Meet the instructors

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 theoretical 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.

Among his industry roles, he served as 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 think tank and a recent research initiative at London School of Economics 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.

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 created multiple new data science modules across levels—from undergraduate to MSc—and supervised research students on wide range of projects: from AI-driven music generation to applications of AI in neuroscience, oncology, ecological research and medical imaging analysis.

Later, at the University of Cambridge as a Senior Machine Learning Engineer in the Accelerate Programme for Scientific Discovery, he led the software engineering efforts of the programme, playing a pivotal role in expanding the team and developed the programme's machine learning strategy. He established initiatives like Cambridge's AI Clinic and software engineering workshops to help researchers troubleshoot their technical AI challenges. These initiatives have received great feedback from participants, engaging over 150 PhDs, postdocs, and faculty members within 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 Royal Mail.

Earlier in his career, in 2010, he worked for three years as a Product Manager at the Financial Times, where he developed novel NLP language models to analyse the semantic context of financial reports.

He has also lectured on mathematics and AI at institutions including Imperial College London, Cambridge University, LSE, 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 for his outstanding impact on teaching and academic supervision, including four student-led awards from the London School of Economics.