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  Multimodal Data and Processing led Explainable AI: Application Maritime Domain


   School of Engineering

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  Dr Mohsen Naqvi  No more applications being accepted  Funded PhD Project (Students Worldwide)

About the Project

Award Summary

100% fees covered, and a minimum tax-free annual living allowance of £18,622 (2023/24 UKRI rate).

Overview

We are in the era of Data and AI. The main demand on AI from the responsible data engineering bodies is to provide explainable AI (XAI). This project will focus GEO-located multimodal data and XAI for downstream tasks in the maritime domain.

The proposed innovation will impact the industry by exploiting the generalized and fast-deployable AIs feature extractors (multimodal data processing and feature extraction pipeline is already achieved in Innovate UK AKT2I project). The major focus will be on explainable classification of the multiple maritime downstream tasks such as vessels behaviour prediction, monitoring, anomaly, and threat detection.

This innovation is also crucial to transfer Newcastle University’s unique strength in signal and information processing to yield physics-informed and signal processing led XAI for the above-mentioned maritime downstream tasks. This project will transform from our own fundamental breakthroughs/algorithms on multimodal data processing i.e., multi-target tracking for security and surveillanceabnormal event detectionbehaviour analysisintelligent sensing, and noise and complex signal enhancement.

The industrial input will be also part of this project. Therefore, the project will provide equal opportunities in the career progression in academia as well as industry.

The dataset recorded at Newcastle University from the North-Sea will be also used. The Intelligent Sensing Laboratory, a unique multi-sensor state-of-the-art £1M research facility and the GPU server-based processing power will be provided. Moreover, the candidate will work in a team environment with full research career development support and training.

Number Of Awards

1

Start Date

16.09.2024

Award Duration

3.5 years

Application Closing Date

31.03.2024

Sponsor

EPSRC DTP

Supervisors

Mohsen Naqvi

Shidong Wan

Eligibility Criteria

You must have, or expect to gain, a minimum 2:1 Honours degree or international equivalent in a subject relevant to the proposed PhD project (inc. Electrical and Electronic Engineering, Computing, etc.). Enthusiasm for research, the ability to think and work independently, excellent analytical skills and strong verbal and written communication skills are also essential requirements.

Home and international applicants (inc. EU) are welcome to apply and if successful will receive a full studentship. Applicants whose first language is not English require an IELTS score of 6.5 overall with a minimum of 5.5 in all sub-skills.

International applicants may require an ATAS (Academic Technology Approval Scheme) clearance certificate prior to obtaining their visa and to study on this programme. 

How To Apply

You must apply through the University’s Apply to Newcastle Portal 

Once registered select ‘Create a Postgraduate Application’.  

Use ‘Course Search’ to identify your programme of study:  

  • ‘Course Title’ using the programme code: 8060F
  • Research Area: Electrical and Electronic Engineering 
  • select ‘PhD Electrical and Electronic Engineering (FT)’ as the program of study 

You will then need to provide the following information in the ‘Further Details’ section:  

  • a ‘Personal Statement’ (this is a mandatory field) - upload a document or write a statement directly in to the application form  
  • ‘Research Proposal’ - when prompted for how you are providing your research proposal – select either ‘Write Proposal’ or ‘Upload document’. Your research proposal should be no more than 1500 words. 
  • the studentship code ENG133 in the ‘Studentship/Partnership Reference’ field  

In the ‘Supporting Documentation’ section please upload:

  • your CV  

Contact Details

Mohsen Naqvi

Computer Science (8) Engineering (12) Mathematics (25) Physics (29)
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