Assistant Professor in Machine Learning 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 Large Language Models and Computer Vision. She is also working part-time as an AI Scientist at Combient Mix AB, Stockholm (previously at Silo AI).
Email: contact@ektavats.se
Doctoral student, 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.
Masters thesis student with Ekta Vats as her supervisor. Her thesis focuses on investigating vision-based deep learning approaches for human fall detection, with case study on elderly patient’s fall detection. Ola is a second-year master’s student specializing in data science, specifically the machine learning and statistics track.
PhD student in Machine Learning and Computer Vision (under recruitment). Supervisor: Ekta Vats.
We are recruiting a motivated PhD student to join us in conducting fundamental machine learning research and developing principled foundations of vision-language models, with opportunities to validate the methods on challenging real-world problems involving computer vision.
(Advertisement, deadline Aug. 12th)
PostDoc in Deep Learning with a focus on Vision-Language Models (under recruitment). Supervisor: Ekta Vats.
(Advertisement, deadline May 14th [closed])
Previous Members
- 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.