Lu Luque
Organiser · CRUK Scotland Institute, Glasgow
Dr Luciana Melina Luque is a cross-disciplinary scientist working at the interface of physics, mathematics, computation, biology, and immuno-oncology. She is currently an independent Cross-Disciplinary Fellow in Cancer Research at the Cancer Research UK Scotland Institute in Glasgow, where she combines computational and experimental approaches to study cancer–immune interactions, with a particular focus on CAR T-cell immunotherapy.
Lu began her academic career in physics, completing her undergraduate degree at the National University of Catamarca, Argentina, before undertaking a Master’s degree in Theoretical Physics at Aix-Marseille University, France, where she worked on topics related to Loop Quantum Gravity. She later completed a PhD in statistical physics and critical phenomena at the National University of La Plata and the Institute of Physics of Liquids and Biological Systems, developing numerical and Monte Carlo approaches to study complex systems. She subsequently expanded her experience in computational biology through postdoctoral work and research internships at the Institute of Physical Chemistry Blas Cabrera in Madrid, the University of Edinburgh, Harvard Medical School, and King’s College London. Her transition into cancer research brought these quantitative tools into immuno-oncology, where she developed agent-based models to investigate CAR T-cell dynamics and therapeutic strategies.
Her expertise spans several pillars of computational biomedicine, including mathematical and computational modelling, agent-based modelling, multiplexed image analysis, bioinformatics, machine learning, and artificial intelligence. She has worked with high-dimensional spatial technologies such as Imaging Mass Cytometry, CODEX, and IHC, as well as RNA-seq, allowing her to study cancer across biological scales — from tissue architecture and cellular neighbourhoods to intracellular regulation. Her current work is increasingly wet-lab integrated, allowing her to generate, analyse, and interpret biological data in close collaboration with experimentalists, clinicians, and translational partners.
Lu is particularly interested in building mechanistic, data-informed models that can help bridge the gap between laboratory research and clinical impact. Her collaborative experience spans academia, clinical research, and the private sector, reflecting her commitment to developing computational tools that are biologically grounded, clinically relevant, and ultimately useful for patients. Alongside her scientific work, she is an advocate for women and underrepresented groups in STEM, using her own path from theoretical physics to cancer research to promote visibility, inclusion, and supportive scientific communities.
