Note: I am looking for PhD students. If you are interested in working with me please have a look at my personal homepage.
I am a lecturer (Assistant Professor) and member of CPS Group. I am interested and working on topics that deal with mobile health, mobile sensing, security and performance of systems. Previously, I worked at Univeristy of Cambridge with Cecilia Mascolo in Mobile System Group (2018-2020) and at Aalto University with Dr. Tuomas Aura in Secure Systems Group (2018).
I did my PhD at the School of Electrical Engineering and Telecommunications, UNSW, Australia and Data61 (CSIRO), Australia under the supervision of Dr. Aruna Seneviratne in the area of usable security. I was awarded an International TFS from UNSW and Data61 Scholarship to pursue my PhD. I was also associated with LiveLabs @ SMU, Singapore where I worked with Dr. Archan Misra and Dr. Youngki Lee during my internship in 2016-17 on breathing based user authentication.
I received my MSc in Computer Science from the University of Saskatchewan, Canada where I was part of the DISCUS lab and worked on simulating big data schedulers.
Research
Research interests
My work deals with performance measurements, mobile sensing, mobile health, on-device learning, and security of mobile systems.
Current Projects:
Covid-19 project: Large crowdsource data collection of audio sounds to build predictive models and contribute to the early diagnosis of COVID-19. (2020 - Ongoing) https://www.covid-19-sounds.org/en/
Google Research Grant based Project on using Deep Learning for embedded and resource constrained devices. (2020 - Ongoing)
Medical Adherence project: Working with Public Health department (University of Cambridge) to develop a scalable low-cost intervention to support medication adherence in people who are prescribed treatment for certain illnesses in primary care. (2018 - Ongoing)
Manchester United’s Brandon Williams would ideally fit Saints’ playing style and team chemistry. Image credit: AI Abacus.
Machine learning algorithms developed by computer scientists from the University of Southampton have pinpointed a transfer target that would most suit Southampton FC in the January transfer window.
The AI insight tips that England Under-21s’ Brandon Williams would be an excellent fit for the Saints and offer a long-term replacement to 31-year-old left-back Ryan Bertrand.
The analysis suggests that Williams’ playing style and chemistry with his prospective teammates are ideally suited to the Southampton FC, with the club being much better for his development than other reported loan options such as Newcastle United FC.
Brandon Williams has moved down the pecking order at Manchester United this season, however it remains to be seen if the club will be willing to let the English prospect leave on loan.
Southampton FC have also been linked with Manchester City's Oleksandr Zinchenko, but the AI scout warns the left-back would not be as good a fit and may require higher wages and fees due to his age.
Sentient Sports, a new company launched by postgraduate researcher Ryan Beal, has devised a set of algorithms based on cutting-edge AI research that can optimise the decision-making and scouting process when buying and selling players. These are being utilised by AI Abacus, another leading start-up founded by Ramm Mylvaganam who is a business leader in football analytics.
They are already winning business from major football teams across Europe. They use AI to analyse the player’s chemistry (how he fits in with the new teammates) and style fit (how he fits the new teams tactics) to provide decision making support to top teams.
"Professional team sport is a game of winners and losers and globally the stakes have never been higher," Ryan says. "Football, like other sports, has huge amounts of data associated with it, and some of this is already used by clubs to analyse the performance of their players. We are using our world-leading expertise to get more value out of that data and turn these insights into match-winning insights."
The Southampton experts are offering a teamwork algorithm that looks at how pairs and groups of players work together on the pitch to assess ‘player chemistry’; an algorithm that predicts the number of goals/assists a player will achieve; another that evaluates the suitability of a player in the style of play of a new team; and a final algorithm that looks at the cost benefit of players.
These algorithms are then used to predict how a player would perform if they were to play for a specified team.
"One of the key things our chemistry model shows for Saints is that the signing of Kyle Walker-Peters has been key this season,” Ryan says. “He has been shown to link up effectively with a number of the attacking players in the team and help boost the team overall."
Ryan is lifelong Southampton FC fan and is delighted with the club’s strong first half of the season which has placed the club in contention for European qualification. The club’s recent transfer dealings have all fitted well with Sentient Sports’ modelling.
"When Theo Walcott arrived on loan in the summer we looked at all the best options for him in the Premier League and Saints came out on top," Ryan explains. "We also identified Mohammed Salisu as one of the top young centre backs in Europe last season before he signed for Saints. So, I'm holding out hope that when he gets fit, he will be a very good long-term signing."
Read more about Sentient Sports in the latest edition of Re:action, the University's research and enterprise magazine. AI Abacus's work has been featured by the Sunday Times and the Daily Mail.
The Safeguard device can fit into a hard hat, armband or pocket.
Electronic engineers at the University of Southampton are helping optimise the performance of a new wearable technology for the construction industry.
Energy harvesting experts in the Smart Electronic Materials and Systems research group have partnered with leading UK construction technology company Mafic to further development of its Safeguard Internet of Things (IoT) solution.
Safeguard is a wearable device that can fit into a hard hat, armband or pocket. Using machine learning, the devices can recognise the unique movement patterns of users completing different tasks and record exactly what is happening.
The new collaboration, funded by a grant from the £5 million SPRINT (SPace Research and Innovation Network for Technology) programme, will exploit technology developed within the School of Electronics and Computer Science.
Dr Alex Weddell, Lecturer in the SEMS group, says: “The key objectives of this SPRINT project are reducing the power consumption of the Safeguard device, harvesting energy and optimising the charging of the hard hat. We have a long history of working in energy harvesting, including the design and development of power management subsystems for CubeSats.
"More recently, we have explored wireless power transfer technology - which also has applications in space. We are excited to explore how energy harvesting from light, movement, or temperature differences can be used to extend the battery life of Mafic's Safeguard IoT device."
The project will allow Mafic customers to be less reliant on a power source and deploy Safeguard into remote environments with minimal supporting infrastructure such as on-board commercial ships, in offshore environments, or in 'not-spots' or remote construction sites.
