Toqeer Ehsan is a Postdoctoral Researcher in the Quantitative Science and Technology Studies team at VTT Technical Research Centre of Finland. He holds a doctoral degree in Computer Science, with a strong focus in Artificial Intelligence, and has over a decade of academic and research experience. His research primarily focuses on the evaluation and fine-tuning of Large Language Models (LLMs) and Generative AI, as well as the development of systems for low-resource languages in areas such as Information Extraction, Sentiment Analysis, Machine Translation, and Code-mixed Text Analysis. His research interests also include cross-lingual data augmentation techniques to address challenges related to the scarcity of annotated data.

At VTT, he is particularly engaged with emerging challenges related to the safe, trustworthy, and effective deployment of LLMs, including their fine-tuning, persona alignment, and systematic evaluation across multilingual and low-resource contexts. His earlier work at MBZUAI and the University of Gujrat established his expertise in information extraction, machine learning, syntactic parsing, treebank development, and low-resource NLP, while his international collaborations including with University of Konstanz (DAAD) and partners in Europe, have advanced neural parsing and benchmarking methods. Beyond research, he has contributed extensively as a reviewer and program committee member for international conferences (COLING, LREC, NAACL workshops), supervised graduate theses in deep learning and NLP, and received recognition such as the DAAD scholarship and best paper awards. Together, his work bridges foundational AI evaluation with applied innovation in multilingual and low-resource NLP, positioning him to contribute to both academic advancement and responsible AI deployment.