2020
Two Postdoctoral Research Assistant/Associate positions open BIM2TWIN
Two positions are currently being recruited for, under the project "BIM2TWIN: Optimal Construction Management & Production Control".
- http://www.jobs.cam.ac.uk/job/28135/ - 2 years FTC
- http://www.jobs.cam.ac.uk/job/28140/ - 3 years FTC
The key responsibilities and duties are to: devise, implement, and test solutions for the BIM2TWIN project; disseminate the outcomes of the BIM2TWIN project and author reports to the project's sponsor; develop proposals for own or joint research; conduct individual and collaborative research; present and publish research work; and manage own research and administrative activities, with guidance if required. The post holder may also: assist in the supervision of students and provide limited supervision/instruction to classes. The post holder will also be expected to: liaise with the BIM2TWIN consortium partners and staff; liaise with colleagues and students; build internal and external contacts; administer meetings of the BIM2TWIN consortium; plan the use of research resources; plan and manage own research activity; and contribute to planning of joint research projects led by the principal investigator.
Deadline is on the 15th January 2021.
If you have any questions about this vacancy please contact: Dr I. Brilakis (ib340@cam.ac.uk) for queries of a technical nature related to the role or Dr Maria Carvalho (cit-admin@construction.cam.ac.uk) for the application process.
Submitted by administrator on Thu, 17/12/2020
Two PhD studentships open in the Digital Twins field
Two funded PhD studentships are currently open at the University of Cambridge (FIBE2 CDT) in the area of Digital Twins, and specifically in infrastructure digitisation. One focuses on Industrial Facilities and is co-sponsored by AVEVA and bp. The other focuses on Roads and is co-sponsored by Trimble Inc.. Both UK and overseas applicants are eligible. Overseas applicants are also encouraged to apply before 1 December to qualify for additional Cambridge University scholarships.
(1) EPSRC FIBE2 CDT PhD studentship with AVEVA and BP: Digitising Industrial Facilities - deadline 3 December 2020
(2) EPSRC FIBE2 CDT PhD studentship with Trimble: Digitising the Road Network - deadline 1 January 2021
Submitted by administrator on Thu, 19/11/2020
Railway Digital Twins conference paper receives a Best Paper Award at the 37th International Symposium on Automation and Robotics in Construction (ISARC)
A conference paper titled “Digital Twinning of Railway Overhead Line Equipment from Airborne LiDAR Data” authored by PhD student Mahendrini Ariyachandra and Dr Ioannis Brilakis received the Best Paper Award (best out of 221 papers) presented at the 37th International Symposium on Automation and Robotics in Construction. The research presented in this paper used a novel model-driven approach that exploits the highly regulated and standardised nature of railways to detect and reconstruct the geometric digital twins of Overhead Line Equipment in railways.
The objective of the annual ISARC Best Paper Awards is to recognize outstanding contributions to the body of theoretical or practical knowledge in automation and robotics in construction. The awards were presented at the yearly symposium on 28th October 2020. ISARC, which started in 1984 in Pittsburgh, serves as the annual meeting for the members of the International Association in Automation and Robotics in Construction (IAARC). The ISARC 2020 was held as an online symposium due to COVID-19 outbreak. For more details please visit the website here.
Submitted by administrator on Wed, 28/10/2020
Funding secured for research aimed at improving construction using Digital Twins
Dr Ioannis Brilakis, Director of the Department’s Construction Information Technology (CIT) Lab group (part of the Laing O’Rourke Centre for Construction Engineering and Technology) and visiting Professor Rafael Sacks, have been awarded grant funding to enhance building progress monitoring and quality control through Digital Building Twins.
Dr Ioannis Brilakis, Director of the Department’s Construction Information Technology (CIT) Lab group (part of the Laing O’Rourke Centre for Construction Engineering and Technology) and visiting Professor Rafael Sacks, have been awarded grant funding to enhance building progress monitoring and quality control through Digital Building Twins.
This €6 mil, 42-month grant is sponsored by the European Commission’s Horizons 2020 Framework Programme through its Digital Twins call for proposals. It is titled “BIM2TWIN: Optimal Construction Management & Production Control” and it aims to build a Digital Building Twin (DBT) platform for construction management that implements lean principles to reduce operational waste of all kinds, shorten schedules, reduce carbon footprint and costs, and enhance quality and safety. BIM2TWIN consists of a DBT platform that provides full situational awareness and an extensive set of construction management applications. It supports a closed loop Plan-Do-Check-Act mode of construction.
