Sebastian Welter

Biography: Sebastian is the AI Lead Architect for DACH region at Accenture. He has years of experience with unstructured data analytics, human-machine interaction, machine learning, NLP and IT architecture. His day to day business is solving real world customer problems and transforming and digitalizing customer businesses. His recent focus is on ML platforms and human-machine interaction. In the past, Sebastian was IBM’s lead technical architect for Watson in DACH and is OpenGroup certified as Expert Solution Architect.

Lucia Specia

Biography: Lucia Specia is Professor of Natural Language Processing at Imperial College London, with part-time appointments at the University of Sheffield and Dublin City University. Her research focuses on data-driven approaches to language processing, with a particular interest in multimodal and multilingual context models and work at the intersection of language and vision. She is the recipient of the MultiMT ERC Starting Grant on Multimodal Machine Translation (2016-2021) and is also currently involved in research projects on in-browser machine translation and quality estimation.

Lewis Tunstall

Biography: Lewis is a Machine Learning Engineer in the open-source team at Hugging Face. He has several years experience building machine learning powered applications for startups and enterprises in the domains of natural language processing, topological data analysis, and time series. His current work focuses on developing tools for the NLP community and educating people on how to use them effectively.

Zenodia Charpy

Biography: Working many years hands-on as an in-house data scientist, an external deep-learning consultant , a cloud solution architect (on Azure) and now a deep learning solution architect at Nvidia. She has equipped herself with years of industrial experiences and practical tips & tricks learned from pitfalls with real-world projects. She spent extensive amount of time under-studying in NVIDIA NLP research group to adopt frameworks such as Megatron-LM to train very large language models. Her main goal is to help researchers and organization alike to accelerate their research work with her knowledge and graduating the work to apply in real life challenges.

Adam Grzywaczewski

Biography: Adam Grzywaczewski is a deep learning solution architect at NVIDIA, where his primary responsibility is to support a wide range of customers in delivery of their deep learning solutions. Adam is an applied research scientist specializing in machine learning with a background in deep learning and system architecture. Previously, he was responsible for building up the UK government’s machine-learning capabilities while at Capgemini and worked in the Jaguar Land Rover Research Centre, where he was responsible for a variety of internal and external projects and contributed to the self-learning car portfolio.