Evolutionary Computation in Practice

ECiP 2017: Berlin July 17th 2017


In the Evolutionary Computation in Practice (ECiP) track, well-known speakers with outstanding reputation in academia and industry present background and insider information on how to establish reliable cooperation with industrial partners. They actually run companies or are involved in cooperations between academia and industry.

If you attend, you will learn multiple ways to extend EC practice beyond the approaches found in textbooks. Experts in real-world optimization with decades of experience share their approaches to creating successful projects for real-world clients. Some of what they do is based on sound project management principles, and some is specific to our type of optimization projects.

A panel of experts describes a range of techniques you can use to identify, design, manage, and successfully complete an EA project for a client. If you are working in academia and are interested in managing industrial projects, you will receive valuable hints for your own research projects.


  • S1 Bridging the gap between academia and industry: How to establish & continue cooperation with industrial partners
  • S2 “Real” real-world optimization: Best practice
    Talks & Discussions
  • S3 Ask the experts / Getting a job: What to do and what not to do


Nugent, Ronan

Senior Editor – Computer Science, Springer-Verlag.
Theoretical Computer Science, Natural Computing, Computational Intelligence, Artificial Intelligence, and Information Security and Cryptography

Kokot, Volker

MAGMA Gießereitechnologie GmbH

Shayani, Hooman

Hooman Shayani. Senior Principal Research Scientist. Autodesk, Ltd.

Hein, Daniel

Daniel Hein is a research scientist at Siemens Corporate Technology in Munich, Germany, working in the area of applied machine learning and reinforcement learning. He received his B.Sc. degree in Computer Science from the University of Applied Sciences Zwickau, Germany, in 2011 and the M.Sc. degree in Informatics from the Technische Universität München, Germany, in 2014. He is currently pursuing a Ph.D. in Informatics at Technische Universität München, Germany. His main research interests include evolutionary algorithms, particle swarm optimization, genetic programming, interpretable reinforcement learning, and industrial applications of machine learning approaches.

Rehbach, Frederik

Deb, Kalyan


Session Date Speaker Title Chair
S-1 17.07.2017 Deb Collaborations with industry E. Goodman
S-1 17.07.2017 Nugent Springer, TBA T. Bartz-Beielstein
S-1 17.07.2017 Kokot Integration of genetic Algorithms into a Simulationsoftware A. Fischbach
S-1 17.07.2017 Shayani Autodesk, TBA T. Bartz-Beielstein
S-2 17.07.2017 Hein Particle Swarm Optimization Policy (PSO-P) for Industrial Reinforcement Learning Problems A. Fischbach
S-2 17.07.2017 Rehbach Electrostatic Precipitator Optimization using a model-based Evolutionary Algorithm T. Bartz-Beielstein
S-3 17.07.2017 Mehnen, Goodman, Bartz-Beielstein Ask the experts / Getting a job E. Goodman


Dedicated to the discussion of issues related to the practical application of EC. Organized in cooperation with Synergy Project. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 692286.