Thought Leadership Events, University of Essex Series

We are delighted to launch a new series of thought leadership events with the University of Essex. 

Join us each month to expand and enhance your own knowledge plus build on your networks.

Explore as well our Thought Leadership overview

Coming up next!

Dr Mays Al-Naday, School of Computer Science and Electrical Engineering, University of Essex

Semantic based networking for digital transformation

“The adoption of the Internet of Things (IoT) for digital transformation is sketching new forms of distributed data and decentralised machine learning, localised with data sources, or in a proximity to adhere to such requirements as data privacy and possibly latency. The new form of data and machine learning is opening new horizons in future networks (such as 6G) while introducing novel requirements that leverage the role of data semantics at the network layer.

In this talk, I will share our vision on how future networks can find and exchange semantically-relevant data for such applications as machine-learning. Specifically, I will show how state-of-the art information-centric networks can be extended with novel networking services to enable semantic-based mapping and delivery of context-relevant, not necessarily exact copies, of data.”

Dr Amit Kumar Singh, School of Computer Science and Electrical Engineering, University of Essex

Attacks and defences for Edge Devices: side and covert channels perspective

Previous Thought Leadership Talks in the University of Essex series

Professor Stuart Walker, Essex University and Dave Townend, BT
Building dense urban mobile networks and the journey beyond 100GHz

Recording available now on the presentation page or on YouTube

In this talk we explored the challenges with densifying mobile networks and the role wireless backhaul has to play in building future mobile network architectures.

Zilong Liu, School of Computer Science and Electrical Engineering, University of Essex
6G for Future V2X Communications
Recording available now on the presentation page or on YouTube

Among many emerging vertical industries, connected autonomous vehicles (CAVs) with the aid of vehicle-to-everything (V2X) communication and networking are deemed to transform our travel experience with numerous far-reaching societal and economic benefits. With 5G communication networks rapidly rolling out globally, it is time to ask how 6G will help revolutionize our future V2X communications.

Somdip Dey, School of Computer Science and Electrical Engineering, University of Essex

AI, IoT and Blockchain being the future of food security
Recording available now on YouTube
Outline:

• Introduction to the problem of food wastage and food security around the world
• Brief introduction of AI and machine learning and their advancement
• State-of-the-art of using blockchain and AI/ML in food supply chain and reduction of food wastage
• Introduce FoodSQRBlock and SmartNoshWase frameworks – frameworks using blockchain, AI, IoT and Cloud to digitize food supply chain for easy accessibility and traceability while helping stakeholders in the supply chain to reduce food waste and catering for food security

Prof Maria Fasli, Executive Dean, Faculty of Science and Health, University of Essex on "Collaboration in Data Science Projects"

Conference TFNetworkAutumn21

Data Science - The beating heart of AI
➣ Conference overview and registration 
➣ YouTube TFNetworkSummer21 Conference Playlist 

Maria Fasli is a Professor of Computer Science (Artificial Intelligence) and the Executive Dean of the Faculty of Science and Health at the University of Essex. She is also the Founding Director of the Institute for Analytics and Data Science (IADS) at the University of Essex and the Director of the ESRC Business and Local Government Data Research Centre (BLGDRC). She obtained her BSc in Informatics from the Technological Education Institute of Thessaloniki in 1996, and her PhD in Computer Science from the University of Essex in 2000.

She has held research and academic positions at the University of Essex since 1999 and became Professor in 2012. In 2009, she became the Head of the School of Computer Science and Electronic Engineering at Essex, a post which she held until the end of 2014. In August 2014, she was appointed in her current role as Director of IADS. In 2016, she was awarded the first UNESCO Chair in Analytics and Data Science.

Her research interests lie in artificial intelligence techniques for analyzing and modeling complex systems and structured and unstructured data in various domains. Her research has been funded by National Research Councils in the UK and other organisations including businesses. She has worked with a range of companies in data analytics related projects. Maria has published over 130 papers in the field of artificial intelligence, modelling and learning from data and has delivered keynote talks at international conferences. She is also passionate about education and pedagogic innovation and in 2005, she was awarded a National Teaching Fellowship by the Higher Education Academy (UK) for her innovative approaches to education.

Collaboration in Data Science Projects

Dr Zoë Webster, AI Director at BT on "Establishing an AI Centre of Enablement"

Conference TFNetworkAutumn21

Data Science - The beating heart of AI
➣ Conference overview and registration 
➣ YouTube TFNetworkSummer21 Conference Playlist 

Zoë has a background in computer science (with a MSc and PhD in AI) and in developing novel AI technologies across a few verticals. From a focus on AI at QinetiQ and SEA, Zoë moved into supporting innovation more broadly at Innovate UK, leading and implementing innovation strategies in ICT, enabling technologies and high value manufacturing. She also had responsibility for Innovate UK’s Horizon Scanning Unit. Zoë moved to BT in Nov 2020 to turn her focus back to AI as AI Director in BT’s Data and AI team.