The grant team is composed of 17 partners. The (1) Centre Scientifique Et Tecqnique Du Batiment (CSTB) in France is the operational coordinator, supported by the (2) University of Cambridge; (3) Technion – Israel Institute of Technology; (4) Technical University of Munich; (5) Institut National De Recherche En informatique Et Automatique; (6) Fira Group; (7) Intsite; (8) Technalia; (9) Acciona; (10) Ruhr-University Bochum; (11) Spada; (12) University Polytechnic Delle Marche; (13) Unismart; (14) Orange; (15) Siemens; (16) IDP; (17) Aarhus University.
Dr Brilakis and his CIT Lab group have made pioneering scientific accomplishments in ‘twinning’ infrastructure scenes. For example, extracting a rich digital copy (Digital Twin) of real world infrastructure (such as buildings, industrial plants, bridges, tunnels, roads and railways), so that the Digital Twin can then be used for managing, maintaining and retrofitting the modelled assets.
| Dr Brilakis said: “Digital Twins allow us to automate and control many repetitive, low level construction tasks. This has the potential to significantly improve key performance indicators and the abysmal productivity performance of the construction industry.” |
The grant directly contributes to the mission and objectives of the Centre for Digital Built Britain, the Laing O’Rourke Centre for Construction Engineering and Technology, the National Research Facility for Infrastructure Sensing, and the Centre for Smart Infrastructure and Construction in Cambridge.
Submitted by administrator on Fri, 01/05/2020
PhD studentship opportunity on digitising industrial facilities (closing date: 3 December 2020)
here is a EPSRC FIBE2 CDT PhD studentship opportunity open, funded by AVEVA and BP: Digitising Industrial Facilities.
https://www.jobs.cam.ac.uk/job/26897/
Project Details: There is a growing awareness that industrial facility owners are managing very expensive and complex facilities with data that is too little or too outdated but most of all not integrated. This leads to suboptimal facility design, construction and operation. The Digital Twin concept offers a theoretically viable solution to this problem. However, we currently do not know (i) how to structure an industrial facility Digital Twin or (ii) how to cost-effectively construct and maintain it. This project aims to address these two knowledge gaps.
The Digitising Industrial Facilities project will focus on geometry and visual data of large scale energy assets to maintain feasibility. In this project, the student will: a) collaborate with the FIBE2 Partners and the Centre for Digital Built Britain (CDBB) to conduct a user requirements analysis for the purpose of deriving a geometric Digital Twin data structure; b) develop a matching method for comparing captured data with the geometric digital twin to construct and maintain it; c) if time allows, develop a data fusion method for linking other forms of data into the geometric digital twin.
Informal enquires about this post can be made to Dr Ioannis Brilakis (ib340@cam.ac.uk ).
For general enquiries, please email cdtcivil-courseadmin@eng.cam.ac.uk.
Submitted by administrator on Tue, 22/09/2020
2019
PhD studentships advertised as part of the Cloud-based Building Information Modelling (CBIM) training network
The following PhD studentships are available at the University of Cambridge on the European Commission-funded, Marie Sklodowska-Curie "CBIM" European Training Network (ETN).
The Cloud-based Building Information Modelling (‘Cloud BIM’/CBIM) training network aims to set the foundations for generating and exploiting digital twins of existing assets. It will make a step change in addressing the practical barriers to the concept and train capable Early Stage Researchers (ESRs). CBIM is funded by the EU Horizon 2020 program under the Marie Skłodowska-Curie Innovative Training Network call.
Three of the below studentships will be supervised by Dr Ioannis Brilakis, Director of the Construction Information Technology Laboratory (part of the Laing O'Rourke Centre for Construction Engineering and Technology in the University of Cambridge) and deputy coordinator of the CBIM training network.
Click on the links below for further details on each project.
| PhD Studentship - Marie Sklodowska-Curie Early Stage Researcher in Civil Engineering | Infrastructure Objects Detection Based on Cascaded Deep Learning Architectures Enhanced With Design Priors |
| PhD Studentship - Marie Sklodowska-Curie Early Stage Researcher in Civil Engineering | Updating model geometry from registered point cloud and image datasets |
| PhD Studentship - Marie Sklodowska-Curie Early Stage Researcher in Asset Management | Lifecycle Data Management |
| PhD Studentship (part-time)- Marie Sklodowska-Curie Early Stage Researcher in Civil Engineering | Infrastructure digitisation and gamification |
The closing date on applications for each of these projects is the 15th of February 2020.
For further details about the training network, visit the CBIM website.
