Jakob Macke was appointed as Professor for "Machine Learning in Science" at Eberhard Karls University Tübingen, Faculty of Mathematics and Natural Sciences on May 01, 2020. The W3 professorship has been set up within the framework of our Cluster of Excellence "Machine Learning: New Perspectives for the Sciences". Jakob studied mathematics at the University of Oxford. After his studies, he worked as a doctoral student at the Max Planck Institute for Biological Cybernetics in Tübingen, as a postdoc at the Gatsby Unit at University College London and as a Bernstein Fellow at the Max Planck Institute in Tübingen. From 2015 to 2018, he was Max Planck Group Leader at the Caesar Research Centre in Bonn, and from 2017 he was also professor at the Centre for Cognitive Science at the Technical University of Darmstadt. From 2018 to 2020, Macke was Professor of Computational Neuroengineering at the Technical University of Munich. From 2013 to 2018 he was a member of the Young Academy at the German Academy of Sciences Leopoldina. TwitterWebsite


Franziska Weiler, Administrative assistant. I studied multilingual management and started to work at the University in March 2017. My first two jobs were at the Central Administration. I have been working for Prof. Dr. Philipp Hennig and his Chair Methods of Machine Learning since July 2018 and joined the MackeLab in July 2020. I am responsible for all kinds of things here, among them Human Resources, Purchasing and Financing.


PostDocs

Pedro Gonçalves (Caesar Bonn). I joined the lab as a postdoc in January 2016. I am broadly interested in building biologically constrained theoretical models (combining methods from dynamical systems, statistical physics and machine learning) to guide new experiments and ultimately refine the models to further our understanding of neural systems. Before joining the lab, I was a postdoctoral research fellow working with Maneesh Sahani at the Gatsby Computational Neuroscience Unit, UCL. My PhD was supervised by Christian Machens at École normale supérieure in Paris. Twitter, Website

Richard Gao I joined the lab as a postdoc in the middle of a pandemic (Jan 2021). My overarching goal is to better connect neurobiology with brain dynamics, and eventually to cognition, so that we can make inferences in the reverse direction for better diagnoses and interventions. I currently work with simulation-based inference tools and mechanistic models of neural circuits to achieve that. My broader interests lie in model-discovery for dynamical systems using both parametric and non-parametric approaches. I'm from Toronto and I did my PhD in sunny San Diego with Bradley Voytek. Twitter, Website


PhD Students

Michael Deistler I joined the lab as a master's student in March 2019 and then continued in the lab as a PhD student. I develop machine learning tools for neuroscience reseach and work on algorithms for simulation-based inference. Twitter, Github, Website

Auguste Schulz I joined the lab as a PhD student in fall 2019. I am working on state-space models for neuroscience, in particular on sequential variational autoencoders for neural population activity and behaviour.

Janne Lappalainen I joined the Macke Lab in Tübingen in October 2020 as a PhD student and will investigate visual representations in the human brain and in artificial neural networks using new tools from Deep and Machine Learning.

Poornima Ramesh

I joined the lab as an internship/masters student in 2016, working on statistical models for neural data. I started my PhD with the lab in 2018. I work on Generative Adversarial Networks (GANs) and their uses for modeling neural data and for simulation-based inference.

Jan-Matthis Lueckmann

I studied Neuroscience in Amsterdam, Bordeaux, and Berlin for my Masters, and joined the lab in October 2014. I work on simulation-based inference: comparing existing and developing new algorithms, as well as applying them to mechanistic models of neuronal dynamics. Twitter, Website

Artur Speiser

I joined the lab as a PhD student in 2016. I have focused on applying deep learning and generative modeling to analyze microscopy data for neuroscience and biology applications.

Jan Boelts (TU Munich) I joined the lab as a master student in 2017, working on Bayesian model comparison for intractable models, and continued as a PhD student 2018. Since then, I am working on inferring rule of synapse formation in large intractable connectomics models, and on algorithms for simulation-based inference. Twitter, Github


Student Assistants 

Matthijs Pals I joined the lab in September 2020 for an internship as part of my Masters in Neuroengeering at TU Munich. The focus of my project is studying oscillations in Working Memory using Recurrent Neural Networks.  LinkedIn

Ole Wenzel I joined the lab in March 2020 for my Master Thesis on Simulation-Based Inference for Cognitive Models. I pursue to promote (neuro)science with machine learning methods.

Tharanika Thevururasa

I joined the lab in March 2021 as a student assistant during my Bachelor's studies. I support the lab by maintaining a database of neural activity.
 


PhD Students Munich & Bonn 

Franziska Gerken (TU Munich) I am a PhD student of the Dynamic Vision and Learning group at TU Munich, supervised by Prof. Leal Taixe. Im am working with the Mackelab on the joint project "Deep Human Vision". I am working on deep learning methods to study how the human brain is encoding visual information.

Alana Darcher (University Hospital Bonn) In March 2019, I joined MackeLab as a master's student to study how human medial temporal neural populations track naturalistic stimuli over time. I continued with the same project as a PhD student in Florian Mormann's group in Bonn, co-supervised by Jakob Macke. Twitter, Github, Website


Master Students

Cansu Sancaktar I joined the lab in March 2020 for my Master’s thesis and I’m working on state space models to extract low-dimensional dynamics from neurophysiological data.

Anastasia Lado 

I joined the lab as a Master's student in January 2021. The focus of my project is gamma oscillations and functional properties of neurons in MTL.

Manuel Glöckler 

I joined the lab as a Master's student in March 2021. The focus of my work is to explore variational methods for simulation-based inference.

Jonas Beck 

I joined the lab in April 2021 as part of my Master's degree in Neural Information Processing at the Graduate Training Centre of Neuroscience. I aim to find out how data features constrain the parameter space of Hodgkin Huxley models using Simulation Based Inference and apply this to electrophysiolocigal recordings of M1 neurons.

Paul Fischer

I joined the lab in April 2021 as a Master's student to study the rewiring of the adult brain in fruit flies using probabilistic machine learning techniques.