Jan S. Rellermeyer
I received my MSc CS in Distributed Systems from ETH Zürich, Switzerland, in 2006 and completed my PhD in Computer Science in the Systems Group at ETH in 2011. My thesis work was on Modularity as a Systems Design Principle.
In 2010, I did an internship at Microsoft Research in Redmond, WA in the eXtreme Computing Group and worked on an operating system design and energy management for the Intel SCC (Rock Creek) architecture.
After graduation, I joined IBM Research in Austin, TX where I worked as an RSM in the Future Systems and Next Generation Datacenters Group. I was part of the team that built and released the first mobile app that IBM ever published, IBM Mobile Systems Remote. This effort lead sparked the IBM Mobile First initiative. I was also a co-lead of the winning 2013 Global Technology Outlook (GTO) topic Software-Defined Environments. I then wored on workload-optimized systems for the POWER architecture where I leveraged features like coherently-attached flash through CAPI. This work is available on Github, In 2016, I worked on cloud and datacenter computing and in 2017 my group switched to working on machine learning and natural language processing.
In 2013, I became an Adjunct Assistant Professor in the Department of Computer Science at The University of Texas at Austin and taught the Programming Languages, Programming Languages Honors, and Principles of Computer Systems classes until 2017.
I was the Invited Researcher of the OSGi Alliance from 2008-2011 and contributed to several successful open source projects in the Eclipse and Apache Foundations. I am the project lead of the Eclipse Concierge project.
In 2017, my co-authors Gustavo Alonso, Timothy Roscoe, and I received the ACM/IFIP/USENIX Middleware Test of Time award for our 2007 paper R-OSGi: Distributed Applications through Software Modularization.
In 2019, I was appointed as a Master Coordinator for the Software Technology Track of the MSc in Computer Science program at TU Delft.
I am a member of the Faculty EEMCS Diversity and Inclusion Team (EDIT).
My research revolves around building and researching large-scale distributed systems for demanding applications like Big Data Processing and Distributed Machine Learning. I am interested in the architecture of systems and the resulting properties like performance, efficiency, scalability, reliability, and security.
If you are interested in writing your master's thesis under my supervision, please contact me through email.
Current PhD Students
Current Research Interns
Shivansh Dhar, University of Waterloo
Current Research Developers
PhD Committee Member
Scott V. Luedtke: Simulations of Laser-Plasma Experiments at the QED Frontier, The University of Texas at Austin, 2020, Committee: Björn Manuel Hegelich (UT Austin, Adviser), Todd Ditmire (UT Austin), Philip J. Morrison (UT Austin), James R. Chelikowsky (UT Austin), Jan S. Rellermeyer
Do Le Quoc: Approximate Data Analytics Systems, TU Dresden, 2018. Committee: Christof Fetzer (TU Dresden, Adviser), Pramod Bhatotia (University of Edinburgh, Adviser), Jan S. Rellermeyer
Amiya K. Maji: Dependability Where the Mobile World Meets the Enterprise World. Purdue University, 2015. Committee: Saurabh Bagchi (Purdue, Adviser), Elisa Bertino (Purdue), Anand Raghunathan (Purdue), Jan S. Rellermeyer
Current Master Students
Carsten Grießmann - Middleware for Illuminator (with Milos Cvetkovic, EE)
Federico Fiorini - Dynamic Memory Expansion
Jannes Timm - Self-Adaptive Thread Pool for Linux
Yuanhao Xie (thesis work partly conducted at ING as part of the AI for Fintech Lab) - Deploying ML Models at Scale
Mihai Voicescu - Programming Language Support for Big Data Processing
Michalis Vrachasotakis (thesis work partly conducted at ARM Research, Cambridge) - Making Kubernetes Scale for Edge Computing Applications
Past Master Students
Niket Agrawal - EDIRO: Edge-driven IoT Resource-aware Orchestration Framework for Collaborative Processing in Large Scale Internet of Things (co-supervised with Aaron Ding, Faculty TPM)
Janko Lopez - Blockchain-based crowdfinancing mechanisms for renewable energy projects
