About me
I am Dr. Madhuleena Dasgupta, a computational neuroscientist and educator based in Hamburg. My work brings together brain science, mathematical modelling, scientific communication and teaching.
My academic journey
My route into computational neuroscience began with an MSc in Micro and Nano Systems at Technische Universität Chemnitz in Germany. That training gave me a foundation in modelling, systems and engineering at very small scales — and led naturally towards a question of extraordinary complexity: how can mathematical and computational methods help us understand the living brain?
I went on to complete a PhD in Computer Science (Health Informatics) at Liverpool Hope University in the UK, supported by a Vice-Chancellor’s Scholarship. My doctoral research investigated brainstem–thalamic circuitry, cholinergic signalling and computational markers associated with early visuomotor impairment in Alzheimer’s disease.
I am currently a Research Fellow with Liverpool Hope University’s School of Computer Science and the Environment. My research lies at the intersection of computational neuroscience and mathematical modelling, with a particular interest in neural-circuit dynamics, neurotransmitter-mediated processes and astrocyte–neuron networks.
Research
A biologically informed computational framework examining whether astrocytic mechanisms can partially restore synaptic transmission under cholinergic depletion, supported by in-vivo validation.
A computational study incorporating receptor-level cholinergic kinetics into a neural mass model of the thalamocortical visual pathway and identifying a pathway-specific change in model behaviour.
Why writing and teaching?
Interdisciplinary research constantly requires translation: between biology and mathematics, models and experiments, specialists and non-specialists.
That experience shapes both sides of my work. In scientific writing, I look for the clearest way to preserve complex meaning for a chosen audience. In teaching, I begin with what the learner understands and build carefully from there. Neither process is about making a subject artificially simple; it is about making the route through it visible.
Teaching experience
From 2017 to 2019, I worked as a Graduate Teaching Assistant at Liverpool Hope University, including delivering first-year Computer Science seminars. Working with students at the beginning of their university studies strengthened my commitment to supportive, approachable teaching.
Explore teaching and tutoringHow I work
Clear communication should preserve evidence, uncertainty and technical meaning rather than smoothing them away.
A journal reader, interested member of the public and first-year student need different routes into the same idea.
Whether editing a manuscript or teaching a learner, constructive questions help expose assumptions and strengthen understanding.
Selected credentials
I work with researchers and organisations on scientific communication, and with learners seeking supportive English and STEM tuition.