Mika Senghaas Avatar
Hi 👋🏻, I'm Mika. I am a master student and research assistant in data science at EPFL.


Navigating Indoors With Computer Vision: Using Deep Learning for Room-Level Indoor Localisation

In my bachelor thesis I investigated whether state-of-the-art deep learning architectures for image and video classification (CNNs, CRNNs, Transformers) can accuractely predict where a human is located in an indoor environment given only information from the camera feed.

Computer Vision
Deep Learning

Work & Publications


Advancing Homepage2Vec with LLM-Generated Datasets for Multilingual Website Classification

M. SenghaasL. CizinskyP. Nutter

Unlocking the Palate - A Data-Centric Approach to Understanding Beer Descriptors

M. SenghaasP. LardetL. CizinskyP. NutterC. Bastin

Benchmarking SOT Feature Transform for Biomedical Few-Shot Learning Tasks

M. SenghaasA. BarlaL. Cizinsky

Deep Learning Methods for Mutagenicity Prediction in Chemical Compounds

M. Senghaas

Navigating Indoors with Computer Vision - Deep Learning Approaches for Room-Level Indoor Localisation

M. SenghaasS. Grasshof


Custom Conditional-RNN for Novel Name Generation

M. Senghaas


Weighted Bipartite Graph Projection Methods for a GitHub Recommender System

Projects & Initiatives

Selected Lecture Notes

Reach me

© Mika Senghaas 2024