Dan Graur (thesis work partly conducted at ETH Zurich with Gustavo Alonso) - Evaluating and Improving Large-Scale Machine Learning Frameworks
Pandji Yosep Pandji Hario Wicaksono - Applicability Study of Artificial Intelligence to Forecast New Infrastructure Project Introduction Based on The Decision-Making Duration by The Government (Faculty TPM)
Apourva Parthasarathy - Reducing the JVM Startup Overhead in Big Data Systems
Stefan Stojkovski (EIT Digital, thesis work conducted at Rabobank and co-supervised with Dick Epema) - Addressing the challenges of Cloud Computing Adoption in an Enterprise Environment
Gabriel Vilén (EIT Digital, thesis conducted at Logical Clocks and co-supervised with Dick Epema) - Mounting External Storage in HopsFS
Master Thesis Committee Member
Chiel Bruin, TU Delft, 2020: Dynamix on the Frame VM, Committee: Eelco Visser, Casper Poulsen, Jan S. Rellermeyer, Peter Mosses
Mitchell Olsthoorn, TU Delft, 2020: FBase: Trustworthy code module execition. Committee: Johan Pouwelse, Jan S. Rellermeyer, Asterios Katsifodimos
Maryam Tavakkoli, TU Delft, 2019: Analyzing the Applicability of Kubernetes for the Deployment of an IoT Publish/Subscribe System. Committee: Dick Epema, Jan S. Rellermeyer, Fernando Kuipers, Kimmo Hätönen (Nokia)
Emmanouil Manousogiannis, TU Delft, 2019: Medical Concept Normalization in User-Generated Text. Committee: Alessandro Bozzon, Robert-Jan Sips (myTomorrows), Geert-Jan Houben, Jan S. Rellermeyer
Erwin de Haan, TU Delft, 2019: Automated FPGA Hardware Synthesis for High-Throughput Big Data Filtering and Transformation, Committee: Zaid Al-Ars, Peter Hofstee, Jan S. Rellermeyer, Johan Peltenburg.
Lars van Leeuwen, TU Delft, 2019: High-Throughput Big Data Analytics Through Accelerated Parquet to Arrow Conversion, Committee: Zaid Al-Ars, Peter Hofstee, Jan S. Rellermeyer, Johan Peltenburg.
Lars Wijtemans, TU Delft, 2019: Enabling FPGA Memory Management for Big Data Applications Using Fletcher, Committee: Zaid Al-Ars, Peter Hofstee, Jan S. Rellermeyer, Johan Peltenburg.
Bart Rijnders, TU Delft, 2019: 3D Gradient Printing of Energetic Multi-Materials. Committee: Koen Langendoen, Marco Zuniga Zamalloa, Jan S. Rellermeyer, Michien Straathof (TNO).
Niels van Kaam, TU Delft, 2019: Epoch alignment in stateful streams. Committee: Alessandro Bozzon, Asterios Katsifodimos, Georgios Gousios, Jan S. Rellermeyer.
Erwin van Eyck, TU Delft, 2019: The Design, Productization, and Evaluation of a Serverless Workflow-Management System. Committee: Alexandru Iosup, Jan S. Rellermeyer, Arie van Deursen, Alessandro Bozzon.
Laurens van den Bercken, TU Delft, 2019: Evaluating Neural Text Simplification in the Medical Domain. Committee: Geert-Jan Houben, Christof Lofi, Jan S. Rellermeyer, Robert-Jan Sips (myTomorrows).
Danilo Verhaert, TU Delft, 2018: An Architecture-Agnostic Protection Interface for the Tock Operating System. Committee: Koen Langendoen, Jan S. Rellermeyer, Mitra Nasri.
Mingfeng Li, TU Delft, 2018: Early DNA Analysis Using Incomplete DNA Data. Committee: Zaid Al-Ars, Arjan van Genderen, Jan S. Rellermeyer
Tim Hegeman, TU Delft, 2018: Experimental Performance Analysis of Graph Analytics Frameworks. Committee: Alexandru Iosup, Jan S. Rellermeyer, Andy Zaidman.
Olaf Maas, TU Delft, 2018: Towards Language Parametric Web-Based Development Environments. Committee: Eelco Visser, Peter Mosses (Swansea University), Jan S. Rellermeyer
Bas van IJzendoorn, TU Delft, 2018: Communicating with low latency peers - Building a low latency overlay in P2P networks. Committee: Johan Pouwelse, Jan S. Rellermeyer, Matthijs Spaan
Christos Kyprianou, TU Delft, 2018: Permissionless Banking API. Committee: Johan Pouwelse, Jan S. Rellermeyer, Zeki Erkin
Huang-da Chi, TU Delft, 2017: Parallelizing a Video Filterchain for Multi- and Many-core Systems. Committee: Zaid Al-Ars, Mauricio Alvarez-Mesa (Spin Digital), Jan S. Rellermeyer
ChangLiang Luo, TU Delft, 2017: Peer Discovery With Transitive Trust in Distributed System. Committee: Johan Pouwelse, Neil Yorke-Smith, Jan S. Rellermeyer
Past Honors Thesis Students
Matthew Allen: UT Austin, 2016: Parametric Polymorphism in the Go Language.