Research
Publications
Contact
Research
Teaching
Contact
Contact
Research
Teaching
Publications
Contact
Research
Contact
Publications
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.
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
Kazantzidis, Ilias, Norman, Timothy, Du, Yali and Freeman, Christopher (2022) How to train your agent: active learning from human preferences and justifications in safety-critical environments. International Conference on Autonomous Agents and Milti-Agent Systems 2022, Auckland, Auckland, New Zealand. 09 - 13 May 2022. (In Press)
Brown, Andrew, Todman, Tim, Luk, Wayne, Thomas, David, Vousden, Mark, Bragg, Graeme, Beaumont, Jonny, Moore, Simon, Yakovlev, Alex and Rafiev, Ashur (2022) Non-deterministic event brokered computing. In Proceedings of the 12th International Symposium on Highly Efficient Accelerators and Reconfigurable Technologies, HEART 2022. The Association for Computing Machinery. pp. 84-86 . (doi:10.1145/3535044.3535055).
Rafiev, Ashur, Morris, Jordan, Xia, Fei, Yakovlev, Alex, Naylor, Matthew, Moore, Simon, Thomas, David, Bragg, Graeme, Vousden, Mark and Brown, Andrew (2022) Practical distributed implementation ofvery large scale petri net simulations. Koutny, Maciej, Kordon, Fabrice and Moldt, Daniel (eds.) In Transactions on Petri Nets and Other Models of Concurrency XVI. vol. 13220 LNCS, Springer Science and Business Media Deutschland GmbH. pp. 112-139 . (doi:10.1007/978-3-662-65303-6_6).
Koohy, Behrad, Stein, Sebastian, Gerding, Enrico and Manla, Ghaithaa (2022) Reward function design in multi-agent reinforcement learning for traffic signal control. ATT'22: Workshop Agents in Traffic and Transportation, July 25, 2022, Vienna, Austria: Part of IJCAI 2022, Austria, Vienna, Austria. 23 - 29 Jul 2022. (In Press)
Rafiev, Ashur, Yakovlev, Alex, Tarawneh, Ghaith, Naylor, Matthew F., Moore, Simon W., Thomas, David B., Bragg, Graeme M., Vousden, Mark L. and Brown, Andrew D. (2022) Synchronization in graph analysis algorithms on the Partially Ordered Event-Triggered Systems many-core architecture. IET Computers and Digital Techniques, 16 (2-3), 71-88. (doi:10.1049/cdt2.12041).
2021
Brown, Andrew, Vousden, Mark, Bragg, Graeme McLachlan, Shillcock, Julian, Beaumont, Jonathan and Thomas, David Barrie (2021) Coupling bulk phase separation of disordered proteins to membrane domain formation in molecular simulations on a bespoke compute fabric. Membranes, 12 (1). (doi:10.3390/membranes12010017).
Todman, Tim, Thomas, David and Luk, Wayne (2021) Exploring performance enhancement of event-driven processor networks. In Proceedings - 2020 International Conference on Field-Programmable Technology, ICFPT 2020. Institute of Electrical and Electronics Engineers Inc. 1 pp . (doi:10.1109/ICFPT51103.2020.00056).
Naylor, Matthew, Moore, Simon W., Thomas, David, Beaumont, Jonathan R., Fleming, Shane, Vousden, Mark, Markettos, A. Theodore, Bytheway, Thomas and Brown, Andrew (2021) General hardware multicasting for fine-grained message-passing architectures. In Proceedings - 29th Euromicro International Conference on Parallel, Distributed and Network-Based Processing, PDP 2021. Institute of Electrical and Electronics Engineers Inc. pp. 126-133 . (doi:10.1109/PDP52278.2021.00028).
Shahsavari, Mahyar, Thomas, David, Brown, Andrew and Luk, Wayne (2021) Neuromorphic design using reward-based STDP learning on event-based reconfigurable cluster architecture. In ICONS 2021 - Proceedings of International Conference on Neuromorphic Systems 2021. The Association for Computing Machinery. 8 pp . (doi:10.1145/3477145.3477151).
Shahsavari, Mahyar, Beaumont, Jonathan, Thomas, David and Brown, Andrew (2021) POETS: A parallel cluster architecture for Spiking Neural Network. International Journal of Machine Learning and Computing, 11 (4), 281-285. (doi:10.18178/ijmlc.2021.11.4.1048).
2019
Li, Qiang, Wang, Erwei, Fleming, Shane T., Thomas, David B. and Cheung, Peter Y.K. (2019) Accelerating position-aware top-k listnet for ranking under custom precision regimes. Sourdis, Ioannis, Bouganis, Christos-Savvas, Alvarez, Carlos, Toledo Diaz, Leonel Antonio, Valero, Pedro and Martorell, Xavier (eds.) In Proceedings - 29th International Conference on Field-Programmable Logic and Applications, FPL 2019. Institute of Electrical and Electronics Engineers Inc. pp. 81-87 . (doi:10.1109/FPL.2019.00022).
Thomas, David B. (2019) Compile-time generation of custom-precision floating-point IP using HLS tools. Takagi, Naofumi, Boldo, Sylvie and Langhammer, Martin (eds.) In Proceedings - 26th IEEE Symposium on Computer Arithmetic, ARITH 2019. vol. 2019-June, Institute of Electrical and Electronics Engineers Inc. pp. 192-193 . (doi:10.1109/ARITH.2019.00044).
