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Centre for Digital Built Britain

 

Research Background

Didem cares about the future of the world and nature. She is a computer scientist with a Ph.D. in mechatronics, which can give you an idea about how much she loves to talk about the future and emerging technologies. She is a data person, always finds a way to talk about how important it is to know your data, use it to make decisions and at some point expect her to talk about art, visualizations and visual analytics. Didem is a person who does not hesitate to talk about inequalities and point out her ethical concerns. She dreams of a better world and actively works on improving inequalities regardless of their nature. She is an analytical thinker with a passion for design thinking, a researcher with a future perspective, an engineer who likes problems more than solutions and a teacher who likes to play during lectures. She is a good reader, sailor, divemaster, photographer and drone pilot.

CDBB projects involved with

Digital twins for smart infrastructure 

Future built environments

Research ambitions for CDBB

  • To provide guidelines and strategies for the built environment industry that will enable to create a sustainable future world.
  • To understand the role of digital twins and data in this rapidly changing world and provide a framework to build resilient, interoperable and sustainable smart infrastructure.
  • To identify the current needs of the existing infrastructure but also imagining what their role will be in an integrated, data-driven, digitalised and intelligent future world

Biography

Didem is an experienced researcher and holds a Ph.D. degree in mechatronics from KTH Royal Institute of Technology, Stockholm Sweden. Currently, she is a research associate at the University of Cambridge. She is associated with the Centre for Smart Infrastructure and the Centre for Digital Built Britain. Her research focuses on data-centric methods, methodologies and implementations for smart infrastructure and asset management. Earlier to this position, she worked at the Mechatronics Division of KTH where she taught research methodology and advanced mechatronics project courses, in addition to supervising several students on mechatronics and robotics thesis projects. Didem collaborated with universities and companies all around Europe through three EU-funded projects while conducting research on data and visual analytics for cyber-physical systems. Didem received a bachelor’s degree as a computer engineer as the top student of her class with an exceptional track record, awarded with the best graduation project. She has been awarded the best conference paper from different scientific conferences. She also actively volunteered in different human rights organizations to increase the awareness of LGBT rights, gender equality, refugee rights, and animal rights. She has been interviewed by several blogs, magazines, newspapers and attended television programs to discuss women in technology and engineering, to motivate girls to choose STEM disciplines and to increase the awareness on sustainability and equality related issues.

Research

Digital Twin and Computer Vision Techniques for Infrastructure Monitoring and Construction Applications​

Didem's current research interest includes data modeling, interoperability assessment, data analytics, knowledge discovery, information visualization, visual analytics, and cyber-physical systems. Didem’s research focuses on blending systems thinking, future studies and design thinking approaches to develop methods, methodologies and implementations for the purpose of overcoming interoperability, complexity and sustainability challenges related to cyber-physical systems such as smart infrastructure systems, autonomous vehicles and collaborative robots. She uses data, visual analytics and digital twins to improve the interoperability between these systems, to make these systems more understandable and to develop sustainable systems for a better future. 

 

Publications

Key publications: 
Other publications: 
Research Associate

Affiliations

Classifications: