Recruitment

Prospective Graduate Students

Thank you for your interest! We are looking for Ph.D. candidates in areas of Cyber-Physical Systems, Mobile/Wearable Systems, Edge-AI and On-chip Intelligence.
Students with either a CS or EE background are highly encouraged to apply.

Candidates are expected to have:

(1) a good background in either computer hardware, mobile systems, or AI,

(2) a strong motivation towards academic excellence,

(3) and should be prepared for 3-4 years of concentrated work.

The following backgrounds are not essential but would be a big plus:

(4) Graduated with a Master's Degree from accredited colleges and universities.

(5) Published research articles as first author.

(6) Experience in developing cyber-physical, mobile, or wearable systems. 

(7) Experience in digital signal processing and/or machine learning.

Students in our team will build a diverse skill set in both system implementation and theoretical modeling. They will also acquire a broad knowledge of physiological sensing, mobile healthcare, wearable computing, edge AI, etc. Because of such unique strength, our team has publications and awards in highly selective venues such as MobiCom, MobiSys, SenSys, UbiComp, IEEE TMC, etc. We also have collaborations with people in Oxford, Cambridge, Imperial, Uni. of Massachusetts, and Uni. of Colorado that could help open up your research career after graduation.

Please refer to our publication list to get a general understanding of our research topics.
Please send your pre-application package, including a CV, a sample of publications, and IELTS/TOEFL, to Dr. Nhat (Nick) Pham (phamn@cardiff.ac.uk) if you are interested.

PhD Project Topics

(1) Enabling continuous, personalised stress quantification and management with a wearable system [FindaPhD]

Work-related stress and burnout cost the UK economy more than £28 billion, 23 million sick days, and 165,000 bed days for the National Health Service (NHS) per year [1]. Long-term unhealthy stress could also develop chronic negative effects on our body, such as increased anxiety and depression, degraded cardiovascular functions, reduced brain grey matter, and a weakened immune system [2]. This significantly burdens our workforce’s productivity, quality of life, and the NHS system. Thus, there is an imminent need for a system that could continuously monitor stress levels throughout the day and provide personalised feedback/relief to prevent chronic stress development and build resiliency. Additionally, the developed solution needs to be unobtrusive, socially acceptable, and able to invisibly weave into user’s daily activities. Unfortunately, existing solutions are yet to meet these requirements.

Aims. The project aims to investigate and develop a wearable system to continuously monitor human stress levels and provide a non-invasive, closed-loop, personalised biofeedback to relieve or manage stress. In particular, the project will focus on the following objectives.

(1) Explore the method to accurately and continuously track stress levels using various biosignals such as brainwaves, cortisol concentration, heart rate variability, breathing rate, bioimpedance responses, muscle tension, etc.

(2) Investigate and devise a non-invasive, personalised biofeedback technique and algorithms to manage or relieve stress based on the captured biosignals. Potential directions include vagus nerve stimulation, vestibular stimulation, somatosensory, phototherapy, or guided meditation.

(3) Develop a wearable hardware and form factor design that can facilitate both sensing and biofeedback functionalities. The form factor needs to be unobtrusive to daily activities and has the potential to integrate into everyday wearables such as earphones, clothes, hats, eyeglasses, etc.

(4)  Evaluate the developed system on human subjects to study the efficiency and usability of the proposed system.

[1]  AXA, “The true cost of running on empty”, 2023, https://tinyurl.com/2a3pfbre

[2] Mariotti, Agnese. "The effects of chronic stress on health: new insights into the molecular mechanisms of brain–body communication." Future science OA 1.3 (2015).

References.

[1] Mariotti, Agnese. "The effects of chronic stress on health: new insights into the molecular mechanisms of brain–body communication." Future science OA 1.3 (2015).

[2] Giannakakis, Giorgos, et al. "Review on psychological stress detection using biosignals." IEEE Transactions on Affective Computing 13.1 (2019): 440-460.

[3] Kim, Heena, et al. "Recent Advances in Multiplexed Wearable Sensor Platforms for Real-Time Monitoring Lifetime Stress: A Review." Biosensors 13.4 (2023): 470.

[4] Howland, Robert H. "Vagus nerve stimulation." Current behavioral neuroscience reports 1 (2014): 64-73.

[5] Pham, Nhat, et al. "WAKE: a behind-the-ear wearable system for microsleep detection." Proceedings of the 18th International Conference on Mobile Systems, Applications, and Services. 2020. 

Supervision team.

Dr Nhat (Nick) Pham (Lead supervisor), Dr Charith Perera

(2) Enabling highly energy-efficient computing for wearable/implantable computers by exploiting analogue and in-memory computing [FindaPhD]

There has been a sharp rise in the growth of wearable electronics in recent years, reaching over $186 billion globally by 2030 [1]. However, many long-term healthcare applications, e.g., epileptic seizure monitoring, microsleep detection, etc., have not been deployed due to limited energy and on-device computational power. In particular, low-power microcontrollers on smartwatches and wireless earbuds consume 1-100 mW while most flexible batteries only provide <5 mWh/cm2 and wearable bioenergy harvesters can only generate <1 mW/cm2 power [2]. Thus, there is an imminent need for a solution that can provide ultra-efficient computation while being universally deployable on various wearable/implantable platforms.

Analogue computing, such as in-memory and in-ADC (analogue-to-digital converters) computing is an emerging approach that tackles the fundamental bottleneck of all von Neumann computers, i.e., the need to move data back and forth between the computing and memory units, aka the “memory wall”. This bottleneck leads to an inherent inefficiency in power consumption and latency as the computing unit and memory bus always need to wake up from sleep mode for all the calculations. By blurring the boundary between computing and storage units, it is possible to achieve significant gains in computational efficiency. A similar effect could be observed in extremely energy-efficient human brains where memory and processing are tightly coupled with each other.

Aims: In this project, we will explore non-von Neumann approaches to overcome the “memory wall” by exploiting analogue properties of memory and ADCs to provide local computations without the need to wake the main CPU. In particular, the project will focus on the following objectives.

(1) Explore the methods to produce basic logical Boolean operations on memory or ADCs by exploiting their electrical properties and biosignals’ characteristics.

(2) Devise the algorithms to mitigate intermittent power loss on battery-less devices to maintain the correctness and progress of the computation.

(3) Develop a software-to-hardware abstraction layer and/or a compiler to provide advanced computations to software developers based on the basic logical Boolean operations.

(4) Simulate and evaluate the developed solutions on important computation tasks such as biosignal filtering and transformation, machine learning and neural network operations.

(5) Fabricate and deploy a prototyped system on practical use cases, such as epileptic seizure monitoring to study the efficiency and usability of the proposed solution.

[1] Grand View Research. Wearable Technology Market Size, 2023 - 2030. https://tinyurl.com/4t965e3w.

[2] Yin, Lu, and Joseph Wang. "Wearable energy systems: what are the limits and limitations?." National Science Review (2023).

References.

[1] Sebastian, Abu, et al. "Memory devices and applications for in-memory computing." Nature Nanotechnology 15.7 (2020): 529-544.

[2] Indiveri, Giacomo, and Shih-Chii Liu. "Memory and information processing in neuromorphic systems." Proceedings of the IEEE 103.8 (2015): 1379-1397.

[3] Gao, Fei, Georgios Tziantzioulis, and David Wentzlaff. "Computedram: In-memory compute using off-the-shelf drams." Proceedings of the 52nd annual IEEE/ACM international symposium on microarchitecture. 2019.

[4] Ulmann, B. "Why algorithms suck and analogue computers are the future." (2017).

[5] Pham, Nhat, et al. "PROS: an efficient pattern-driven compressive sensing framework for low-power biopotential-based wearables with on-chip intelligence." Proceedings of the 28th Annual International Conference on Mobile Computing And Networking. 2022. 

Supervision team.

Dr Nhat (Nick) Pham, (Lead supervisor), Dr Charith Perera, Prof Omer Rana

Funding

There are various sources of funding for PhD projects from the School of Computer Science and Informatics and UK research councils. Most of the studentships will cover the tuition fee and living expenses for 3.5 years (no tuition fee after 3 years). Prospective candidates are always welcome if they can secure their own funding sources.

Application deadlines

There are four intakes for the Ph.D. program each year, i.e., October, January, April, and July. However, if you want to apply for School scholarships, there is only one intake in October with the application deadline is 13 March. Details are available on the School's website.

UK research councils' studentships

EPSRC Doctoral Training Partnership to develop Distributedly Self-powered Wearables (Project 2):  ~£90k, 2024 - 2028, 100% home-fee + £18.6k PhD annual tax-free stipend for 3.5 years. Additional funding to supplement international fees is also possible.

School Scholarships (UK + International)

The School offers fully-funded scholarships (Deadline: 13 March) for outstanding applicants (both UK and international students). The scholarships are competitive, so it will always be good to reach out to me early to prepare the application.

China Scholarship Council (CSC) + Cardiff University 

Deadline: 30 November 2023 with the School of Computer Science and Informatics @ Cardiff (Apply here). The China Scholarship Council (CSC) predominantly funds Chinese university students to study overseas for PhD degrees in the fields of science and technology, but will also consider disciplines in the humanities. CSC awards typically cover airfares and living costs for up to four years. The School will nominate up to 10 candidates.

Commonwealth Scholarship

Commonwealth Scholarships enable talented and motivated individuals to gain the knowledge and skills required for sustainable development and are offered to citizens from low and middle-income Commonwealth countries. More info and application can be found here.

Teaching Associate + Part-time PhD (UK students or visa holders)

The School also often recruits teaching associate posts with a part-time PhD opportunity (6-year program). As it is restricted by Visa requirements, it is currently open to candidates who already have work permits in the UK. The TA posts will usually be advertised in August.

Current TA advertisement (closed on 22/9/2023)