Will Bring Together Over 600 Attendees To Explore The Latest Advancements And Cutting Edge Ai Research
Join RE•WORK for the dual track Deep Learning Summit & Deep Learning in Healthcare Summit in London, Sept 20 – 21. The eighteenth global Deep Learning Summit and the fifth global Deep Learning in Healthcare Summit return to London, joined by full two days of interactive workshops: this event has been expanded due to popular demand, and will bring together over 600 attendees to explore the latest advancements and cutting edge AI research.
The Deep Learning Summit will cover the latest advancements in deep learning technology from global leaders in the field and explore how industry leaders and startups alike are applying such techniques across industry and society. The Deep Learning in Healthcare Summit will explore the breakthrough tools and methods set to revolutionize healthcare applications, medicine and diagnostics. Attendees are free to attend sessions across all tracks, providing a diverse agenda to explore.
Our goal at RE•WORK is to bring together industry experts, CEOs, Data Scientists, Startups, and researchers working in AI, to encourage new partnerships, explore the latest research and applications of deep learning, and to bridge the gap between academia and industry: “The value of the event for me was knowing the business, the use cases, the actors that work on and with deep-learning.” Coordinator of Innovation, Rakuten Institute of Technology
Track 1: Deep Learning Summit
Recent advancements in Deep Learning are creating a pathway for new technologies, and the impact of AI on real-world problems is becoming ever more prevalent. Recently announced to present her work is Raia Hadsell, Senior Research Scientist at DeepMind who leads the team studying robot navigation and lifelong learning. Raia will explain how previous methods for continual learning exist, but they are not applicable to deep neural networks. Her presentation will cover how she’s taking a step forward in this direction by using progressive neural networks.
Joining Raia on the Deep Learning track is Jian Li, Principal Data Scientist at Sky who leads a team focusing on machine learning research for Sky’s content discovery products and services including search and recommendation. Before joining Sky, Jian was with Microsoft Research in Cambridge where he developed the personalized email classification product for Microsoft Exchange and Office 365 services. Jian will introduce Sky’s brand-new content discovery system which helps customers to discover movies and TV shows using queries which naturally express human moods. Also presenting their breakthrough applications of Deep Learning is Alan Rosenwinkel, Senior Data Scientist at Urban Outfitters, Fabrizio Silvestri, Software Engineer at Facebook, and Yevgeniy Vahlis, Head of Applied Machine Learning at Borealis AI amongst other leaders in the field.
“We’ve met some great people and have discussed potential partnerships. We’ve made connections as the audience here is very specific and far more focused than other conferences we’ve attended.” Nikki Hallgrimsdottir, Co-Founder, Algomus.
Track 2: Deep Learning in Healthcare Summit
Healthcare is one of the industries seeing the most impactful transformations through AI, and deep learning techniques, in particular, are advancing drug discovery, diagnostics and research at an alarming pace. Experts from the likes of Google, Philips, NHS England, The Institute of Cancer Research, University of Oxford, MedicSen and many more will delve into topics such as personalized medicine, speech recognition, pattern recognition, image retrieval, neural networks, genomics amongst others. Graeme Rimmer, Engineering Manager at Google will share his work at Google Fit in tracking and analyzing cardiovascular signals in photoplethysmography, learning heart health from the wrist in the form of wearable sensors.
The NHS, the largest healthcare provider in the UK have identified the potential AI has to revolutionize healthcare in a novel manner, and Sarah Culkin, Strategic Lead will unpack emerging policies of how AI can work in the NHS. Sarah will also touch on some of the preliminary research and development projects being explored by their own data scientists.
“The Healthcare event is a great opportunity to meet people who I would have otherwise never come across. Before today, I didn’t think that AI in healthcare could cover such a wide range of topics, it is amazing the new things that are being explored and implemented.” Ka Wai Kong, CUHK, Machine Intelligence in Healthcare Summit, Hong Kong.
Both industry experts and academics will present challenges and solutions to real-world problems with research methods and business applications, following the opportunity to share knowledge and discuss in over 7 hours of networking. RE•WORK’s Deep Learning summits are attended by Data Scientists, Data Engineers, Machine Learning Scientists, CTOs, Founders, Director of Engineering, CEOs, Academics and Students.
Here’s a list of speakers that we are keen on;
Sarah Culkin, Strategic Data Lead, NHS England
Here’s what Sarah has to say about herself on LinkedIn: I am interested in innovative uses of data in the health system, for better health and care. I previously established and led the Department of Health Data Science Hub. Areas of interest include cross-sector data linkage and analysis, AI and machine learning, text analysis and use of social media data for predictive analytics in health.
Graeme Rimmer, Engineering Manager, Google Fit
Graeme is engineering lead on Google Fit as it pivots into the health space. His team build apps for Android, iOS and wearable devices as well as a platform for third-party fitness and health developers. One particular passion is researching digital biomarkers that can be inferred from both mobile and wearable devices.
Ahmed Serag, Research Scientist, Philips
Here’s how Ahmed describes himself on LinkedIn: I am a Scientist with extensive experience in turning data into knowledge for top-tier firms and academic institutions in USA and Europe. I have spent over a decade developing data analysis and decision support tools for Philips, Children’s National Health System, and Imperial College London, among others. I have experience in data science techniques with an emphasis on machine learning, deep learning and big data. I also have experience in computer vision, image analysis, and predictive modeling and analysis of multi-dimensional data.
Yinyin Yuan, Team Leader, The Institute of Cancer Research
I lead a team of computer scientists and statisticians to develop powerful machine learning algorithms for cancer research. Specifically, our approach bridges bioinformatics and high-throughput image analysis for pathological samples, to attain a better understanding of cancer biology and develop more accurate predictive models.
Steve Finkbeiner, Director and Senior Investigator, Center for Systems and Therapeutics
As one of the first investigators to join the Gladstone Institute of Neurological Disease in 1999, Dr. Finkbeiner is best known for his pioneering work on neurodegenerative diseases. He invented robotic microscopy, a new form of imaging that has helped unravel cause-and-effect relationships in amyotrophic lateral sclerosis (ALS, or Lou Gehrig’s disease), Huntington’s, Alzheimer’s and other neurodegenerative diseases. Dr. Finkbeiner used his robotic microscope to resolve a long-standing puzzle in Huntington’s disease. A study based on results from the microscope became the most-cited paper in the field of neuroscience in the last decade.