Picture of Thomas at the Bendery Fortress.

I am a PhD student at the Department of Computer and Systems Sciences at Stockholm University. The focus of my research is privacy-preserving techniques in natural language processing. My PhD project is funded primarily by the DataLEASH project and I am supervised by Professor Hercules Dalianis and Professor Aron Henriksson.

I have a MSc in computer science and engineering (civ.ing. i datateknik) from KTH Royal Institute of Technology. I worked in the tech industry as an IT consultant before starting my PhD, primarily as a back-end developer and data engineer.

I am currently on a research visit to Chile at the CMM - Centro Modelamiento Matemático in Santiago where I am mentored by Professor Jocelyn Dunstan.

Publications

End-to-End Pseudonymization of Fine-Tuned Clinical BERT Models

Thomas Vakili, Aron Henriksson & Hercules Dalianis

Pre-print under review at BMC Medical Informatics and Decision Making

Using Membership Inference Attacks to Evaluate Privacy-Preserving Language Modeling Fails for Pseudonymizing Data

Thomas Vakili & Hercules Dalianis

In Proceedings of the 24th Nordic Conference on Computational Linguistics (NoDaLiDa 2023)

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

Alexander Dolk, Hjalmar Davidsen, Hercules Dalianis & Thomas Vakili

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

Thomas Vakili, Anastasios Lamproudis, Aron Henriksson & Hercules Dalianis

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

Olle Bridal, Thomas Vakili & Marina Santini

In Proceedings of the Legal and Ethical Issues Workshop @ LREC2022

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

Oskar Jerdhaf, Marina Santini, Peter Lundberg, Tomas Bjerner, Yosef Al-Abasse, Arne Jönsson & Thomas Vakili

In Proceedings of the TERM21 Workshop @ LREC 2022

Utility Preservation of Clinical Text After De-Identification

Thomas Vakili & Hercules Dalianis

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

Thomas Vakili & Hercules Dalianis

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

Thomas Vakili

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

Thomas Vakili

Publications

End-to-End Pseudonymization of Fine-Tuned Clinical BERT Models

Using Membership Inference Attacks to Evaluate Privacy-Preserving Language Modeling Fails for Pseudonymizing Data

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

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

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

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

Utility Preservation of Clinical Text After De-Identification

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

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

Theses

Attacking and Defending the Privacy of Clinical Language Models

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

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

Teaching

Interests & Contact