Thomas, David B. (2019) Templatised soft floating-point for high-level synthesis. In Proceedings - 27th IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2019. Institute of Electrical and Electronics Engineers Inc. pp. 227-235 . (doi:10.1109/FCCM.2019.00038).
2018
Su, Jiang, Fraser, Nicholas J., Gambardella, Giulio, Blott, Michaela, Durelli, Gianluca, Thomas, David B., Leong, Philip H.W. and Cheung, Peter Y.K. (2018) Accuracy to throughput trade-offs for reduced precision neural networks on reconfigurable logic. Voros, Nikolaos, Keramidas, Georgios, Antonopoulos, Christos, Huebner, Michael, Diniz, Pedro C. and Goehringer, Diana (eds.) In Applied Reconfigurable Computing: Architectures, Tools, and Applications - 14th International Symposium, ARC 2018, Proceedings. vol. 10824 LNCS, Springer-Verlag. pp. 29-42 . (doi:10.1007/978-3-319-78890-6_3).
Su, Jiang, Faraone, Julian, Liu, Junyi, Zhao, Yiren, Thomas, David B., Leong, Philip H.W. and Cheung, Peter Y.K. (2018) Redundancy-reduced MobileNet acceleration on reconfigurable logic for ImageNet classification. Voros, Nikolaos, Keramidas, Georgios, Antonopoulos, Christos, Huebner, Michael, Diniz, Pedro C. and Goehringer, Diana (eds.) In Applied Reconfigurable Computing: Architectures, Tools, and Applications - 14th International Symposium, ARC 2018, Proceedings. vol. 10824 LNCS, Springer-Verlag. pp. 16-28 . (doi:10.1007/978-3-319-78890-6_2).
2017
Inggs, Gordon, Thomas, David B. and Luk, Wayne (2017) A domain specific approach to high performance heterogeneous computing. IEEE Transactions on Parallel and Distributed Systems, 28 (1), 2-15, [7465804]. (doi:10.1109/TPDS.2016.2563427).
Tavakkoli, Aryan and Thomas, David B. (2017) A high-level design framework for the automatic generation of high-throughput systolic binomial-tree solvers. IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 26 (2), 341-354, [8081850]. (doi:10.1109/TVLSI.2017.2761554).
Tarawneh, Ghaith, Mokhov, Andrey, Naylor, Matthew, Rast, Alex, Moore, Simon W., Thomas, David B., Yakovlev, Alex and Brown, Andrew (2017) Programming model to develop supercomputer combinatorial solvers. In Proceedings - 46th International Conference on Parallel Processing Workshops, ICPPW 2017. Institute of Electrical and Electronics Engineers Inc. pp. 171-179 . (doi:10.1109/ICPPW.2017.35).
2016
Su, Jiang, Thomas, David B. and Cheung, Peter Y.K. (2016) Increasing network size and training throughput of FPGA restricted Boltzmann machines using dropout. In Proceedings - 24th IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2016. Institute of Electrical and Electronics Engineers Inc. pp. 48-51 . (doi:10.1109/FCCM.2016.23).
Fleming, Shane T. and Thomas, David B. (2016) StitchUp: Automatic control flow protection for high level synthesis circuits. In Proceedings of the 53rd Annual Design Automation Conference, DAC 2016. vol. 05-09-June-2016, Institute of Electrical and Electronics Engineers Inc.. (doi:10.1145/2897937.2898097).
Xue, Zeping and Thomas, David B. (2016) SynADT: dynamic data structures in high level synthesis. In Proceedings - 24th IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2016. Institute of Electrical and Electronics Engineers Inc. pp. 64-71 . (doi:10.1109/FCCM.2016.26).
Thomas, David B. (2016) Synthesisable recursion for C++ HLS tools. In 2016 IEEE 27th International Conference on Application-Specific Systems, Architectures and Processors, ASAP 2016. vol. 2016-November, Institute of Electrical and Electronics Engineers Inc. pp. 91-98 . (doi:10.1109/ASAP.2016.7760777).
2015
Salem, V., Izzi-Engbeaya, C., Coello, C., Thomas, D. B., Chambers, E. S., Comninos, A. N., Buckley, A., Win, Z., Al-Nahhas, A., Rabiner, E. A., Gunn, R. N., Budge, H., Symonds, M. E., Bloom, S. R., Tan, T. M. and Dhillo, W. S. (2015) Glucagon increases energy expenditure independently of brown adipose tissue activation in humans. Diabetes, Obesity and Metabolism, 18 (1), 72-81. (doi:10.1111/dom.12585).
Contact
Email: ik3n19@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
Contact
Email: i.p.bodala@soton.ac.uk
PhD
Contact
Email: GS1N17@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
Publications
Contact
Email: d.b.thomas@soton.ac.uk
- Integrated PhD Student in Machine Intelligence for Nano-Electronic Devices and Systems
- Postgraduate Researcher
- Integrated PhD Student in Machine Intelligence for Nano-Electronics devices and systems at the University of Southampton (2021-2026)
- MSc in Embedded Systems Engineering with distinction at the University of Leeds, The UK (2019-2020)
Research
Research interests
- Embedded Artificial Intelligence
- Hardware Security
- Secure and Resilient Hardware Implementation of AI Modules
Ph.D.
Contact
Telephone: +44 (0) 23 8059 7402927722
Email: shaa1n20@soton.ac.uk
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