All of our events may be recorded and shared via the University of Sheffield Kaltura platform so those who cannot attend may still benefit. We will consider your attendance implicit consent to this.
We are excited to present the Best Practices in AI Afternoon 2 which will be held on the 11th of November, 12-5pm at Design Studio 01 (D05), Pam Liversidge Building, Broad Lane, S1 3JD.
The afternoon will consist of talks and walkthroughs on best practices for research, design, development, and deployment of AI. It will 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.
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, and the N8 CIR.
Register to attend in-person or remotely
Speakers from the community Amir Ghalamzan, University of Sheffield Shaun Donnelly, University of Sheffield Denis Newman-Griffis, University of Sheffield Anna Louise Ollerenshaw, Nvidia Mozhgan Kabiri Chimeh, Nvidia Roy Ruddle, University of Leeds Fred Sonnenwald, University of Sheffield William Smith, University of Manchester Mohse Farid, University of Derby Jon Stammers, AMRC, University of Sheffield Shereen Zafar, University of Leeds Micheal Abaho, University of Liverpool Ernst Matthias Sachs, MARS, Lancaster University Anthony Evans, University of ManchesterDr Amir Ghalamzan is an Associate Professor at the University of Sheffield and Theme Lead for Robotics and Autonomous Systems at the Centre for Machine Intelligence. He leads the Intelligent Manipulation Lab, where his research focuses on robotic grasping and manipulation, teleoperation, agri-food robotics, robot learning, and haptic and tactile sensors. Amir holds a PhD in Robotics and Automation Engineering from Politecnico di Milano and is committed to advancing data-driven control and planning for real-world robotic challenges, especially in agricultural robotics and tactile perception.
Shaun is a research software engineer at the University of Sheffield with a background in astrochemistry and AI-driven computational chemistry. Since joining the RSE team in December 2024, he’s been exploring how large language models can transform research workflows, from Retrieval Augmented Generation to tool-driven Agentic AI. He’s particularly interested in exploring how to make research software more accessible by the use of natural language as an interface between researchers, their software and their research workflows.
Denis Newman-Griffis (they/them) is a Senior Lecturer in the School of Computer Science and Theme Lead for AI-Enabled Research in the University of Sheffield’s Centre for Machine Intelligence. Their award-winning work investigates the responsible use of AI for human flourishing, including pioneering work on responsible AI in research funding and assessment, ethical practice for AI in policy and public services, and critical perspectives on AI for health and disability. Denis is a British Academy Innovation Fellow and a former Research Fellow of the Research on Research Institute.
Anna Ollerenshaw is a Solutions Architect supporting partners by delivering AI/deep learning solutions. She specialises in conversational AI, particularly speech technology, LLMs, data curation and retrieval augmented generation systems. She has several years experience working in engineering and automation across aerospace, manufacturing and defence, and received her PhD in End-to-End Automatic Speech Recognition (ASR) from the University of Sheffield.
Mozhgan Kabiri Chimeh is a Developer Relations Manager at NVIDIA, focused on growing the AI and accelerated computing ecosystem across the UK and Ireland. In this role, she works with researchers, startups, and industry partners to support the adoption of NVIDIA’s AI software platforms and GPU technologies, helping them accelerate innovation and scale solutions.
Roy Ruddle is a Professor of Computing at the University of Leeds, and Director of Research Technology at the Leeds Institute for Data Analytics (LIDA). Roy has worked in both industry and academia, and specialises in interdisciplinary research into interactive visualization, data quality and data science workflows. His Leeds Virtual Microscope (LVM) has been commercialised by the healthcare company Roche and was a REF2021 Impact Case Study. He was an Alan Turing Institute Fellow from 2018 – 2023, and is currently principal investigator on two major projects: Making Visualization Scalable (MAVIS) for explainable AI (funded by the EPSRC) and AI for Dynamic prescribing optimisation and care integration in multimorbidity (DynAIRx; funded by the NIHR). He has published a practitioner’s guide for rigorously and efficiently checking data quality (https://doi.org/10.5518/1481) and an associated software package as open source (https://pypi.org/project/vizdataquality/).
In-person spaces are limited, please register to attend!
For queries relating to collaborating with the RSE team on projects: rse@sheffield.ac.uk
Information and access to Bede.
Join our mailing list so as to be notified when we advertise talks and workshops by subscribing to this Google Group.
Queries regarding free research computing support/guidance should be raised via our Code clinic or directed to the University IT helpdesk.