The University of Southampton

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Research

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Research

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Research

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Southampton is renowned for offering a first-rate education in an exceptional research environment, but we do not merely rest on our history and past successes. This bold expansion of staff and facilities in Electronics and Computer Science will place Southampton at the cutting-edge of AI teaching and research long into the future, delivering our mission to change the world for the better.

Professor Mark E. Smith - President and Vice-Chancellor
Email:
ik3n19@soton.ac.uk

 

https://www.linkedin.com/in/ilkaza/

I am a PhD student at the UKRI Centre for Doctoral Training in Machine Intelligence for Nano-Electronic Devices and Systems (MINDS) of the University of Southampton, currently in the second year of the programme. The first year consisted of a number of taught modules related to Artificial Intelligence. I hold a Diploma (5-years undergraduate degree) in Electrical and Computer engineering from the Democritus University of Thrace (Greece) and an MSc in Artificial Intelligence from the University of Southampton.

My research is on Safe Reinforcement Learning and combines tools from Control Theory and Software Engineering. A big part of it focuses on the field of Human-Agent Interaction. In many real-world applications, where safety is of primary importance, plain reinforcement learning methods (even combined with deep learning) will fail. My goal is to build provably safe reinforcement learning agents for safety-critical real-world systems. Applications that can benefit from my research are mainly autonomous vehicles and a range of robotic tasks.

Research

Research interests

Machine Learning, Deep Learning, Reinforcement Learning, Online Learning, Human-Agent Interaction, Game Theory, Control Theory, Robotics, Software Engineering

Publications

2022

2021

2019

2018

2017

2016

2015

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Email:
i.p.bodala@soton.ac.uk

 PhD

Indu P Bodala is a Lecturer in Computer Science. She received her Ph.D. from the National University of Singapore where she studied vigilance fluctuations during naturalistic tasks using EEG and eye-tracking modalities and developed techniques for vigilance enhancement through multisensory stimuli. She worked as a postdoc at the NUS School of Computing where she studied human factors such as trust and attention during interactions with autonomous agents. She also worked as a postdoc at the Department of Computer Science and Technology, University of Cambridge, in the areas of HRI and social robotics and developed a robotic coach that can deliver mindfulness. She used longitudinal methods to study changes in the user affect and perceptions of the robotic mindfulness coach which received recognition in the media platforms such as BBC Look East and Raspberry Pi Foundation's Hello World magazine. Her recent work is also shortlisted for the RSJ/KROS Distinguished Interdisciplinary Research Award in the IEEE RO-MAN 2021 conference. Her research interests include human-robot interaction, affective computing, machine learning, healthcare technologies, and cognitive neuroscience. 

The full publication list is available on my google scholar page.

Research

Research interests

My research encompasses, but is not limited to the following topics:

  • human-robot interaction
  • affective computing
  • machine learning
  • healthcare technologies
  • cognitive neuroscience 
  • mental health and wellbeing

Teaching

Modules 

Semester 2, 2021-22:

  • COMP6214 - Open Data Innovation
  • COMP6239 - Mobile Applications Development

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Email:
d.b.thomas@soton.ac.uk

 

I studied Computer Science as an undergrad at the Dept. of Computing in Imperial,
then did my PhD in digital architectures in the same department. After 5 years as
a researcher associate and then research fellow, in 2010 I moved to the Dept. of Electrical
and Electronic Engineer at Imperial as a Lecturer, then Senior Lecturer. In 2021 I joined
the Electronics and Computer Science Dept. as a Professor. Both my research and teaching
interests are at the intersection of software and hardware, particularly in the interaction and
relationshops between programming languages, algorithms, computer achitecture and digital
implementation. A lot of my research involves the use of FPGAs (Field Programmable Gate
Arrays), as they provide a great playground for exploring and implementing new digital architectures,
such as custom CPUs, application-specific accelerators, or new programming paradigms such
as event-driven computing.

Research

Research interests

My research interests range up and down the hardware-software stack, from low-level implementation
of mathematical digital blocks, through to custom processors and on-chip networks, and up into high-level
languages for describing pipelined and distributed programs. A lot of my work involves FPGAs, which
are useful both as prototyping platforms and as target computational platforms. I'm particularly interested
in languages and architectural patterns which make it easier to program FPGAs (and other digital architectures),
such as High-Level Synthesis (HLS), meta-programming for logic design, and hardware co-ordination using
events. Some overall research themes include:

  • Financial computing, such as credit-risk analysis and option pricing, using FPGAs and GPUs
  • Highly optimised uniform and non-uniform random number generation for FPGAs, providing best-in-class area-efficiency-quality tradeoffs
  • Meta-programming for high-level synthesis, in order to allow extension of the HLS language and primitives at compile-time
  • Event-driven computing as a way of designing programmes for large multi-FPGA systems

Teaching

Previously I was the course director for the EIE (Electrical and Information Engineering) degree at Imperial College,
which covered both computer science and electrical engineering. I've previously taught and assessed the following subjects:

  • Programming
  • Computer Architecture
  • Compilers
  • Networks
  • Databases
  • High-performance Computing

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Research

Research interests

  • Embedded Artificial Intelligence
  • Hardware Security
  • Secure and Resilient Hardware Implementation of AI Modules
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Student Biography: I'm a first year PhD student, undertaking a project in collaboration with Siemens Mobility on "Artificial Intelligence and Mechanism Design for Optimal Routing of Connected and Autonomous Vehicles". I am supervised by Dr Stein and Dr Gerding within the School of Electronics and Computer Science at the University of Southampton. Prior to undertaking a PhD, I graduated from the University of Southampton with a BSc in Computer Science. 

I am particularly fascinated by the field of intelligent traffic management, including, but not limited to the applications of reinforcement and deep learning in traffic systems - it is estimated that 46,447,500 (83%) of the United Kingdom population live in urban areas where road traffic congestion is a major factor to poor air quality for individuals which is associated with increased morbidity from respiratory diseases. In 2017, commuters in London lost on average 227 hours and £1,680 due to congestion and the total cost of congestion to the UK was approximately £8 billion.

Supervisors: Dr Sebastian Stein, Dr Enrico Gerding

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