Cedric Renggli

Cedric Renggli

I am a PhD candidate at ETH Zurich's DS3Lab, supervised by Ce Zhang.

My main research interest lies in all kind of human interactions in a machine learning ecosystem beyond labeling. This spans from defining engineering principles, such as continuous integration (CI), to comparison-based/preferential optimization algorithms for tuning hyper-parameters and providing efficient methods for model-selection. Additionally, I am working on different optimization techniques and systems relying on distributed machine learning algorithms to speedup the training process.

I hold a bachelor degree from the Bern University of Applied Sciences and received my MSc in Computer Science from ETH Zurich in 2018. My work on Efficient Sparse AllReduce For Scalable Machine Learning got awarded with the silver medal of ETH Zurich for outstanding master thesis.

My office is located at CAB E 61.2 and feel free to contact me by email cedric.renggli@inf.ethz.ch.



Lossy Image Compression with Recurrent Neural Networks: from Human Perceived Visual Quality to Classification Accuracy
Maurice Weber, Cedric Renggli, Helmut Grabner and Ce Zhang
ArXiv Preprint
SparCML: High-Performance Sparse Communication for Machine Learning
Cedric Renggli, Saleh Ashkboos, Mehdi Aghagolzadeh, Dan Alistarh and Torsten Hoefler
High Performance Computing, Networking, Storage and Analysis (SC) 2019
Ease.ml/ci and Ease.ml/meter in Action: Towards Data Management for Statistical Generalization (Demo)
Cedric Renggli*, Frances Ann Hubis*, Bojan Karlas, Kevin Schawinski, Wentao Wu and Ce Zhang
International Conference on Very Large Data Bases (VLDB) 2019 Demo
Distributed Learning over Unreliable Networks
Chen Yu, Hanlin Tang, Cedric Renggli, Simon Kassing, Ankit Singla, Dan Alistarh, Ji Liu and Ce Zhang
International Conference on Machine Learning (ICML) 2019
Continuous Integration of Machine Learning Models with ease.ml/ci: Towards a Rigorous Yet Practical Treatment
Cedric Renggli, Bojan Karlas, Bolin Ding, Feng Liu, Kevin Schawinski, Wentao Wu and Ce Zhang
Conference on Systems and Machine Learning (SysML) 2019
Speeding up Percolator
John T. Halloran, Hantian Zhang, Kaan Kara, Cedric Renggli, Matthew The, Ce Zhang, David M. Rocke, Lukas Käll and William Stafford Noble
Journal of Proteome Research 2019


The Convergence of Sparsified Gradient Methods
Dan Alistarh, Torsten Hoefler, Mikael Johansson, Nikola Konstantinov, Sarit Khirirat and Cedric Renggli (Authors ordered alphabetically)
Neural Information Processing Systems (NeurIPS) 2018


MPIML: A High-Performance Sparse Communication Layer for Machine Learning (Poster)
Cedric Renggli, Dan Alistarh and Torsten Hoefler
Neural Information Processing Systems (NIPS) 2017 Workshop: Deep Learning At Supercomputer Scale

MSc Thesis

Efficient Sparse AllReduce For Scalable Machine Learning
Cedric Renggli
Outstanding thesis award: Silver medal of ETH Zurich


Dept. of Computer Science
CAB E 61.2
Universitätsstrasse 6
8092 Zürich