Category Archives: Talks

Upcoming talk at Trends in Functional Programming 2018

As part of my work at the Fraunhofer-Chalmers Research Centre for Industrial Mathematics, I have been working on a platform for distributed data analytics. I will present one facet of it, updating code on client devices without restarting them, at the upcoming conference Trends in Functional Programming 2018, which will take place from June 11 to June 13 at Chalmers University of Technology in Gothenburg, Sweden.

The abstract is reproduced below. Note that this is a work-in-progress paper or an extended abstract, depending on how you want to call it.

Active-Code Reloading in the OODIDA Platform
Gregor Ulm, Emil Gustavsson, Mats Jirstrand
Fraunhofer-Chalmers Research Centre for Industrial Mathematics, Sweden

The OODIDA (On-board/Off-board Distributed Data Analytics) Platform has been designed for distributing concurrent data analysis tasks to a network edge devices that are connected to a central server. It has been implemented in Erlang and Python. Its focus is the automotive industry, even though it is, in principle, a general solution. The heavy lifting is performed by edge devices. In contrast, the central server mostly performs supplementary tasks. One practical issue is that some data analytics tasks, for instance explorations of machine learning algorithms, do not lend itself well to the paradigm of deploying a new software installation to the edge device as it is both more time-consuming and inconvenient, due to the necessity of having to restart the applications that are executed on an edge device. As a response to this problem, we developed a solution for reloading active code on the client, which means that a data analyst using the OODIDA platform can define a custom function in Python and use it for local aggregations on the affected edge devices. This makes OODIDA even more flexible. It also enables new use cases such A/B testing of algorithms or experimental explorations. In particular the latter would have been inconvenient when relying on the standard deployment model of updating the software run on client devices.

Two Talks at the Singapore Elixir and Erlang Meetup Group

I will give two talks at the Singapore Elixir and Erlang Meetup Group on Monday, 14 May 2018. Kaligo is hosting the event. Their address is 298 Jalan Besar #03-01, Singapore 208959, Singapore. In order to attend, join the Meetup group and bring an ID document. There is a separate event page on

Below you will find the event description in full.

Talks related to Distributed Data Analytics and Erlang in the Workplace

Gregor Ulm is an R&D Engineer from Sweden, working in industrial research. He is currently visiting Singapore and agreed to give two talks related to his work. One talk is on his current main project, an analytics platform for connected vehicles that has largely been implemented in Erlang. The other is on his experience with introducing Erlang in a mature organization.

• 6:45 pm: Snacks - Pizzas, drinks, mingling
• 7:10 pm: OODIDA: On-board/Off-board Distributed Data Analytics for Connected Vehicles
• 8:00 pm: Break
• 8:10 pm: Introducing Erlang in the Workplace: An Experience Report

Thanks for all the following volunteers:

Pizza Sponsor: Yojee.
Venue provider: Kaligo.
Anil Thaplar (@athaplar|
Grzegorz (@arnvald |

Speaker: Gregor Ulm, Research and Development Engineer at the Fraunhofer-Chalmers Research Centre for Industrial Mathematics (FCC), Gothenburg, Sweden


1. OODIDA: On-board/Off-board Distributed Data Analytics for Connected Vehicles
A modern connected vehicle generates dozens of gigabytes of data per hour, which implies that central data processing (off-board) of a fleet of connected vehicles is not feasible. Instead, a large part of data processing has to happen locally on the client (on-board). The OODIDA platform facilitates concurrent distributed data analytics. Its key feature is the ability to concurrently execute multiple distributed data analytics tasks on overlapping subsets of client devices. This talk gives an overview of OODIDA, which is largely implemented in Erlang, discusses design considerations, and highlights various use cases, ranging from the simple, such as filtering, to the more complex, such as coordinating and executing distributed machine learning tasks with a large number of client devices. OODIDA is an ongoing research project at FCC. It is carried out in collaboration with industry partners.

2. Introducing Erlang in the Workplace: An Experience Report
The number of developers with an interest in functional programming seems to easily outnumber the number of industry jobs that entail using functional programming in practice. However, you don't have to only use functional programming languages in your spare time! One approach to get a job as a functional programmer would be to launch your own startup or join one of the comparably few companies that prominently use a functional programming language. A different approach is to introduce a functional programming language in your own workplace. In this talk, I discuss how I introduced Erlang at FCC in early 2017, and got it adopted for a major project. Since then, we filled several internship positions and, much more importantly, very recently hired two full-time Erlang developers and thus actively grew the local Erlang community.

About Yojee (Pizza Sponsor)
Agile startup in Singapore building logistics software utilizing Block-chain, AI and Machine Learning to optimize and manage fleets.

What to bring