Ekta Vats

Assistant Professor in Machine Learning, Docent 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 current projects focus on Multimodal learning, Vision-Language(-Action) Models and Multi-spectral imaging for cultural heritage collections to uncover hidden texts in old manuscripts. She teaches courses: Large Language Models and societal consequences of AI (also course responsible) and Deep Learning at Uppsala University. She is a member of WASP–Diversity and Inclusion Group. She previously worked as an AI Scientist at Silo AI (now AMD Silo AI), 2021–2024.

Email: contact@ektavats.se

Robin Hollifeldt

Doctoral student (Sept. 2024–), supervised by Asst. Prof. Ekta Vats and Prof. Thomas Schön.

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. Her PhD studies is funded by Kjell och Märta Beijers Stiftelsen and is affiliated with Wallenberg AI, Autonomous Systems and Software Program (WASP).

Tianru Zhang

PostDoc (March 2025–) Topic: Vision-Language Models and Multimodal Learning. PI: Ekta Vats.

Tianru holds a PhD in Scientific Computing from Uppsala University. During his PhD, he worked on hierarchical data management using machine learning. His research interests include representation learning, reinforcement learning, and data management. 

Jessica Ström

MSc Thesis (Jan 2025–) Topic: Multispectral handwritten text and palimpsests modelling. 

The project aims to uncover the palimpsests and obscured texts hidden beneath damaged manuscripts. To achieve this, the aim is to develop methods for palimpsest text separation and restoration using deep neural networks. The project also investigates handwritten text recognition and language modeling to further enhance the quality of text transcriptions.

Doctoral Student Co-supervision

  • Hong Wang (Sept. 2024–). Thesis topic: Large language models-powered social robots in cybersecurity applications.
  • Raphaela Heil (2018–2023). Thesis title: Document Image Processing for Handwritten Stenography Recognition – Deep Learning-based Transliteration of Astrid Lindgren’s Stenographic Manuscripts. She is now a Researcher at Stockholm University. She previously worked as a Software Engineer (Text Recognition)Folkrörelsearkivet för Uppsala län (Labour’s Memory Project).

M.Sc. Student Supervision

  • 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 ML Engineer at Scaleout.
  • 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.

Subject Reviewer