Catalogue of Possibilities / Supervisors

Dr Dongzhu Liu she/her

Mutual enhancement: environmental sensing and wireless communication in synergy

Lecturer

School of Computing Science

Research interests:

Multimodal sensing, Environmental awareness, Wireless communication, Integrated sensing and communication, Edge intelligence, Task-oriented communication, Deep learning, Signal processing, High-mobility networks, Generative AI

Research fields:

Wireless communications, Sensor networks, Machine learning, Computer vision, Signal processing, Environmental science, Robotics, Embedded systems, Data science, Control systems

Mission Priority Areas

Why do you want to join the DiveIn community?

I am excited to join the DiveIn CDT community because it aligns strongly with my research vision and values. My work on multimodal sensing and intelligent wireless communication directly contributes to building data-driven technologies that adapt to and interact with complex environments — a core mission of DiveIn. What draws me most to DiveIn is its interdisciplinary and collaborative ethos, which unites researchers from diverse disciplines to address real-world challenges in areas such as environmental resilience, infrastructure monitoring, and inclusive technology design. The community’s emphasis on people-centred, impactful innovation resonates with my goal of developing communication systems that are not only technically efficient but also socially and environmentally responsible. DiveIn’s training model, which blends technical excellence with societal engagement, offers a unique platform to co-create PhD projects that cut across sensing, communication, and systems thinking. I look forward to contributing to and learning from this vibrant, interdisciplinary network of scholars and innovators.

Personal profile:

My group works on areas including multimodal sensing, integrated sensing and communication (ISAC), edge intelligence, and task-oriented learning. A key strand of our work explores distributed Bayesian learning, which allows us to quantify model uncertainty in federated or decentralized settings — vital for decision-making in safety-critical and low-trust environments. We combine tools from wireless signal processing, deep learning, and probabilistic modelling, and apply them in domains such as smart cities, environmental monitoring, and next-generation wireless systems.

I actively seek interdisciplinary collaborations that connect computing, signal processing, environmental science, and robotics. I’m particularly interested in co-designing systems where communication infrastructure and environmental awareness inform each other, and where machine learning is made both reliable and deployable in the real world.

As an early-career academic, I currently supervise three funded PhD students, with another joining in October 2025. All students are supported by full scholarships and engaged in cutting-edge research at the intersection of communication and intelligence. I take a collaborative, supportive approach to supervision, balancing structured guidance with the freedom to explore and innovate.

Equity, diversity, and inclusion are core to my academic values. As a female researcher in a male-dominated field, I am committed to supporting and mentoring female students. I actively encourage women to pursue PhDs in computing and engineering, and strive to create an inclusive, respectful, and empowering research environment.

Outside of academia, I am a keen amateur badminton player and enjoy road trips, especially those that let me explore nature and new places with my family. These moments recharge my energy and often give me fresh perspectives on my research. I believe that research should be both technically excellent and socially meaningful — and the CDT community offers an inspiring environment to help co-create that future.

https://www.gla.ac.uk/schools/computing/staff/dongzhuliu/