Submitted by administrator on Wed, 13/11/2019
Infrastructure Computer Vision – Book available for pre-order
Pre-order the soon-to-be-released Infrastructure Computer Vision authored by Dr Ioannis Brilakis, Director of the Construction Information Technology (CIT) Laboratory - part of the Laing O’Rourke Centre for Construction Engineering and Technology in the University of Cambridge - and Dr Carl Haas, University of Waterloo Research Chair and Chair of the Department of Civil and Environmental Engineering.
Infrastructure Computer Vision delves into this field of computer science that works on enabling computers to see, identify, process images and provide appropriate output in the same way that human vision does. However, implementing these advanced information and sensing technologies is difficult for many engineers. This book provides civil engineers with the technical detail of this advanced technology and how to apply it to their individual projects.
| Pre-order: here |
| Expected Released Date: 6 December, 2019 |
Key Features
Infrastructure Computer Vision:
- Explains how to best capture raw geometrical and visual data from infrastructure scenes and assess their quality
- Offers valuable insights on how to convert the raw data into actionable information and knowledge stored in Digital Twins
- Bridges the gap between the theoretical aspects and real-life applications of computer vision
Readership
Professionals and students in Built Environment disciplines: asset owners, designers, contractors, subcontractors, and asset operators/maintainers
Authors
Dr Ioannis Brilakis completed his PhD in Civil Engineering at the University of Illinois, Urbana Champaign in 2005. He then worked as an Assistant Professor at the Departments of Civil and Environmental Engineering, University of Michigan, Ann Arbor (2005-2008) and Georgia Institute of Technology, Atlanta (2008-2012) before moving to Cambridge in 2012 as a Laing O’Rourke Lecturer. He was promoted to University Reader in October 2017. He has also held visiting posts at the Department of Computer Science, Stanford University as a Visiting Associate Professor of Computer Vision (2014) and at the Technical University of Munich as a Visiting Professor, Leverhulme International Fellow (2018-2019), and Hans Fischer Senior Fellow (2019-2021). He is a recipient of the 2019 ASCE J. James R. Croes Medal, the 2018 ASCE John O. Bickel Award, the 2013 ASCE Collingwood Prize, the 2012 Georgia Tech Outreach Award, the NSF CAREER award, and the 2009 ASCE Associate Editor Award. Dr Brilakis is an author of over 190 papers in peer-reviewed journals and conference proceedings, an Associate Editor of the ASCE Computing in Civil Engineering, ASCE Construction Engineering and Management, Elsevier Automation in Construction, and Elsevier Advanced Engineering Informatics Journals, and the past chair of the Board of Directors of the European Council on Computing in Construction.
Dr Carl Haas is the Chair of the Department of Civil and Environmental Engineering and a University Research Chair at the University of Waterloo in Canada. His interests include infrastructure computer vision, construction human-robotic systems, capital projects process analytics, construction productivity, and circular economy in the built environment. He serves on a number of editorial boards and on professional committees for organizations such as ASCE (American Society of Civil Engineers), NSERC and IAARC. He is a member of the Canadian Academy of Engineering and a Fellow of the ASCE. He was elected to the US National Academy of Construction in 2013. He received the ASCE Peurifoy Construction Research Award In 2015. In 2017, he received the University of Waterloo Award of Excellence in Graduate Supervision. In 2019, he received the ASCE Computing in Civil Engineering Award and the Canadian Society of Civil Engineers’ Alan Russell Award.
Submitted by administrator on Mon, 28/10/2019
PhD student Eva Agapaki shortlisted as finalist for IET innovation award
The Institution of Engineering and Technology (IET) innovation awards recognise and celebrate the very best new innovations across the breadth of science, engineering and technology. This year the IET received over 360 entries for the innovation awards and we are delighted to announce that they have shortlisted Eva Agapaki, Laing O’Rourke Centre for Construction Engineering and Technology PhD student working in the Construction Information Technology Laboratory, in the category of "Information Technology".
