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I'm Laurent Bindschaedler

I'm a Researcher working on Systems for Big Data, Graph Processing, and Machine Learning

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I am a Research Group Leader at the Max Planck Institute for Software Systems (MPI-SWS). I build systems for Big Data, Graph Processing, and Machine Learning. I am also interested in improving Systems with Machine Learning. Prior to joining MPI-SWS, I was a Postdoctoral Fellow at MIT CSAIL working with Prof. Tim Kraska. In 2020, I completed my Ph.D. at EPFL, Switzerland, advised by Prof. Willy Zwaenepoel. Before my graduate studies, I worked on my own Cloud Computing startup.

Research Interests

Big Data
Distributed Systems
Software Architecture
Machine Learning
Cloud Computing
Security & Privacy


AlterEgo: A Dedicated Blockchain Node For Analytics
In 7th International Workshop on Edge Systems, Analytics and Networking (2024). 
Qi Guo, Mahdi Alizadeh, Ali Falahati, and Laurent Bindschaedler.
[ PDF] [ BibTeX]
Unshackling Database Benchmarking from Synthetic Workloads
In Demo of the 39th IEEE International Conference on Data Engineering (2023). 
Parimarjan Negi*, Laurent Bindschaedler*, Mohammad Alizadeh, Tim Kraska, Jyoti Leeka, Anja Gruenheid, and Matteo Interlandi.
[ PDF] [ BibTeX]
Accurate Automatic Camera Calibration on Low-Quality CCTV Traffic Video Streams
In Proceedings of the International Conference on Computers and Automation (2022). 
Audhav Durai, Sankarshanaram Vempati, and Laurent Bindschaedler.
[ PDF] [ BibTeX]
Tesseract: Distributed, General Graph Pattern Mining on Evolving Graphs
In Proceedings of the 16th European Conference on Computer Systems (2021). 
Laurent Bindschaedler, Jasmina Malicevic, Baptiste Lepers, Ashvin Goel, and Willy Zwaenepoel.
[ PDF] [ Slides] [ Video] [ Short Video] [ Code] [ BibTeX]
Towards a Benchmark for Learned Systems
In Proceedings of the 12th International Workshop on Self-Managing Database Systems (2021). 
Laurent Bindschaedler, Andreas Kipf, Tim Kraska, Ryan Marcus, and Umar Farooq Minhas.
[ PDF] [ Slides] [ Video] [ BibTeX]
Hailstorm: Disaggregated Compute and Storage for Distributed LSM-based Databases
In Proceedings of the 25th International Conference on Architectural Support for Programming Languages and Operating Systems (2020). 
Laurent Bindschaedler, Ashvin Goel, and Willy Zwaenepoel.
[ PDF] [ Slides] [ Video] [ Code] [ BibTeX]
Rock You Like a Hurricane: Taming Skew in Large Scale Analytics
In Proceedings of the 13th EuroSys Conference (2018).
Laurent Bindschaedler, Jasmina Malicevic, Nicolas Schiper, Ashvin Goel, and Willy Zwaenepoel.
[ PDF] [ Slides] [ Video] [ Code] [ BibTeX]
Chaos: Scale-out Graph Processing from Secondary Storage
In Proceedings of the 25th Symposium on Operating Systems Principles (2015).
Amitabha Roy, Laurent Bindschaedler, Jasmina Malicevic, and Willy Zwaenepoel.
[ PDF] [ Slides] [ Video] [ Code] [ BibTeX]
Benchmarking X-Stream and Graphchi
EPFL Technical Report (2014).
Laurent Bindschaedler, and Amitabha Roy.
[ PDF] [ Code] [ BibTeX]
Big Brother Knows Your Friends: on Privacy of Social Communities in Pervasive Networks
In Proceedings of the 10th International Conference on Pervasive Computing (2012).
Igor Bilogrevic, Murtuza Jadliwala, Istvan Lam, Imad Aad, Philipp Ginzboorg, Valtteri Niemi, Laurent Bindschaedler, and Jean-Pierre Hubaux.
[ PDF] [ BibTeX]
Track Me If You Can: on the Effectiveness of Context-based Identifier Changes in Deployed Mobile Networks
In Proceedings of the 19th Annual Network & Distributed System Security Symposium (2012).
Laurent Bindschaedler, Murtuza Jadliwala, Igor Bilogrevic, Imad Aad, Philipp Ginzboorg, Valtteri Niemi, and Jean-Pierre Hubaux.
[ PDF] [ Slides] [ Code] [ BibTeX]
Making Mobile Augmented Reality A Reality
In Proceedings of the 13th International Conference on Human Computer Interaction with Mobile Devices and Services (2011).
Laurent Bindschaedler, Hendrik Knoche, and Jeffrey Huang.
[ PDF] [ Code] [ BibTeX]






