6:00 - Doors open. Networking. Wine, beer & snacks.
6:45 - Opening remarks.
7:00 - Talk #1 - From science to startups with Tensorflow, Computer Vision and people by Daniel Martinho-Corbishley (Aura Vision Labs)
7:25 - Q&A break
7:30 - Talk #2 - Towards the use of Graphical Models in business modelling and technology strategy by Dr Alastair Moore, Head of Analytics and Machine Learning, Mishcon de Reya
7:55 - Q&A break 8:00 - Wrap-up
Speaker - Dr. Daniel Martinho-Corbishley, CEO at Aura Vision Labs
Title - From science to startups with Tensorflow, Computer Vision and people.
Abstract: Convolutional Neural Networks are the most popular approach to performing image recognition. But how can we move them from the lab to the real world? In this talk Daniel will discuss the challenges of classifying pedestrian demographics in unconstrained environments and using the latest advances in computer vision to solve critical business problems. You can expect to hear about novel image labelling techniques, why people are so valuable, and the future of computer vision.
Bio: Daniel has just completed his PhD in Computer Science and Biometric Identification from the University of Southampton and is now the co-founder and CEO of Aura Vision Labs, a video AI platform specialising in measuring and improving retail shopping experiences. His research involves robust estimation of pedestrian demographics from CCTV imagery using the latest techniques in computer vision and psychological crowdsourcing. Daniel’s research is published in the leading applied machine learning journal, IEEE TPAMI and Aura Vision was featured on BBC Click in May 2018.
Speaker - Dr Alastair Moore, Head of Analytics and Machine Learning, Mishcon de Reya
Title - Towards the use of Graphical Models in business modelling and technology strategy
Abstract: Recent developments in understanding technology diffusion and business strategy lend themselves towards analysis as directed graphs. Alastair will briefly introduce a Wardley Map, a directed dependency graph situated in a metric space. I will highlight aspects of this representation that lend themselves to analysis using dynamic graphical models. I will discuss some preliminary thinking about modelling aspects of a business, specifically those that are dependent on machine learning systems.
Bio: Alastair is a UCL Computer Science PhD (Computer Vision) with broad experience of applied Machine Learning and Statistical Analysis in a variety of settings. His background includes stints with corporate research, internet startups and universities. He was on the founding team on spin-out Satalia.com (Data Science) and venture backed WeArePopUp.com (Real Estate contracting) and helped setup the IDEALondon innovation centre with UCL and Cisco Systems. His primary objective at Mishcon de Reya is to ensure the firm consistently uses data and machine learning techniques to support and improve its business process, and helps advise its clients on innovation and technology. Alastair continues to maintain an active teaching role in the UCL School of Management (Predictive systems) the Cambridge Judge Business School (Entrepreneurship) and Peking University, Beijing (Technology innovation). His research interests include technology strategy, smart contracting and computational law.
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