Assistant Professor in Machine Learning, Docent (Associate Professor) in Computerised Image Processing at the Division of Systems and Control, Department of IT, Uppsala University and a Beijer Researcher at The Beijer Laboratory for Artificial Intelligence Research. Her research focuses on developing AI and machine learning methods to extract knowledge from a variety of data (documents, images, videos), and to efficiently deliver it to the general public. Her current projects focus on Vision-Language Models and Multi-spectral imaging for cultural heritage collections to uncover hidden texts in old manuscripts. She teaches the course: Large Language Models and societal consequences of AI at Uppsala University.
Email: contact@ektavats.se
Doctoral student (Sept. 2024-), supervised by Asst. Prof. Ekta Vats (main supervisor) and Prof. Thomas Schön (co-supervisor).
Thesis topic: Multimodal deep learning and vision-language models.
Robin holds a MSc in Mathematics from Uppsala University and a BSc in Mathematics from Lund University, Sweden.
Affiliated Member, previous Doctoral student (2018-2023), co-supervised by Ekta Vats at the Department of IT, Uppsala University. Raphaela defended her thesis on 4 Oct. 2023.
Thesis title: Document Image Processing for Handwritten Stenography Recognition – Deep Learning-based Transliteration of Astrid Lindgren’s Stenographic Manuscripts. She now works as a Software Engineer (Text Recognition)Folkrörelsearkivet för Uppsala län, collaborating with us on the Labour’s Memory Project.
Incoming PostDoc in Deep Learning with a focus on Vision-Language Models.
Supervisor: Ekta Vats.
Project start date: Nov. 2024.
Previous Members
- Ola Karrar, Masters thesis: Vision-based Deep Learning Approach for Human Fall Detection, UU, 2024.
- Till Grutschus, Technical University of Munich. Masters in Data Science Project: Human fall detection on untrimmed videos using large foundational video-understanding model, 2023.
- Emir Esenov, Masters in Data Science Project: Vision-based fall detection, UU, 2023.
- Alex Kangas, Masters in Data Science Project: Leveraging Generative AI Models for Handwritten Text Image Synthesis, UU, 2023.
- Vasiloius toumpanakis, Masters in Data Science Project: Leveraging Generative AI Models for Handwritten Text Image Synthesis, UU, 2023.
- Liam Tabibzadeh, Masters in Data Science Project: Leveraging Generative AI Models for Handwritten Text Image Synthesis, UU, 2023.
- Liang Cheng, Masters in Data Science Project: Uncovering the Handwritten Text in the Margins: End-to-end Handwritten Text Detection and Recognition, UU, 2022. Now PhD student at University of Oslo, Norway.
- Jonas Frankemölle, Masters in Data Science Project: Uncovering the Handwritten Text in the Margins: End-to-end Handwritten Text Detection and Recognition, UU, 2022. Now Research Engineer at CDHU.
- Adam Axelsson, Masters in Data Science Project: Uncovering the Handwritten Text in the Margins: End-to-end Handwritten Text Detection and Recognition, UU, 2022.
- Dmitrijs Kass, Masters in Data Science Project: AttentionHTR: Handwritten Text Recognition Based on Attention Encoder-Decoder Networks, UU, 2021. Now Machine Learning Engineer at Modulai, Stockholm.
- Charalampos Poulikidis Moutsanas, Masters in Data Science Project: Attention-based Handwritten Text Recognition, UU, 2021.
- Simon Leijon, Hampus Widén, Martin Sundberg, Petter Sigfridsson and Jonathan Kurén, Masters in Data Science Project: Document Image Binarization for Heavily Degraded Swedish Manuscripts, UU, 2021.