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We are excited to present Best Practices in AI Afternoon which will be held on the 5th of July, 12-6pm at Workroom 2, 38 Mappin, Sheffield, S1 4DT and online.
The afternoon will consist of talks and walkthroughs on best practices for research, design, development, and deployment of AI systems with guest speakers from Nvidia, University of Cambridge and University of Bristol. A focus on practical aspects such as tooling, optimisation, profiling, tips and tricks to supercharge AI in your research!
Buffet lunch and coffee will be provided, with a drinks reception sponsored by Nvidia after the event.
This event is held in collaboration between the Research Software Engineering (RSE) group and the Centre for Machine Intelligence (CMI) in the University of Sheffield.
Karin is a Senior Solutions Architect at NVIDIA, with a specific focus on the Higher Education and Research (HER) industry in the UK. At NVIDIA, she’s leading collaborative efforts with the NVAITC initiative, particularly centred around Isambard-AI. Prior to joining NVIDIA, Karin was a research engineer at Alana AI, where she specialized in Large Language Models (LLMs) and Retrieval Augmented Generation (RAG) systems. Her primary research interests include exploring topic transitions within conversational systems and devising effective strategies for recommendation settings. Karin holds a Ph.D. in Natural Language Processing from Heriot-Watt University, UK, which she completed in July 2023. During her doctoral studies, she focused on advancing conversational AI and recommendation systems. Notably, she contributed to Heriot-Watt’s participation in the Amazon Alexa Prize 2018 competition. Additionally, Karin gained valuable industry experience through an internship at Amazon in 2021, where she worked as an applied scientist on recommendation algorithms.
Ryan is a machine learning engineer at the Accelerate Programme for Scientific Discovery and is interested in driving forward scientific research which is grounded in excellent software engineering and machine learning fundamentals. Before working at Accelerate, Ryan’s research interests explored unconventional approaches to computing using complex physical devices from the world of condensed matter physics.
Wahab finished their PhD in machine learning from the University of Bristol on computer vision applications in biomedicine and material science. They worked as a visiting researcher at the European Space Agency analysing motion capture data of stroke-survivors. More recently working as a machine learning engineer in robotics and aerospace applications. He joined the Isambard AI team in April 2024.
Edwin joined the RSE team in October 2022. He comes from a background in geophysics following a BSc and MSc in Geophysical Sciences at the University of Leeds. After university, he worked in the private sector, developing machine learning (ML) workflows to solve geophysical imaging and inversion problems.
Edwin has practical experience in the designing, training and evaluation of ML models. He is experienced in Python having worked with data science libraries such as Numpy, Pandas, Scikit-learn, Tensorflow and Keras. He has a growing interest in MLOps (Machine Learning Operations) and the practical challenges of scaling up ML practices.
Bob works in the Modernising Medical Microbiology group in the Nuffield Department of Medicine on software as a service platforms for infectious disease diagnostics, public health and research applications.
He has collaborated with a wide range of academic, public and private sector partners including GPAS, AirQo, Institut Pasteur, the UK Health Security Agency and Health Data Research UK. Bob has been a maintainer and a reviewer for The Carpentries, and has contributed to more than 20 peer-reviewed publications, including one in Nature. He is currently interested in technologies and working practises that result in useful research software.
Book a 15 to 30 minutes 1 to 1 meeting with Nvidia experts on the day! They are open to discuss your research project at any stage whether you are already familiar and use accelerated computing looking to optimise or scale your project or whether you are relatively new and want to explore how to use AI/HPC in your project. Example discussion topics include:
Nvidia experts on the day:
In-person meetings will take place on the day and slots are limited and are first come, first served. Remote meetings (may not happen on the day) will be offered once we’ve run out of meeting slots.
For queries relating to collaborating with the RSE team on projects: rse@sheffield.ac.uk
Information and access to JADE II and Bede.
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Queries regarding free research computing support/guidance should be raised via our Code clinic or directed to the University IT helpdesk.