2037: Tech Foresight
Unravelling complexity – The Science of the Future
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Tech Foresight 2037 aims to bring together academics, industry leaders and members of the public to discuss and engage with the increasing complexity of our future world. The future will be smart; the future will be networked; the future will be complex. TF2037 uses these concepts as a springboard to ask how the evolution of technology will give us the capability to process and address increasingly complex decisions and innovations.
TF2037 will explore how a decentralised, dynamically networked, personalised future may unfold and what this could mean for your business.
We will step into a world where all of our appliances and devices might make decisions on our behalf without consulting us first; where networks will behave like stormy seas – rapidly churning and shifting in humanly unpredictable ways. We will also examine technological advances from the human perspective, exploring how computer systems can be used to replicate our brains and how robots become more intelligent systems to improve our quality of life. Not only will machines learn like us, but computers will help us diagnose illnesses that affect our brains. Another 20 years of progress will let us choose our preferred energy sources by the millisecond, communicate in natural language with computer systems, and make use of companion or service robots that understand the world and derive meaning in the same way we do.
Join us on 14th June and help us unravel the complex world of 2037.
- Dr Simon Tindemans: Dr Simon Tindemans works in the area of smart grids and electricity control. The energy domain has the same potential for “flash crashes” – or wide-ranging failures – that have been seen in the financial domain. Simon’s work focuses on ways to avert or respond to these, as well as ways to use machine learning to continually adapt smart electricity provision. In particular, the work performed as part of the Low Carbon London initiative examines the mechanisms by which smart pricing and electricity provision can modify human behavior to encourage sustainability.
- Prof Alessandra Russo: Prof Alessandra Russo works in machine learning, looking specifically at algorithms that mean a machine can continue to learn, as well as have a natural-language dialogue with a human user about what has been learnt and why decisions have been made. Crucially, this requires the machine to process information provided back to it from the human user about any errors that it’s made, and turn these into data which it can use to continue learning. The learning process is therefore one of continuous improvement, focusing on the areas in which the improvement is needed.
- Dr Stefan Leutenegger: Dr Stefan Leutenegger’s research focuses on autonomous robot navigation, in particular on the sensing capabilities and the algorithms required to navigate in a potentially unknown environment. Stefan works on indoor service robots, drones and has a special interest in autonomous vehicles. He explores why motion tracking and spatial perception is so crucial to the operation of autonomous vehicles, and to the development of “intelligent” robots that can adapt to human needs.
- Dr Benjamin Almquist: Dr Ben Almquist’s work lies in the intersection of material sciences, biology and nanotechnology. He focuses on the development of methods to dynamically manipulate the behavior of cells and tissues. In particular, this work enables us to understand how to direct the process of tissue repair by manipulating signaling networks. One application of this work is the design of wound dressings that can program the sequence of drug release into a patient wound, while another lies in the ways in which cell behaviours can be guided in order to promote blood vessel growth in damaged tissue.
- Dr Thomas Heinis: Dr Thomas Heinis works in the area of management of big data, particularly on the development of software and hardware to improve the diagnosis of brain disease. These technological solutions seek to mimic the connections in the brain, making use of unsupervised learning to create a signature of disease. This involves using different sets of patient data as input into the learning algorithm, in order to identify clusters of patients that have similar disease and understand how they relate to each other.
Confirmed Keynote Speaker:
- Naveen Jain: Naveen Jain is an entrepreneur and philanthropist driven to solve the world's biggest challenges through innovation. He is the founder of Moon Express, World Innovation Institute, iNome, TalentWise, Intelius, and Infospace. Naveen sees beyond the current business and technological landscape, creating companies that make a true impact. Ernst and Young's Entrepreneur of the Year, Silicon India's "Most Admired Serial Entrepreneur," and the receiver of "Albert Einstein Technology Medal" for his pioneers in technology, he has been repeatedly honored for his entrepreneurial successes.
- Engage with world-class Imperial academics with deep expertise across fields such as smart energy networks, machine learning, neuroscience, bioengineering and robotics.
- Network with other experts from industry, academia and beyond, learn how other sectors and domains are grasping the opportunities of radical technological change
- Explore how the next generation of technological advances will influence sectors and domains in the long-term future through our Tech Foresight presentations
- Actively participate in the process of defining how this future might develop, through our Realtime Future Mapping digital experience
- Take back learnings and use them in your business to inform your new technology directions and market opportunities
- Learn about Imperial’s IBP engagement platform and how to continue longer-term engagement
Information for delegates:
- Registration: Invitation only
- Venue: London City Hall, The Queen's Walk, London SE1 2AA. 9th Floor (for London’s Living Room). Map can be found here
- Directions by public transport: City Hall is situated next to Tower Bridge on the south bank of the river Thames. It is most easily reached by public transport and the main entrance to the building is located on the riverfront. Tube- stations London Bridge (Jubilee and Northern lines and mainline station; Tower Hill (Circle and District lines); Tower Gateway (Docklands Light Railway); Buses- 42, 47, 381, RV1.
- Interactive Q&A: On the day, we will be using a simple interactive Q&A system that will allow you to ask and vote for the questions that interest you.
- Access requirements: if you have not already communicated any access requirements to Jolanta Leonaite then please do so as soon as possible.
If you require any assistance on the day please do not hesitate to contact me at firstname.lastname@example.org