Distributed Databases
Disaggregate Storage and Compute to Improve Throughput and Utilization
Hailstorm, disaggregation, compute, storage, distributed, database, key-value store, skew, compaction offloading, RocksDB, MongoDB, TiKV, TiDB, YCSB, TPC-C, TPC-E

Hailstorm is a drop-in replacement filesystem for existing distributed LSM-based databases that disaggregates storage from processing, thereby improving throughput and utilization. Hailstorm pools all storage devices at rack-level to reduce load imbance without resharding by allowing individual storage engines to utilize spare storage capacity and bandwidth. The system also addresses CPU load imbalance by allowing expensive compactions tasks to be outsourced to less utilized storage engines.





Taming Skew in Large Scale Analytics
Hurricane, big data, analytics, cluster computing, skew, high performance, task cloning, adaptive work partitioning, merging, repartitioning, load balancing, storage disaggregation, decentralized storage, bags, chunks, fine-grained partitioning, distributed scheduling, batch sampling, late binding.

Hurricane is a high-performance large-scale data analytics system that successfully tames skew in novel ways. Hurricane performs adaptive work partitioning based on load observed by nodes at runtime. Overloaded nodes can spawn clones of their tasks at any point during their execution, with each clone processing a subset of the original data.





Graph Analytics
Scale-out Graph Processing from Secondary Storage
Chaos, big data, analytics, graph processing, high performance, edge-centric, streaming partition, disaggregation, secondary storage, work stealing.

Chaos is a graph processing system for analytics on big graphs using small clusters. Chaos builds on the X-Stream single-machine graph processing system, but scales out to multiple machines. Chaos treats the aggregate storage of all machines as a single flat disk and uses work stealing to balance the load across nodes in the cluster. It exposes the familiar scatter-gather-apply programming model.

Work Experience

2022 -

Research Group Leader

Max Planck Institute for Software Systems

2020 - 2022

Postdoctoral Fellow

Data Systems Group, CSAIL

Host: Prof. Tim Kraska

2015 - 2020

PhD Candidate

LABOS, IC Faculty

Thesis Advisor: Prof. Willy Zwaenepoel

2014 - 2015

Scientific Assistant

LABOS, IC Faculty

2010 - 2011

Student Assistant

IC Faculty

2006 - 2018

IT Pioneer

Staff 1st Region — Swiss Armed Forces


2015 - 2020

PhD in Computer Science

2009 - 2011

Master in Computer Science

2006 - 2009

Bachelor in Computer Science

Awards and Achievements

Early Postdoc.Mobility — 2020
Awarded an Early Postdoc.Mobility Fellowship by the Swiss National Science Foundation. [ Link]
Best Video Award — ASPLOS Conference — 2020
“Hailstorm: Disaggregated Compute and Storage for Distributed LSM-based Databases” was voted best presentation at the ASPLOS’20 conference. [ Link] [ Watch]
Teaching Assistant Award — EPFL IC Faculty — 2017
Awarded by EPFL’s School of Computer and Communication Sciences for excellent contributions to teaching. [ Link]
Public Prize Winner — Exposure Movie Hackathon — 2017
Exposure is a 3-day hackathon that brings together scientists and filmmakers to create short science films. “Jenna & DANBOT”, our movie about Artificial Intelligence and Machine Learning was voted best film by the public. [ Link] [ IMDb] [ Watch]
PhD Fellowship — EDIC EPFL — 2015
Awarded by EPFL’s Computer and Communication Sciences Doctoral Program (EDIC). EDIC awards promising students a one-year fellowship. [ Link]
Round 1 Winner — Venture Kick — 2012
Venture Kick is an initiative to support Swiss startups with enough funding to kick-start their entrepreneurial success. Awarded a first round grant with LakeMind. [ Link]

Contact Me

Feel free to get in touch with me. I am always open to discussing new ideas, projects or opportunities.

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