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CHRISTOPH JOHANN FEINAUER

CHRISTOPH JOHANN FEINAUER
Assistant Professor
Department of Computing Sciences

Courses a.y. 2022/2023

20605 MACHINE LEARNING II
30539 COMPUTER SCIENCE - MODULE 1 (INTRODUCTION TO COMPUTER SCIENCE AND PROGRAMMING)
30586 MACHINE LEARNING AND ARTIFICIAL INTELLIGENCE LAB

Courses previous a.y.

I teach a master course in advanced machine learning, one bachelor course in AI and one on programming using C.


Biographical note

I am an Assistant Professor of Computer Science at Bocconi University in Milan, Italy. I obtained my PhD in the context of the Marie-Curie program Netadis from the Polytechnic University of Turin, with research stays at the UPMC Paris and the KTH Stockholm. My work focuses on generative models for protein sequence data and explainable deep learning. After doing a postdoc in Martin Weigt’s group in Paris, I worked as a Machine Learning Scientist in a deep learning startup in Berlin and then joined Bocconi University in 2019.


Research interests

My research interests are mainly generative models for protein sequence models, protein design and explainable deep learning with applications for deep models trained on biological data. I am especially interested in the prediction of pathogencity of genomic mutations using deep learning and the interpretation of the results in terms of the underlying biology. I also work on the structure of loss landscapes of neural networks, using methods derived from statistical physics.


Selected Publications

Feinauer, Christoph; Lucibello, Carlo
Reconstruction of Pairwise interactions using energy-based models
JOURNAL OF STATISTICAL MECHANICS: THEORY AND EXPERIMENT, 2021

C, Feinauer; B. Meynard; C. Lucibello
Interpretable Pairwise Distillations for Generative Protein Sequence Models
NeurIPS, 2021

F. Pittorino; C. Lucibello; C. Feinauer; G. Perugini; C. Baldassi; E. Demyanenko; R. Zecchina
Workshop on Machine Learning in Structural Biology
2021

Pittorino, Fabrizio; Lucibello, Carlo; Feinauer, Christoph; Perugini, Gabriele; Baldassi, Carlo; Demyanenko, Elizaveta; Zecchina, Riccardo
Entropic gradient descent algorithms and wide flat minima
Proceedings of International Conference on Learning Representations, 2021

Feinauer, Christoph; Lucibello, Carlo
Reconstruction of pairwise interactions using Energy-Based Models
Proceedings of Machine Learning Research vol 145: 2nd Annual Conference on Mathematical and Scientific Machine Learning, 9999

M. Negri; D. Bergamini; C. Baldassi; R. Zecchina; C. Feinauer
Proceedings of Machine Learning Research.
2019

Schwarz, D., Kollo, M., Bosch, C., Feinauer, C., Whiteley, I., Margrie, T. W., Schaefer
Natural representation of composite data with replicated autoencoders.
Arxiv, 2018

Schwarz, Dietmar; Kollo, Mihaly; Bosch, Arles.; Feinauer, Christoph Johann; Whiteley, Iya; Margrie, Troy W.; Cutforth, Tyler; Schaefer, Andreas T.
Architecture of a mammalian glomerular domain revealed by novel volume electroporation using nanoengineered microelectrodes
NATURE COMMUNICATIONS, 2018

Cocco, Simona; Feinauer, Christoph; Figliuzzi, Matteo; Monasson, Rémi; Weigt, Martin
Inverse statistical physics of protein sequences: a key issues review
REPORTS ON PROGRESS IN PHYSICS, 2018

A. Couce; L. V. Caudwell; C. Feinauer; T. Hindré; P. Feugeas; P. Weigt; M. Tenaillon
Context-aware prediction of pathogenicity of missense mutations involved in human disease
Arxiv, 2017

Couce, Alejandro; Caudwell, Larissa Viraphong; Feinauer, Christoph; Hindré, Thomas; Feugeas, Jean-Paul; Weigt, Martin; Lenski, Richard E.; Schneider, Dominique; Tenaillon, Olivier
Mutator genomes decay, despite sustained fitness gains, in a long-term experiment with bacteria
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2017

Feinauer, Christoph; Szurmant, Hendrik; Weigt, Martin; Pagnani, Andrea
Inter-protein sequence co-evolution predicts known physical interactions in bacterial ribosomes and the trp operon
PLOS ONE, 2016

Feinauer, Christoph; Skwark, Marcin J.; Pagnani, Andrea; Aurell, Erik
Improving contact prediction along three dimensions
PLOS COMPUTATIONAL BIOLOGY, 2014

Baldassi, Carlo; Zamparo, Marco; Feinauer, Christoph; Procaccini, Andrea; Zecchina, Riccardo; Weigt, Martin; Pagnani, Andrea
Fast and accurate multivariate Gaussian modeling of protein families: predicting residue contacts and protein-interaction partners
PLOS ONE, 2014

Feinauer, Christoph J.; Hofmann, Andreas; Goldt, Sebastian; Liu, Lei; Máté, Gabriell; Heermann, Dieter W.
Zinc finger proteins and the 3D organization of chromosomes
Organisation of chromosomes, 2013