When the expertise of a computer scientist and the ambition of a researcher meet the challenges of unraveling large multiomics datasets, interesting things can happen. In my case, it results in theoretically sound yet pragmatic methods in the realm of unsupervised machine learning on networks. Among other applications, these methods reliably infer explainable clusterings and trajectories, bridging the gap between classical machine learning and fundamental research.
Explore my research in network science offering practical insights into complex systems in the fields of neuroscience, single cell genomics and spatial transcriptomics.
Projects
Let me pick your interest in the some of the various projects I worked on
In this paper we described an unsupervised, optimal transport based approach to define a distance between graphs. The idea is to derive representations of graphs as Gaussian mixture models, fitted to distributions of sampled node embeddings over the same space. The Wasserstein distance between these distributions then yields an interpretable and easily computable distance measure, which can further be tailored for the comparison at hand by choosing appropriate embeddings.
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WIPAR stands for Widefield Imaging Pipeline for Analysis and Regression. It is a data pipeline for processing and analysing task-specific (widefield) calcium imaging data through neural decoding. Here, calcium activity is a proxy for neuronal activations. It provides stand-alone functionalities to visualize the data analysis as well as enabling the export of processed data for other visualization purposes.
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The continuous assessment of the impact on various stakeholders is an integral part of development cooperation projects. Nisaba is engaged in the digitization and simplification of these processes, developing a freely configurable software solution for this purpose. This solution is already being used within the projects Aktion Sodis and with initial pilot partners, and will be scaled further as soon as possible.
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If you like my work or research and want to collaborate or work together in some other form, drop me a message via mail or socials. Looking forward to hear from you!