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Event details

23 September 2020
12:00 - 13:00
Executive Education

Event details

23 September 2020
12:00 - 13:00
Executive Education

The development of the internet over the last few decades has resulted in a massive increase in the production of data and the unprecedented availability of computing power for corporate applications. Machine Learning and artificial intelligence (AI) techniques have been fuelled by these revolutions to emerge from being purely academic topics of investigation to be the basis for a new wave of products and services for the digital age. 

The paradigm-shifting opportunities presented to corporates by this emerging technology range from the ability to expose and extract insights and patterns from data lakes to replacing human beings in critical decision-making scenarios. However, with these opportunities also come novel risks and concerns that must be considered when contemplating the development and deployment of AI and machine learning agents. These include understanding how their trustworthiness may be measured, the ethics and policies required for their deployment and the cybersecurity implications of their widespread adoption. 

This webinar will discuss the fundamental features of machine learning and AI across multiple industries as well as the unique opportunities and challenges that this technology presents. By exploring specific game-changing examples from financial services and beyond, our speakers from Imperial College Business School and Citi will also discuss some of the hurdles to implementation such as inherent bias in data. Such considerations being particularly relevant in a post-COVID-19 technology-enabled society.

Speakers

Deeph Chana

Deeph Chana

Professor Deeph Chana has extensive experience of working on world-leading STEM in academia, industry and government. He is the Director of the Cyber Security executive programme, Co-Director of the Centre for Financial Technology and the Institute for Security Science Technology, and co-founder of the UK-Government funded Research Institute in Trustworthy Industrial Control Systems and Imperial's FinTech Network of Excellence.

Prag Sharma

Prag Sharma

Based in Dublin, Dr. Prag Sharma leads the Emerging Technologies Group within Treasury & Trade Services’ Innovation Labs at Citi. Data Analytics and Artificial Intelligence is a focus for the group, which includes research and development on Machine Learning, including Natural Language Processing and Graph Analytics approaches among others. Distributed Ledger Technologies (i.e. Blockchain) is another area of research for the group.

Prag has significant experience in R&D Management, experimental and algorithmic design and development in both business and academic environments with start-ups and multinationals.

Prag holds a PhD in Computer Vision and an MBA majoring in Innovation.

Giles Pavey

Giles Pavey

Giles is a seasoned Data Science Leader, having held positions in both the private and public sector. He is Global Data Science Director at Unilever, the global consumer goods company, where he works  to maximise the benefits from AI and advanced analytics across the business. He works around the world on projects as diverse as supply chain, AI ethics, digitising factories, innovation, sustainability and understanding consumer behaviour.

Prior to his current role, Giles worked at the UK government writing data strategy and building data science innovation capability at the Department for Work and Pensions. He also worked for 18 years at dunnhumby, the Tesco owned marketing consultancy: originally as Head of Analytics and more latterly as the Chief Data Scientist. During his time at dunnhumby he worked around the world with major retailers and consumer goods companies. Giles has a passion for collaboration, notably between academia and industry. As such he holds visiting positions in computer science at University College London and mathematics at Oxford University.

 Giles will be speaking in a personal capacity drawing on insights garnered from his 30 years of experiences in advanced analytics.

Learn more on these upcoming executive programmes

Event details

Date: 23 September 2020
Time: 12:00 - 13:00
Audience: Executive Education