Imperial.Tech.Pitch | Innovation in engineering with AI and Machine learning

Research pitches

Nick Blake - Hitachi (European Big Data Lab)

Nick has been driving innovation in IoT, Artificial Intelligence and Automation for sustainable, resilient and safe societies through collaboration with customers, corporate ventures and academic institutions for many years. Current R&D projects cover autonomous driving, advanced video intelligence, smart spaces and digital trust.

Constantinos Pantelides - Siemens Process Systems Engineering 

Costas Pantelides is currently the CEO & CTO of Siemens Process Systems Engineering, a position he has held for the past 16 years.

Technology pitches

Professor Michael Huth - Chair 

Professor Michael Huth is currently based in the Computer Science Department of Computing, Imperial College London and a member of FinTech Network. His research focuses on Cybersecurity, Cryptography, Mathematical Modeling, and Formal Verification with applications in Machine Learning, FinTech, and the Internet of Things.

Dr Maria Papathanasiou - Towards digitalisation of (bio-)pharmaceutical processes: a hybrid approach

The U.S. FDA has highlighted issues with drug shortages arising mostly from deficiencies in pharmaceutical manufacturing. For this, they urge the pharmaceutical industry to adopt novel process setups for seamless monitoring and high product quality. In that respect, hybrid modelling approaches constitute a suitable solution to assist integrated design, optimisation and control.

Professor Matthew Piggott - Digital twins to support the development of offshore renewable energy systems

What are the challenges and solutions in assessing offshore renewable energy resources? Dr Piggot will discuss the development of yield prediction and optimal array design tools suitable for business decision-making. In particular, he will focus on approaches to address the huge range of scales that need to be modelled, from atmospheric weather systems down to individual turbine blades. 

Professor Deniz Gunduz - Deep Learning Aided Wireless Video Transmission

Wireless video transmission currently suffers a drop in performance when the channel quality falls below the intended communication rate. Professor Gunduz discusses how a new approach harnesses the power of deep learning to achieve a better end-to-end video transmission quality over a wide range of communication channels.

Dr Daphne Tuncer & Dr Oytun Babacan - Data Analytics for Electric Vehicle Public Charging Network

The next decade will be marked by the rise of electric vehicle usage in the UK and Europe. To respond to the requirements of the electric vehicle era, Dr Babacan discusses the need to plan for the deployment of public charging infrastructures that will not only cover large areas cost-effectively but also support sustainable development targets. Dr Babcan will discuss the technology developed to solve this issue.

Who produced this content?

This content was compiled by Imperial Business Partners and Imperial Industry Partnerships and Commercialisation team.