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Welcome to

The 4th Research & applied ai summit

London, UK - Friday June 29th, 2018

 

the leading community for the science and applications of AI.

 

RAAIS is a community for entrepreneurs and researchers who accelerate the science and applications of AI technology. It is organised by Nathan Benaich.

Our 2018 event is invite-only and run over one full day.

RAAIS
 

We're the forum for emerging and established ai leaders

2018 announced Speakers

  Blake Richards  - Principal Investigator at  LiNCLab   Blake is an Assistant Professor at the  University of Toronto  in the Department of Biological Sciences with a cross-appointment to the Department of Cell and Systems Biology. He’s also a Fellow of the Canadian Institute for Advanced Research in the Learning in Machines and Brains Program, and a Lab Scientist with the  Creative Destruction Lab .  Previously,  Blake worked as a programmer and research analyst in magnetic resonance imaging at the Centre for Addiction and Mental Health. He earned his PhD from the  University of Oxford  in Pharmacology where he explored synaptic plasticity in early life.

Blake Richards - Principal Investigator at LiNCLab

Blake is an Assistant Professor at the University of Toronto in the Department of Biological Sciences with a cross-appointment to the Department of Cell and Systems Biology. He’s also a Fellow of the Canadian Institute for Advanced Research in the Learning in Machines and Brains Program, and a Lab Scientist with the Creative Destruction Lab.

Previously,  Blake worked as a programmer and research analyst in magnetic resonance imaging at the Centre for Addiction and Mental Health. He earned his PhD from the University of Oxford in Pharmacology where he explored synaptic plasticity in early life.

  Friederike Schüür  - Research Engineer at  Cloudera Fast Forward Labs   Friederike is a Research Engineer at Fast Forward Labs (FFL). Diving into emerging machine learning capabilities, FFL builds fully functioning prototypes exploring state-of-the-art technology as well as advising companies how to get ready for the future of machine learning and AI.  Prior to Fast Forward Labs, Friederike worked at small to medium startups on the US East Coast, earned a PhD in Cognitive Neuroscience from University College London, and during a postdoc at New York University researched how we make gambling decisions to maximize financial gain. 

Friederike Schüür - Research Engineer at Cloudera Fast Forward Labs

Friederike is a Research Engineer at Fast Forward Labs (FFL). Diving into emerging machine learning capabilities, FFL builds fully functioning prototypes exploring state-of-the-art technology as well as advising companies how to get ready for the future of machine learning and AI.

Prior to Fast Forward Labs, Friederike worked at small to medium startups on the US East Coast, earned a PhD in Cognitive Neuroscience from University College London, and during a postdoc at New York University researched how we make gambling decisions to maximize financial gain. 

  Shakir Mohamed  - Research Scientist at  DeepMind   Shakir is a Research Scientist at DeepMind working on statistical machine learning and artificial intelligence. Much of his current focus is on the interface between probabilistic reasoning, deep learning and reinforcement learning, and how the computational solutions that emerge in this space can be used for systems and agent-based decision-making.  Prior to joining DeepMind, he held a Junior Research Fellowship from the  Canadian Institute for Advanced Research  (CIFAR) as part of the programme on Neural Computation and Adaptive Perception. He holds a PhD in Statistics Machine Learning from the  University of Cambridge .

Shakir Mohamed - Research Scientist at DeepMind

Shakir is a Research Scientist at DeepMind working on statistical machine learning and artificial intelligence. Much of his current focus is on the interface between probabilistic reasoning, deep learning and reinforcement learning, and how the computational solutions that emerge in this space can be used for systems and agent-based decision-making.

Prior to joining DeepMind, he held a Junior Research Fellowship from the Canadian Institute for Advanced Research (CIFAR) as part of the programme on Neural Computation and Adaptive Perception. He holds a PhD in Statistics Machine Learning from the University of Cambridge.

  François Chollet  - Software Engineer at  Google Brain   François Chollet is a software engineer at Google in Mountain View, CA. He is the creator of the Keras deep-learning library, which has over 200k users, as well as a contributor to the TensorFlow machine-learning framework.  François is author of the book “Deep learning with Python” (Manning Publications). He does deep-learning research with a focus on computer vision and the application of machine learning to formal reasoning.

François Chollet - Software Engineer at Google Brain

François Chollet is a software engineer at Google in Mountain View, CA. He is the creator of the Keras deep-learning library, which has over 200k users, as well as a contributor to the TensorFlow machine-learning framework.

François is author of the book “Deep learning with Python” (Manning Publications). He does deep-learning research with a focus on computer vision and the application of machine learning to formal reasoning.

 
  Justin Gilmer  - Research Scientist at  Google Brain   Justin Gilmer was a member of the first Google Brain Residency Program and is now a Research Scientist at Google Brain.  He is interested in building data efficient neural networks for problems in chemistry and biology, studying theoretical properties of deep learning, and machine learning security.  Recently he has been working with Ian Goodfellow on adversarial examples.  In 2015 he received his PhD in Theoretical Mathematics from Rutgers University with a focus in Combinatorics.  

Justin Gilmer - Research Scientist at Google Brain

Justin Gilmer was a member of the first Google Brain Residency Program and is now a Research Scientist at Google Brain.