Establishing an AI Centre of Enablement

There are a number of questions to consider when setting up a team to accelerate the development and adoption of AI at scale. Not all of these centre on the technology. This talk will discuss some of the questions that have focused my attention here at BT and the perspectives that are important in addressing them.

James Grant, Lecturer in Statistics at Lancaster University on "Multi-armed Bandits"

Conference TFNetworkAutumn21

Data Science - The beating heart of AI
➣ Conference overview and registration 
➣ YouTube TFNetworkSummer21 Conference Playlist 

James Grant is a Lecturer in Statistics at Lancaster University where he completed his PhD in 2019. His research considers mathematical models of decision-making and learning, and combines ideas from Statistics, Operational Research, and Machine Learning. He is particularly interested in multi-armed bandit problems, online optimisation, recommender systems, and time series.

University profile

Multi-armed Bandits

In modern data science applications, there is often the opportunity to observe the effects of a decision and revise it, and to iterate this process repeatedly, experimenting in order to learn an optimal action. Multi-armed bandits provide mathematical models of such settings, where designing an optimal sequence of decisions can be highly challenging. This talk will give an introduction to multi-armed bandit models, and explore the best techniques used to tackle the problems.

Libby Kinsey, Ocado Technology on "Scaling Data Science"

Conference TFNetworkAutumn21

Data Science - The beating heart of AI
➣ Conference overview and registration 
➣ YouTube TFNetworkSummer21 Conference Playlist 

Libby Kinsey recently joined Ocado Technology as Head of Data Science - Strategy and Operations. 

Prior to that she was Lead Technologist for AI at Digital Catapult and co-founder of Project Juno. Libby re-trained in machine learning in 2014 after 12 years working in technology, mostly in venture capital.

LinkedIn

Twitter @libbykinsey

Twitter @OcadoTechnology

Scaling Data Science

Data science already powers insights, products and capabilities in every part of Ocado Technology’s solutions, i.e. we know how to do data science at scale. The next big challenge is about reducing effort to value. Scaling data science is hard.

Tuba Islam, Google Cloud on "ML Journey into production - What are the challenges and how to tackle them?"

Conference TFNetworkAutumn21

Data Science - The beating heart of AI
➣ Conference overview and registration 
➣ YouTube TFNetworkSummer21 Conference Playlist 

Tuba Islam is a machine learning specialist at Google Cloud, based in London, primarily focusing on deep learning, forecasting, natural language processing and the automation of machine learning solutions. 

Before Google, she was a data scientist at SAS, working globally across Europe and the US. She started her career in research and development at the National Research Institute of Electronics and Cryptology in Turkey implementing speech recognition engine for Turkish. She has an engineering background in electronics and holds a master’s degree in digital signal processing.

She delivered successful projects across various industries such as rogue trader fraud detection in capital markets, smart metering analytics in utilities, hazard detection and readmission prediction in healthcare, credit risk in banking, churn prediction in telecom, rate making in insurance, demand forecasting in retail, pharmacovigilance analysis in life sciences.

LinkedIn

ML Journey into production

What are the challenges and how to tackle them?

In this talk, we will share the key challenges that the organizations are likely to face when they move their machine learning models from experimentation stage into production and provide recommendations on how to handle these challenges with the right process and technology in place.

James Hamilton, TUI on "It’s not all about the model – challenges applying artificial intelligence"

Conference TFNetworkAutumn21

Data Science - The beating heart of AI
➣ Conference overview and registration 
➣ YouTube TFNetworkSummer21 Conference Playlist 

James Hamilton

I have spent my entire career applying data, analytics and modelling to deliver value in different organisation across a range of sectors including retail, public sector and now travel. My greatest satisfaction comes from building and developing analytics teams and in coming up with innovative solutions to new complex problems.

In my current role I head the data science capability and am also lead product owner for data driven solutions in the commercial part of our business, mostly focus on automated pricing. 

Prior to this I worked as head of customer investment strategy at Tesco and as an analytics and modelling consultant at PwC. I have a maths degree from Exeter and a masters in operational research from Lancaster.

It’s not all about the model – challenges applying artificial intelligence

In TUI we have a very successful automated pricing system that has delivered significant benefits over a number of years. We continue to develop it incrementally and our current focus is on better use of our data and applying artificial intelligence.

We have experienced a number of challenges in applying these approaches and I will talk about our experiences, how we are overcoming them and why if we get to training a new model we have already done the hard part.