Ekta Vats
Associate senior lecturer/Assistant Professor at Department of Information Technology, Division of Systems and Control
- Email:
- ekta.vats[AT-sign]it.uu.se
- Visiting address:
- hus 10, Lägerhyddsvägen 1
- Postal address:
- Box 337
751 05 UPPSALA
Visiting researcher at Department of Information Technology, Vi3; Image Analysis
- Visiting address:
- hus 10, Lägerhyddsvägen 1
- Postal address:
- Box 337
751 05 UPPSALA
Short presentation
I am a Researcher in AI and Deep Learning, with specialisation in text recognition, NLP and document image analysis. My research is focused on document image analysis, Handwritten Text Recognition, Optical Character Recognition, data science and machine learning.
Keywords: image analysis digital humanities data science machine learning human action recognition handwritten text recognition artifical intelligence ocr
I am a Researcher in AI and Deep Learning and I am interested in investigating how research-oriented AI solutions can be adopted in real-world applications in Digital Humanities.
By training, I am a PhD in Computer Vision, and work as an AI Scientist at Silo AI Stockholm, and prior to that, as a Research Engineer at the Centre for Digital Humanities and a Researcher/Postdoc at the Center for Image Analysis at Uppsala University. I have also worked as a Computer Scientist AI/HTR at Folkrörelsearkivet for Uppsala Län on the Labour’s Memory project, which aimed at making large scale material from The Swedish Trade Union Confederation-sphere (from the 1880s until today) available and accessible.
Research Aim: Build innovative data‑driven AI solutions using expertise in Text recognition (OCR, HTR), Document Image analysis, Computer Vision, AI and Machine Learning. My background lies in both traditional image processing/computer vision methods (Hidden Markov Models, keypoint-based word spotting, etc.) and also the current state-of-the-art Recurrent Neural Network (RNN) and attention-based deep learning approaches.
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