Shailza Jolly is a second-year Ph.D. student at TU Kaiserslautern (TUK) in Germany and works as a research assistant at the German Research Center for Artificial Intelligence (DFKI) in the research department Smart Data & Knowledge Services.
There she is investigating how it is possible to have human-like conversations with chatbots if they are trained with only a handful of examples. Behind this is the relevant question of whether small companies and startups can build robust and interpretable NLP systems without extensive computational infrastructure and large data sets.
Shailza is primarily interested in developing machine learning methods for building low-resource natural language generation and understanding systems. Presently, she is working on scoring-based NLG methods in collaboration with Prof. Mou from the University of Alberta, Canada. Her other research interests include vision and language systems, interpretability, and conversational AI. She completed her master's in computer science from TU Kaiserslautern and spent a semester abroad at Kyushu University in Japan, where her work "How do Convolution Neural Networks Learn Design?" won the best student paper award at ICPR 2018. She has published her works at venues like EMNLP and COLING. During her graduate studies, she interned at SAP Machine Learning Research (Berlin, Germany) and Amazon Alexa (Aachen, Germany). Recently, she has been awarded an STSM Grant under Multi3Generation COST action to conduct research for generating fact-checking explanations in low-resource settings in collaboration with Prof. Augenstein at the University of Copenhagen, Denmark.
KI (AI) Camp 2021
With the KI-Camp, a transdisciplinary research convention on the topic of Artificial Intelligence, the German Informatics Society e.V. (GI) and the Federal Ministry of Education and Research (BMBF) would like to bring together brilliant scientists under the age of 35 and renowned researchers. The aim is to bring together brilliant scientists under 35 years of age and renowned researchers.
The aim of the AI Newcomer Award is to highlight new talents who have already achieved outstanding success in the various fields of research and activity in the field of AI and who can be expected to help shape AI research.
Voting is possible with up to 10 votes until March 07, 2021: https://kicamp.org/en/ai-newcomers