He is interested in building data efficient neural networks for problems in chemistry and biology, studying theoretical properties of deep learning, and machine learning security.

Recently he has been working with Ian Goodfellow on adversarial examples.

In 2015 he received his PhD in Theoretical Mathematics from Rutgers University with a focus in Combinatorics.  

  Guy Galonska -  CTO and Co-Founder of    INFARM   As CTO, Guy is responsible for INFARM’s Product R&D, Engineering, Manufacturing and Software development leading various teams of mechanical engineers, software engineers and designers at INFARM.  He is a self-educated farmer, entrepreneur and inventor that led the development of INFARM’S unique patented technology alongside his brother, Erez Galonska.  Guy honed his leadership skills through half a decade in the culinary industry where he explored and matured his interest in holistic ways of eating and producing food.

Guy Galonska - CTO and Co-Founder of INFARM

As CTO, Guy is responsible for INFARM’s Product R&D, Engineering, Manufacturing and Software development leading various teams of mechanical engineers, software engineers and designers at INFARM.

He is a self-educated farmer, entrepreneur and inventor that led the development of INFARM’S unique patented technology alongside his brother, Erez Galonska.

Guy honed his leadership skills through half a decade in the culinary industry where he explored and matured his interest in holistic ways of eating and producing food.

 
  Chris Ré  - Associate Prof. at  Stanford University   Chris is an Associate Professor in the Department of Computer Science at Stanford University in the InfoLab who is affiliated with the Statistical Machine Learning Group, Pervasive Parallelism Lab, and  Stanford AI Lab . His work's goal is to enable users and developers to build applications that more deeply understand and exploit data.   Chris also cofounded a company, based on his research, that was acquired by Apple in 2017. He received a Moore Data Driven Investigator Award in 2014, the VLDB early Career Award in 2015, the  MacArthur Foundation Fellowship  in 2015, and an Okawa Research Grant in 2016.

Chris Ré - Associate Prof. at Stanford University

Chris is an Associate Professor in the Department of Computer Science at Stanford University in the InfoLab who is affiliated with the Statistical Machine Learning Group, Pervasive Parallelism Lab, and Stanford AI Lab. His work's goal is to enable users and developers to build applications that more deeply understand and exploit data. 

Chris also cofounded a company, based on his research, that was acquired by Apple in 2017. He received a Moore Data Driven Investigator Award in 2014, the VLDB early Career Award in 2015, the MacArthur Foundation Fellowship in 2015, and an Okawa Research Grant in 2016.

  Barbara Engelhardt  - Associate Professor at  Princeton   Barbara is an associate professor in the Computer Science Department at Princeton University.  She is a PI on the Genotype-Tissue Expression (GTEx) Consortium. Her research interests involve statistical models and methods for analysis of high-dimensional biomedical data, with a goal of understanding the underlying biological mechanisms of complex phenotypes and human diseases.  Barbara graduated from Stanford and received her Ph.D. from the University of California, Berkeley.

Barbara Engelhardt - Associate Professor at Princeton

Barbara is an associate professor in the Computer Science Department at Princeton University.

She is a PI on the Genotype-Tissue Expression (GTEx) Consortium. Her research interests involve statistical models and methods for analysis of high-dimensional biomedical data, with a goal of understanding the underlying biological mechanisms of complex phenotypes and human diseases.

Barbara graduated from Stanford and received her Ph.D. from the University of California, Berkeley.

 
  Luc Vincent  - VP Engineering at  Lyft   Luc is VP of Autonomous Technology at Lyft. In this role, he bootstrapped and currently leads the "Level 5 Engineering Center", Lyft's ambitious effort to build a Self Driving System. He also oversees Lyft's Open Platform initiative - which enables third party Autonomous Vehicles to operate as part of the Lyft service - as well as Mapping Technology.  Prior to Lyft, Luc spent 12 years at Google, most recently as Sr Director of Engineering. Luc led all imagery-related activities of Google's Geo group and was responsible for launching Street View. He earned his B.S. from Ecole Polytechnique, M.S. in Computer Science from University of Paris XI, and PhD in Mathematical Morphology from Ecole des Mines de Paris.

Luc Vincent - VP Engineering at Lyft

Luc is VP of Autonomous Technology at Lyft. In this role, he bootstrapped and currently leads the "Level 5 Engineering Center", Lyft's ambitious effort to build a Self Driving System. He also oversees Lyft's Open Platform initiative - which enables third party Autonomous Vehicles to operate as part of the Lyft service - as well as Mapping Technology.

Prior to Lyft, Luc spent 12 years at Google, most recently as Sr Director of Engineering. Luc led all imagery-related activities of Google's Geo group and was responsible for launching Street View. He earned his B.S. from Ecole Polytechnique, M.S. in Computer Science from University of Paris XI, and PhD in Mathematical Morphology from Ecole des Mines de Paris.


RAAIS Community


Our Sponsors

We are proudly sponsored by the Google Cloud Platform team and leading technology law firm Cooley LLP.

 


Community PARTNERS

We are grateful for the support of our friends at Code Club and the London.AI meetup.


Venue

RAAIS 2018 will take place in central London. Details will be shared in the Eventbrite invitation post-registration.