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Dr BR Rastegari

Top university

1 year ago

Resilient Resource Allocation in Dynamic Settings under Uncertainty (RRADSU) University of Southampton in United Kingdom

Degree Level

PhD

Field of study

Computer Science

Funding

Fully Funded

Deadline

Expired

Country flag

Country

United Kingdom

University

University of Southampton

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Where to contact

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Keywords

Computer Science
Data Science
Machine Learning
Mathematics
Operations Research
Artificial Intelligence
Mathematical Modeling
Probability Theory
Engineering Mathematics
Computational Mathematics
Resource Allocation
Applied Mathematic
Multi-agent System

About this position

Supervisory Team : Dr Bahar Rastegari, Dr Vahid Yazdanpanah, Prof Sebastian Stein

Allocation of scare resources is prevalent in our lives. From allocating drivers and vans for delivery of goods, to the allocation of paramedics and ambulances in disaster response. Take Emergency Services as an example. They play a critical role by dispatching vehicles and qualified professionals to emergency situations. While providing skilled and well-equipped staff in a short time is key in most scenarios, they operate with limited resources and hence it is crucial to ensure that right level of resources is used to deal with a situation, while maintaining the resilience of the system for upcoming emergencies.

The two highly desired and well-studied properties for allocations are ``efficiency’’ (making the best use of the limited sources available) and ``fairness’’. An allocation is ``Resilient’’ if, should a problem occur (e.g. an ambulance breaks down and becomes unavailable), it can be amended with minimal loss to efficiency and fairness.

Our main goal is to use multi-agent systems and machine learning techniques to design fair, efficient and resilient allocation of scarce, and possibly heavily constrained, resources in dynamic settings with uncertain preferences. The specifics and detailed objectives of the project can be adapted to your skills and interests.

The supervisory team are proud members of the Agents Interaction and Complexity research group . As a PhD student in AIC, you will benefit from engaging and collaborating with a vibrant and diverse group of academics and researchers from wide range of disciplines and expertise in or relevant to AI.

Entry Requirements

A UK 2:1 honours degree, or its international equivalent .

How To Apply

Apply online: Search for a Postgraduate Programme of Study (soton.ac.uk) .

You need to:

• choose programme type (research), 2025/26, Faculty of Engineering and Physical Sciences

• please select if you will be full time or part time

• choose the relevant PhD in Computer Science

• add Dr Bahar Rastegari as the proposed supervisor in Section 2

Applications should include:

• research proposal

• CV (resumé)

• 2 reference letters

• degree transcripts to date

Funding details

Fully Funded

How to apply

Apply online at soton.ac.uk

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