swedish Gastrointestinal Discharge Summaries

Dolk, A., Davidsen, H., Dalianis, H., & Vakili, T.

In Proceedings of the 18th Scandinavian Conference on Health Informatics (SHI 2022)

Downstream Task Performance of BERT Models Pre-Trained Using Automatically De-Identified Clinical Data

Vakili, T., Lamproudis, A., Henriksson, A. & Dalianis, H.

In Proceedings of the 13th Conference on Language Resources and Evaluation (LREC 2022)

Cross-Clinic De-Identification of Swedish Electronic Health Records: Nuances and Caveats

Bridal, O., Vakili, T. & Santini, M.

In Proceedings of the Legal and Ethical issues Workshop @ LREC2022

Evaluating Pre-Trained Language Models for Focused Terminology Extraction from Swedish Medical Records

Jerdhaf, O., Santini, M., Lundberg, P., Bjerner, T., Al-Abasse, Y., J├Ânsson, A. & Vakili, T.

In Proceedings of the TERM21 Workshop @ LREC 2022

Utility Preservation of Clinical Text After De-Identification

Vakili, T. & Dalianis, H.

In Proceedings of the 21st Workshop on Biomedical Language Processing @ ACL 2022

Are Clinical BERT Models Privacy Preserving? The Difficulty of Extracting Patient-Condition Associations

Vakili, T. & Dalianis, H.

In Proceedings of the AAAI 2021 Fall Symposium on Human Partnership with Medical AI: Design, Operationalization, and Ethics (AAAI-HUMAN 2021)

A Method for the Assisted Translation of QA Datasets Using Multilingual Sentence Embeddings

Vakili, T.

An extended abstract of my master's thesis presented at the 2020 workshop on RESOURCEs and representations For Under-resourced Languages and domains.

A Comparison of Clustering the Swedish Political Twittersphere Based on Social Interactions and on Tweet Content

Vakili, T.

Bachelor's thesis at KTH (2016).

Interests & Contact

I am currently working on to what extent masked language models (such as BERT) leak sensitive information about their training data. Since BERT-style models are very common, especially for lesser-resourced languages, this could have significant privacy implications.

Don't hesitate to contact me if you are interested in collaborating!