Ajit is a dedicated leader and teacher in Artificial Intelligence (AI), with a strong background in AI for Cyber-Physical Systems, research, entrepreneurship, and academia.
Currently, he serves as the Course Director for several AI programs at the University of Oxford and is a Visiting Fellow in Engineering Sciences at the University of Oxford. His work is rooted in the interdisciplinary aspects of AI, such as AI integration with Digital Twins and Cybersecurity.
His courses have also been delivered at prestigious institutions, including the London School of Economics (LSE), Universidad Politécnica de Madrid (UPM), and as part of The Future Society at the Harvard Kennedy School of Government.
As an Advisory AI Engineer, Ajit specialises in developing innovative, early-stage AI prototypes for complex applications. His work focuses on leveraging interdisciplinary approaches to solve real-world challenges using AI technologies.
Ajit has shared his expertise on technology and AI with several high-profile platforms, including the World Economic Forum, Capitol Hill/White House, and the European Parliament.
Ajit is currently writing a book aimed at teaching AI through mathematical foundations at the high school level.
Ajit resides in London, UK, and holds British citizenship. He is actively engaged in advancing AI education and innovation both locally and globally. He is neurodiverse - being on the high functioning autism spectrum.
Ajit's work in teaching, consulting, and entrepreneurship is grounded in methodologies and frameworks he developed through his AI teaching experience. These methodologies help to rapidly develop complex, interdisciplinary AI solutions in a relatively short time. These include:
1. The Jigsaw Methodology for low-code data science to non-developers.
2. The AI Product Manager framework and AI product market fit framework
3. Software engineering with the LLM stack
4. Agentic RAG for cyber-physical systems.
5. AI for Engineering sciences:
6. The ability of AI to reason using large language models
He also consults at senior advisory levels to companies.
His newsletter on AI in Linkedin has a wide following
Co-founder, Erdos | Author | Senior Tutor in AI & ML, University of Oxford | AI Ambassador, Oxford AI & ML Competency Center | Data Architect, Metro Bank
Anjali Jain is a London-based data architect, author, and AI expert with over two decades of experience in software development, architecture, data strategy, and applied machine learning.
At the University of Oxford, she serves as Senior Tutor in AI and Machine Learning and as AI Ambassador at the AI & ML Competency Center, where she leads strategic initiatives in AI education and research.
She is the co-founder of Erdos Research, a collaborative research and innovation lab focused on building and implementing AI systems, advancing prompting methods, and developing tools for AI-assisted software engineering.
Anjali also serves as Data Architect at Metro Bank, where she supports the integration of AI into financial systems with a focus on data governance, data architecture and compliance.
She is the co-author of “10X AI Developer Guide with BRIDGE AI Framework” and “AI-Assisted Programming for Web and Machine Learning”, offering practical methodologies for building intelligent, human-centric technologies.
Abhinav Kimothi is a seasoned data science and AI leader with over 15 years of experience in data driven consulting, application development, and leveraging AI and ML to solve complex business problems. Presently, he is a co-founder and the Vice President of Artificial Intelligence at Yarnit where he leads a team dedicated to developing an innovative content marketing platform powered by generative AI.
Abhinav's career has spanned diverse projects in analytics, predictive modeling, machine learning and enterprise product development. Abhinav studied engineering at BITS-Pilani and got his management education at Indian School of Business – Hyderabad.
Passionate about driving AI advancements, he aims to make a meaningful impact by transforming data into actionable insights and pushing the boundaries of technology.
Nicole is the Co-Founder, CEO, and Co-Chief AI Officer at Quantmate, a deep-tech fntech company developing AI agents for portfolio management and strategy development via natural language. She is a globally recognized thought leader in large language models and agentic architectures, with a particular focus on their transformative applications in quantitative finance.
As a guest lecturer, Nicole shares her expertise in Python, machine learning, and deep learning at universities. She is also a frequent speaker at AI and quantitative fnance events.
Nicole has authored Math for Machine Learning and Transformers in Action with Manning Publications. Her forthcoming book, Transformers: The Defnitive Guide – Applications Beyond NLP, will be published by O’Reilly Media.
Senior Cloud Advocate, Microsoft
Chris is Senior Cloud Advocate at Microsoft with more than 15 years's experience in the IT industry. He's a published author on several books about web development as well as the Go language. He's also a recognized speaker as well as keynote speaker and holds a Google developer expert title.
Arthur Orts is Head of Generative and Agentic AI at Pictet Asset Management in Geneva, where he leads the development and adoption of AI capabilities across the firm.
Prior to joining Pictet, Arthur spent 10 years at Bloomberg in London, working in Financial Solutions with a focus on buy-side clients and portfolio management/risk analytics tools.
Arthur combines deep expertise in financial technology with hands-on experience building AI-powered workflows and agentic systems. He is particularly focused on the practical implementation of Agentic Artificial intelligence into professional environments, including coding assistants, autonomous agents and enterprise AI adoption strategies.
Claudia Saleh is an AI Product Leader at Disney with over 20 years of IT experience. She traded the laid-back beaches and sunny Rio de Janeiro, Brazil, where she worked for media companies like Globo.com and ADVPress, for the dynamic international scene of Washington, DC. There, she contributed her expertise to international organisations such as the World Bank, the Inter-American Development Bank, and the United Nations.
She works in the media and entertainment industry, driving innovation at the intersection of technology and creativity. As a graduate student in Artificial Intelligence, she combines academic insights with hands-on expertise, focusing on AI strategies and their transformative potential for knowledge and creative professionals.
An experienced speaker and mentor, Claudia has guided enterprises in adopting technology effectively and strives to empower professionals to see AI as a collaborator. Her diverse background includes a decade as a travel journalist and graphic designer, which adds a unique perspective to her work, enabling her to simplify complex ideas and inspire diverse audiences.
When she’s not exploring the latest AI trends, Claudia can be found writing, travelling, or immersing herself in the magic of Disney. She brings a unique voice to conversations about AI, blending technical insights with a deep appreciation for the creative spark that drives innovation.
Richard Taylor is an AI/ML Lead with over a decade of experience in machine learning and AI within the financial sector. He has a background in Astrophysics, specialising in Computational Cosmology at the University of Manchester, where he conducted statistical analysis of large-scale universe simulations.
Before joining Ninety One, Richard was a Senior Data Scientist at Fable Data, where he was the first technical hire. He built the company’s initial data pipelines, machine learning models, and MVP, securing major investment clients and driving business growth. He also led and expanded the Product and Compliance functions within the Data Science division, fine-tuning Large Language Models for near real-time data classification and automating the capture and processing of additional datasets using AI.
Earlier in his career, he worked at Barclays Bank in Market Surveillance, developing machine learning models to monitor trading activity, following time spent working for KPMG. Now, at Ninety One, he is responsible for looking at applications of AI across the business with a focus on investments.
