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 Models, video-LLMs 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 Video LLMs. 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 video-LLMs. 

Doctoral Student Co-Supervision

  • Hong Wang (Sept. 2024–). Thesis topic: Large language models-powered social robots in cybersecurity applications. Main supervisor: Prof. Ginevra Castellano
  • Wenyi Lian (June 2025–). Thesis topic: Sequential approaches for scalable Bayesian inference and applications. Main supervisor: Prof. Thomas Schön
  • Raphaela Heil (2018–2023). Thesis title: Document Image Processing for Handwritten Stenography Recognition– Deep Learning-based Transliteration of Astrid Lindgren’s Stenographic Manuscripts. Main supervisor: Prof. Anders Hast. 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).

Guest Researcher

  • Anna Starynska (May 2025), from Rochester Institute of Technology and Early Manuscripts Electronic Library. Topic: Unveiling Hidden Texts: Palimpsest Restoration via Deep Generative Architectures. Funded under Equal Opportunity Call for Visiting Researchers, Department of IT, Uppsala University.

M.Sc. Student Supervision

  • Hugo Eidmann, Masters thesis topic: Probabilistic Query-Aware Keyframe Selection for Efficient Video Understanding with Multimodal LLMs, UU, 2026.
  • Jakob Schmidt, Masters thesis topic: LLM-enabled simulated patient–pharmacist conversations to improve communication training, UU, 2026.
  • Jessica Ström, Masters thesis: Generative Handwritten Text Separation and Recognition for Palimpsests Modeling, UU, 2025.
  • 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.

B.Sc. Student Supervision

  • Elin Matsson, Ivar Hammarberg, Pontus Ahlberg and Isac Persson, Investigating Fréchet Inception Distance for Evaluating AI-Reconstructed Handwritings, UU, 2026.

Subject Reviewer