This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 766186.

ESR1: Thiago Rios, (Brazil)

Project Topic: High-dimensionality and big-data models in learning-based optimisation methods.

Objectives: Develop novel learning algorithms for optimisation and design space exploration in high dimensional spaces integrating modelling techniques that use multi-domain knowledge. Benchmarking them on practical and academic benchmarks.

Degree/Qualification: Masters Mechanical Engineering at UFSC (Florianopolis, Brazil).

Hobbies/interests: Motorsports and cycling.

Personal Webpage: https://www.honda-ri.de/

ESR2: Sneha Saha, (India)

Project Topic: Constrained, multiple-criteria and preference-aware optimisation.

Objectives: To develop, analyse, evaluate and compare learning-based constrained and multi-objective constrained optimisation algorithms on both benchmarks and industrial problems.

Degree/Qualification: Integrated masters on Digital Media Technology, Delft University of Technology, The Netherlands, KTH Royal Institute of Technology, Stockholm.

Hobbies/interests: Painting, Exploring new places.

Personal Webpage: https://www.honda-ri.de/people/

ESR3: Sibghat Ullah, (Pakistan)

Project Topic: Uncertainty handling and robust design in learning-based optimisation.

Objectives: To develop, evaluate and compare self-tuning learning-based, multi-objective constrained optimisation algorithms on both benchmarks and industrial problems in dynamic environment, with uncertainty handling ability and robust design.

Degree/Qualification: MS Data Science, Sapienza University, Rome, Italy

Hobbies/interests: Football.

Personal Webpage: https://www.universiteitleiden.nl/en/staffmembers/sibghat-ullah#tab-1

ESR4: Duc Anh Nguyen, (Vietnam)

Project Topic: Automatic algorithm configuration for parameter tuning of modelling and optimisation algorithms.

Objectives: To develop, analyse, evaluate and compare algorithm configuration approaches for their application in the context of learning and optimisation.

Degree/Qualification: Masters in Information Technology Management, Vietnam National University, Vietnam

Hobbies/interests: Reading & sport

Personal Webpage: https://www.universiteitleiden.nl/en/staffmembers/anh-nguyen#tab-1

ESR5: Jiawen (Fay) Kong, (China)

Project Topic: Class imbalance classification through semi-supervised and active earning for experience-based optimisation.

Objectives: To develop, analyse, evaluate and compare novel class imbalance learning algorithms using semi-supervised and active learning ideas on both benchmarks and industrial problems.

Degree/Qualification: Master in Statistics, University of Nottingham, United Kingdom

Hobbies/interests: Translating English lyrics into Chinese, handmade bags by myself.

Personal Webpage: https://www.universiteitleiden.nl/en/staffmembers/jiawen-kong#tab-1

ESR6: Stephen Friess, (Germany)

Project Topic: Big data analytics through learning in the model space for experience computation.

Objectives: To develop, analyse, evaluate and compare novel methods for model generation, distance measures and model learning in the framework of learning in the model space on both benchmarks and industrial problems.

Degree/Qualification: Master of Science, Physics, Darmstadt University of Technology.

Hobbies/interests: Travelling.

Personal Webpage: https://stephensblog90.wordpress.com/

ESR7: Gan Ruan, (China)

Project Topic: Online learning in experience-based optimisation in dynamic and uncertain environments.

Objectives: To develop, analyse, evaluate and compare effective real-time online learning algorithms for concept drifts in a dynamic and uncertain environment on both benchmarks and industrial problems.

Degree/Qualification: Bachelor degree of Engineering and Master degree of Engineering, Xiangtan University, China

Hobbies/interests: Traveling, reading books, playing games.

Personal Webpage: http://www.escience.cn/people/gruan/index.html

ESR8: Giuseppe Serra, (Rome, Italy)

Project Topic: Text and social media mining with deep probabilistic models for product feature optimisation.

Objectives: To develop, analyse, evaluate and compare novel text mining methods for automatically detecting customers’ opinions on aspects and features of products from large collections of unstructured texts.

Degree/Qualification: Integrated masters on Digital Media Technology, Delft University of Technology, The Netherlands, KTH Royal Institute of Technology, Stockholm.

Hobbies/interests: Passionate about Music, Futsal (5-a-side football) Player

Personal Webpage: https://www.linkedin.com/in/giuseppe-serra-a70261120/

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