Ahmad is a seasoned educator and machine learning engineer with a diverse background spanning academia, industry, and public sector projects. He holds an MSc in Advanced Computer Science from the University of Manchester and a PhD in Mathematics from the London School of Economics, where his research utilised large-scale scientific computing to study problems in graph theory.

In 2017, Ahmad joined Imperial College London as a Senior Fellow in Data Science, where he developed a new MSc Data Science module and supervised over 20 students in diverse projects ranging from AI-driven music generation to using AI in neuroscience, bioinformatics, and medical imaging analysis.

Later, at the University of Cambridge as a Senior Machine Learning Engineer in the Accelerate Programme for Scientific Discovery programme, he played a pivotal role in expanding the software engineering team and developed the programme's machine learning strategy. He established initiatives like Cambridge's AI Clinic and software engineering workshops to help researchers at Cambridge troubleshoot their technical AI problems, initaitves which has engaged over 150 PhDs, postdocs, and faculty members in just one year.

Beyond academia, Ahmad has worked on major machine learning projects across various industries. His roles included Solution Architect for the UK Ministry of Justice, Senior Data Engineer for the UK Department of Health and data scientist at the Royal Mail.

He has also lectured on AI and data science at institutions such as LSE, University of Bristol, University of London, the University of Notre Dame (US) and New York University, while delivering technical workshops for organisations like the House of Commons Library and various research-based startups in bioinformatics and healthcare.

Ahmad’s contributions to education have been recognised with multiple teaching awards, including four student-led awards from the London School of Economics for his outstanding impact on teaching and academic supervision.

Steffen is an AI practitioner and educator with an extensive track record of applying AI in various domains across academia, industry, and startups. He holds an MSc and PhD in Mathematics from the London School of Economics (obtained in 2015), where his doctoral research focused on theortical aspects of reinforcement learning.

Following his PhD, Steffen worked with several FTSE 100 companies as an AI specialist, collaborating with engineers, scientists, and financial analysts to integrate machine learning into critical business processes. Most recently, he served as a Senior AI Engineer at Rolls-Royce, contributing to AI-driven advancements in engineering and automation.

In the past five years, Steffen has shifted his focus to the startup ecosystem, applying AI in emerging fields spanning diverse domains, including mental health and insurance automation.

Steffen has also been involved in academic consulting, including a psephology project with Germany’s leading political polling agency and a recent research initiative at LSE exploring the intersection of reinforcement learning and theortical game theory.

Additionally, he has lectured on deep learning and applications of AI and automation at various UK-based universities and corporate institutions.

Jan is an expert in Big Data, Scientific Computing, and Artificial Intelligence, with a career spanning both industry and academia.

He has held senior leadership roles in major organisations, including Head of Data Management at Royal Mail and Senior Big Data Systems Engineer at Hortonworks, where he led projects focused on optimising mathematical models using large-scale computing infrastructure.

Most recently, Jan served as Senior Vice President and Lead Software Engineer at Citi Bank’s Innovation Lab, where he drove advancements in AI and financial technology. He holds a PhD in Distributed Computing and has lectured on software engineering, AI, FinTech, and scientific computing at several UK universities.

Jan is a well-regarded figure on the academic circuit, regularly invited to serve as a guest lecturer, competition judge, and external examiner on academic panels.

He has co-supervised and mentored over 100 students at UK universities, drawing on his industrial experience to complement their academic guidance with industry-informed best practices, and help them apply AI at scale to bridge the gap between theory and implementation in their research