Despite a rise in investment, the adoption of Artificial Intelligence and Machine Learning has been slow and steady in the business community. Most companies have been slow to adopt and implement change, and only a small fraction of companies have successfully launched internal AI and ML initiatives to transform their operations.

Research has discovered that only 29% of UK enterprises have deployed machine learning in some capacity. Another survey by Gartner discovered that 42% of respondents simply did not understand the benefits of AI and ML usage for their organization.

And according to a recent Deloitte survey, 90% of companies believe AI to be “very” or “critically” important to their business, and 74% of adopters anticipate AI will be integrated into all enterprise applications over the next three years.

Join this free webinar, where leading academics from the University of Wolverhampton will help you understand more about how AI and ML can improve your business performance and productivity

Why attend this webinar?

• Learn more about cutting-edge advances in AI & ML use cases

• Gain confidence and find solutions to your own barriers to adoption

• Get access to University expertise and access to funding to diagnose and develop your company’s approach to AI/ML.

Who is this event aimed at?

Business Leaders, CEOs, Senior Managers and Chief Technology Officers from Small and Medium businesses in Telford, Shropshire and across the Marches.

Agenda:

1. Introduction to AI and ML and UoW’s world-leading expertise.

Presenter: Dr. Ahsan Adeel

Summary: The talk includes a gentle introduction to AI and ML and how they are impacting our everyday lives. Furthermore, our new exciting initiatives, world-leading expertise, collaborations, and ongoing national and international prestigious projects will be highlighted, including the world’s first multimodal hearing’s aids, human-like trustworthy companion robots, and next-generation mars rovers – projects with UKRI/ EPSRC, ARM, and NASA.

About the Speaker: Dr Adeel is an internationally recognised expert in brain-inspired multimodal information processing. He is co-leading the prestigious EPSRC £4 million transformative healthcare technologies (2050) programme grant, along with Prof. Hussain (PI). His proposed multisensory 5G IoT-enabled audio-visual (AV) hearing aid (HA) project is ranked second in the EPSRC’s healthcare technologies grand challenge of frontiers of physical intervention. EPSRC believes that the project vision represents a step-change in how healthcare will be delivered in future. As a PI, he is leading vision 2050, which aims to leverage the complementary strengths of both the cloud-based system and internet-independent 'brain-like' on-chip MM big data processing, to enable contextual switching option in HA by 2050. Adeel is a pioneer of conscious multisensory integration (CMI) theory, which sheds light on how our brain contextually/ selectively integrates the incoming multisensory information at the cellular level. It is believed that if his introduced universal contextual field (UCF) in pyramidal cell exists, and behaves in a way he described in his work, this could be a major contribution in our understanding of the intracellular mechanisms responsible for producing coherent thoughts, percepts, and actions, which are well-adapted to different situations and long-term goals. In collaboration with Qualcomm (San Diego), Alpha Data, Oxford Computational Neuroscience, and Plymouth BRIC, he is exploring and exploiting the potential of CMI theory to realize his grand 2050 vision of future brain-inspired technologies, including energy-efficient internet-independent on-chip big data processing, novel AI tool for diagnosing neurological disorders, collaborative and trustworthy partnerships between humans and machines, and novel therapeutic interventions/ assistive technologies. He is an electrical engineer and a cognitive scientist. He holds B. Eng. (Electrical), MSc (Electronics) and PhD (Cognitive Computing) degrees. He is a visiting EPSRC/MRC Research Fellow at the University of Stirling, and also a Fellow at MIT Synthetic Intelligence Lab, Oxford Computational Neuroscience Lab, and Howard Brain Sciences Foundation.

2, Industrial automation and instrumentation

Presenter: Dr. Eva Navarro López, PhD, MEng, BEng, BSc, CEng (ISA), FHEA, IEEE Senior Member

Summary: Control systems theory is the art of making the necessary corrections in the inputs of a system – by means of a feedback mechanism – to ensure a desired value in the outputs. I shall present some of the challenges I faced in my research and development projects devoted to the control of different mechatronic systems, particularly, mechanical and robotic systems. I will also present the new trend in industrial automation: automated verification. Verification is not the same as testing. Verification ensures that a designed system meets all requirements. Testing is applied to the final product to ensure that this is free of bugs and errors. With the increasing complexity of engineering applications, especially in networked and collaborative environments, the verification process has been subsumed as automated verification or formal verification. Currently, automated verification is an expansive dynamical analysis tool, there to provide safety and security in complex dynamical systems. It is used to robustly establish under which conditions –parameter and input ranges– some behavioural patterns emerge and provides systematic computational analysis and a robust validation of models and properties.

About the Speaker: Eva Navarro is Reader in Data Science and Director of AiDAs, the Artificial intelligence and DAta science Research Lab in the School of Mathematics and Computer Science at the University of Wolverhampton. But she is also a computer scientist, a control engineer, an applied mathematician, and a long-standing expert in complex networks, hybrid dynamical systems and cyber-physical systems – she was early in the field. Her work extends across many disciplines and applications, and resists easy classification. Few computer scientists can credibly claim to have controlled walking robots, eliminated mechanical vibration in oil fields, introduced formal methods of computer science into dynamical systems theory, and modelled important aspects of the human brain. She has developed her career in industry and academia in three different countries: the UK, Mexico and Spain. Embedded within the nascent field of cyber-physical social systems, she is also a Honorary Senior Research Fellow of the Spatial Policy Lab of the Manchester Urban Institute and the School of Environment, Education and Development at The University of Manchester. Moreover, she is part of the core team of AI Mexico, one of the coordinating institutions of the Coalition IA2030Mx, in charge of the National Agenda for AI of Mexico.

3, Predictive Maintenance using AI

Hyperspectral imaging and deep learning driven automated maintenance and diagnostic tools to reduce high cost of employing dedicated “Maintenance Engineers or Consultants”. This will involve the use of 3D imaging and deep image segmentation models to detect faults in products/machinery. An example use-case of drill bits manufacturing companies using this for automated fault detection systems.

About the Speaker:

Fahad Zia is a Research and Innovation Graduate at the University of Wolverhampton, working on the SOLVD project. Fahad is a certified Deep Learning specialist and an expert in data analysis. A graduate from National University of Science and Technology (NUST) in Pakistan, he has previously worked with the Data Science team at Teradata on development and deployment of computer-vision based solutions for the Teradata clientele using Nvidia's new Intelligent Video Analytics technologies.

Prior to that, he worked with Systems Limited as part of the Machine Learning team and with Biome Analytics as part of the AI Research team working on various projects ranging from Sales Forecasting to Unsupervised Clustering of healthcare data and Reinforcement Learning.

4, The Next Wave: Video Surveillance for Public Safety

Computer Vision is having a transformative impact upon our daily lives: Video surveillance is becoming almost ubiquitous, with surveillance cameras installed in buildings, factories, offices, and public places alike. However, there is very little automation of video image processing, relying on labour-intensive human analysis. This presentation will showcase the current state-of-the-art in terms of how AI computer vision is being applied to analyse human faces, as well as innovations in detecting objects, we will also highlight the potential benefits to enhanced public safety by the application of video surveillance and analysis through AI computer vision.

About the Speaker:

Dr Lavanya Srinivasan is a Post-doctorate Research Fellow at the University of Wolverhampton, UK. She completed a Bachelor's in Electronics and Communication Engineering, a Masters’ Degree in Systems Engineering and a PhD in Medical Image Processing. Lavanya has varied research and teaching experience at various levels. Her research interests are directly around Computer vision techniques, Image processing and Medical Image Processing.