We are always looking for talent. If you would like to join the IBS Lab, please see the “Join the Team” below.


Dr.-Ing. Alexander von Lühmann
Head of Independent Research Group

R 4.045, Marchstr. 23, D-10587 Berlin

Alexander von Lühmann is currently the head of the independent research group “Intelligent Biomedical Sensing (IBS)” at BIFOLD, Machine Learning Dept, TU Berlin. He is also a visiting researcher at the Neurophotonics Center of Boston University (BU NPC) and Chief Scientific Officer at NIRx Medical Technologies. Previously, he was R&D director at NIRx, post-doc at BU NPC, visiting researcher at the Martinos Center of Harvard Medical School in Boston, USA, and Chief Technology Officer of Crely, a US-Singapore-based healthcare startup. He received his PhD (Dr.-Ing.) with distinction in 2018 from Technische universität Berlin (TU Berlin) and the M.Sc. and B.Sc. degrees in Electrical Engineering from Karlsruhe Institute of Technology (KIT) in 2014/11.
At the Intelligent Biomedical Sensing(IBS) Lab, Alex' research focuses on machine learning and instruments for comprehensive brain-body monitoring. The IBS lab develops miniaturized wearable neurotechnology and body-worn sensors for unobtrusive monitoring of the embodied brain in the everyday world. It uses machine learning on the multimodal sensor data, together with environmental context information, to contribute to a paradigm shift in individualized comprehensive understanding of physical and mental health: Toward intelligent assessment and treatment of physical and mental states and risk factors. Current focus is on instrumentation for diffuse optics and biopotentials (fNIRS, DOT, EEG, ExG) and novel approaches for modelling of physiology and physiological transfer functions using machine learning.

Dr. Eike Middell
Postdoctoral Researcher

R 4.050, Marchstr. 23, D-10587 Berlin

I graduated in astroparticle physics and gained much of my experience while working on neutrino telescopes in Siberia and Antarctica. These experiments instrumented large bodies of water and glacial ice with optical sensors to detect the faint light created by cosmic-ray particles interacting with matter. Subsequently, I transitioned to the field of neuroimaging with a focus on improving the digital signal processing of functional near-infrared spectroscopy (fNIRS) imagers, specifically in the context of assessing side-effects and potential improvements of deep brain stimulation for Parkinson's disease. Eventually, my role in a small team involved overseeing the software development of a portable near-infrared spectrometer from conception to market release. Further on, as a freelancing scientific software developer I contributed to diverse projects, such as forecasting financial time series and improving the safety of industrial plants by using spectroscopic measurements from remote sensors to infer the distribution of leaked gas clouds.
My research interests lie at the intersection of the physical measurement process in functional near-infrared spectroscopy (fNIRS), the inverse problem of image reconstruction as well as the application of machine learning methods on multimodal sensor data to improve the utilization of physiological information during data analysis. As the team's lead software engineer, I am particularly interested in constructing reproducible data processing pipelines that can ensure the reliability and replicability of fNIRS data analysis.

Nils Harmening
Doctoral Researcher

R 4.050, Marchstr. 23, D-10587 Berlin

Nils Harmening received his master's degree in Physics at Freie Universität Berlin in 2017 with a focus on nonlinear dynamics, biophysics and climate science. Since 2019 he is working on enhancing human head models for EEG and fNIRS data analysis and image reconstruction improvement using Photogrammetry and Electrical Impedance Tomography (EIT).
Brain-Computer Interfaces, Electrophysical modeling of the human head, Electrical Impedance Tomography (EIT), Inverse EIT Problem, Deep Learning for inverse problems

We have several researcher positions open. You will find more PhD/PostDocs here soon.


Jacky Behrendt
Student Research Assistant – Analysis & ML

R 4.039, Marchstr. 23, D-10587 Berlin

I am a Master's student in mathematics at Technische Universität Berlin. I earned a bachelor's degree in mathematics and computer science from TU Berlin. During my bachelor's, I focused on harmonic analysis and machine learning. For my Bachelor's thesis, I worked on neural networks and iterative algorithms for phase retrieval in ptychography. I also worked as a tutor in linear algebra in the Math Department.
My research interests are broadly in harmonic and functional analysis. I am also very engaged in machine learning, neural networks, and deep learning. In particular, I am interested in applications of machine learning to model-based algorithms and in solving inverse problems.

Thomas Fischer
Student Research Assistant – Analysis & ML

R 4.039, Marchstr. 23, D-10587 Berlin

I did my bachelor's degree in computer science at the University of Jena. In parallel, I was enrolled in mathematics and took courses in probability theory and numerics together with the mathematics students. My bachelor thesis was in the area of machine learning, in particular variational inference and some graph theory. During my Bachelor's, I also served as a tutor for discrete mathematics. I am currently pursuing a Master's degree in Computer Science at TU, focusing on machine learning and data analytics.
I am interested in theoretical computer science and applied mathematics, especially machine learning, graph theory, computability theory, and algorithms. In particular, deep learning architectures such as CNNs, transformers, and graph neural networks fascinate me. I am also very interested in medicine and the human body, so I enjoy working with all kinds of medical data.

Masha Iudina
Rotation Student – fNIRS Analysis and eye tracking

R 4.039, Marchstr. 23, D-10587 Berlin

I hold a Bachelor's degree in Computer Science from the Polytechnic University of Saint-Petersburg, with a focus on Forward Error Correction coding theory. Currently, I am pursuing a Master's program in Computational Neuroscience at Technische Universität Berlin. In addition, I work as a Software Developer at NIRx Medizintechnik, contributing to the development and support of fNIRS Acquisition Software.

Filip Jenko
Master Student – Headmodelling

R 4.039, Marchstr. 23, D-10587 Berlin

I studied Electrical Engineering as my bachelor’s degree program, my master’s degree is in Biomedical Engineering. I am an Erasmus student from University of Ljubljana, Slovenia. I worked at Jozef Stefan Institute in Ljubljana, which was my introduction to the research field. The research topic I contributed to was motor learning under different conditions. We observed how well subjects learn new movements, depending on whether they know which movement is coming next, or if they know the sequence of the next movements.
I am interested in biomedical image analysis and combining it with a neural network in order to perform image diagnostics. I currently focus on using photogrammetry to improve fNIRS signal processing. My assignment is getting a 3D model (point cloud) of a head from a 3D scan. My other interests are motor learning and prosthetics development.

Christian Tesch
Student Research Assistant – Dev Lab

R 4.039, Marchstr. 23, D-10587 Berlin

I hold a bachelor’s degree in electrical engineering with a specialization on automation. Currently, I’m enrolled in a master’s program in data science. Throughout my bachelor’s I worked in the R&D Electronics and Gas Detection department of MSA Safety, while also working as a tutor for C programming at my university. At MSA Safety my focus was test design, automation, and analysis of mixed signal gas sensor systems.
As a hands on engineer, I enjoy solving problems that span the entire engineering stack. This includes areas such as hardware design, firmware development, and creating software and user interfaces. Work at the IBS lab allows me to combine many of my interests: creating hardware, performing measurements and data analysis.

We have several student assistant positions open. You will find more students here soon.

Join the Team

We are always looking for talent. If you want to join the team, there are several ways to do so:

  • As a researcher doing your PhD or PostDoc
  • Writing your Bachelor or Master Thesis
  • In a lab rotation
  • As a working student

If you want to learn more, visit the Get Involved page.