Large scale industrial facilities require frequent maintenance in order to avoid accidents that impede with production or cause environmental or other damage. To amend the large cost and inconvenience that onsite maintenance implies, one proposed solution is to develop a geometric Digital Twin (gDT) of the facility. However, costs and labor of modeling industrial factories counteract the value of gDTs. 90% of the modelling time is spent in processing real world laser scanned data, due to the complexity and the number of industrial shapes existing in these assets. As such, current conditions are not properly mapped, but also do not even have a designed model. We argue that the use of semantic (clustering by object type) and instance (clustering by individual object) layers gives contextual information that is useful for stakeholders, engineers and managers of the facility. However, these layers could not be generated so far due to the lack of large databases of richly annotated, laser-scanned industrial shapes as well as lack of appropriate inference rules in order to learn these shapes. Our CLOI innovation provides: (a) the largest richly annotated dataset of the most important industrial shapes (CLOI) that need automated modelling, (b) a procedure to intelligently parse large spaces and segment CLOI industrial shapes using deep learning networks and contextual inference rules. Our prototype takes as input spatial coordinates of laser scanned factories and for each coordinate outputs what type of object it belongs to (class), as well as which specific object instance it belongs to. Our pipeline is fully automated and readily applicable by the end user.
The winners will be announced at the Award Ceremony on 13 November at The Brewery in London.
Visit Eva’s profile for further details.
Submitted by administrator on Mon, 30/09/2019
Cloud-based Building Information Modelling (CBIM) - Call for PhD & Post Doc applications
Dr Ioannis Brilakis, Director of the Construction Information Technology Laboratory (part of the Laing O'Rourke Centre for Construction Engineering and Technology in the University of Cambridge) is the deputy coordinator of a new European research and training network in the area of Cloud-based Building Information Modelling - CBIM.
CBIM is funded by the EU Horizon 2020 program under the Marie Skłodowska-Curie Innovative Training Network call.
The network is offering 14 fully funded PhD positions for highly talented people who are eligible for study at any one of its partner universities. Each PhD student will be employed full time for three years at one of the CBIM partner universities or at one of the three CBIM beneficiary companies, while pursuing a PhD degree at one of the universities. We are also offering one funded Post Doc position at the Technion.
CBIM Universities:
· University of Cambridge, United Kingdom
· University College London, United Kingdom
· Technion – Israel Institute of Technology, Israel
· Technical University of Berlin, Germany
· University College Dublin, Ireland
Submitted by administrator on Fri, 27/09/2019
Construction Information Technology Laboratory
Exploring innovative opportunities for flexible project schedule design and execution.
After the launch of the research partnership between the University of Cambridge’s Construction Information Technology (CIT) Lab, nPlan and Kier, the Cambridge team continues to make progress in the exploration of the integrated schedule execution framework comprised of process benchmarking and delay-prediction tools. This research programme, sponsored by the InnovateUK grant, is titled “AI-Optimised Pathways for Schedule Execution (AI-OPSE)”. The project team aims to improve project management by developing an innovative schedule-learning platform which applies data science and machine learning to thousands of historic project schedules. The project will offer a unique and scalable solution for improving reliability and confidence in project planning. There are seven phases in this 24-month industrial research programme. The Cambridge team is in charge of framework development on learning optimal sequences of tasks and learning comparative project performance.
At present, the Cambridge team is designing and developing the prototype framework that uses an identified artificial intelligence (AI) model to read sequences of tasks based on high-level human input. The expected system output will be a probabilistic estimation of delays which can help to train a second AI model to rearrange the existing tasks for the purpose of minimising risks and possible delays. This novel approach will empower the automation of benchmarking and determination of task efficiency and project performances.
The research team has highly qualified members led by Professor Ioannis Brilakis, director of the CIT laboratory, which is part of the Laing O'Rourke Centre for Construction Engineering and Technology, in the Department of Engineering, University of Cambridge. Dr. Brilakis is a recipient of the 2019 ASCE J. James R. Croes Medal, and has authored or co-authored over 190 papers in peer-reviewed journals and conference proceedings. His research interests lie broadly in the field of construction engineering with a focus on construction automation and information technologies.
Dr Haiyan Xie (Sally) joined the research team as a Research Associate on the 16th of August 2019. Her recent research focuses on Smart City, Big Data Analytics, Artificial Intelligence in Construction and Operation, Simulation and Control, and Innovative Technology in Construction Engineering and Management. She is a Professor at Illinois State University (ISU), since 2013. She has over 75 published research articles, books, and reports. Recently, she received the International Outstanding Research Award of the Associated Schools of Constructionon April 12th, 2019. Dr. Xie has over 15 years of experience in teaching and research in the areas of construction materials and project management, as well as seven years of construction industry experience as a project manager. She has supervised multiple undergraduate and graduate students conducting research work and honours projects in renewable energy and construction management areas.
Dr Ying Hong joined the research team on the 1st of August 2019. She received a doctorate degree in civil and environmental engineering from the University of New South Wales in 2019. Her research interests cover the area of machine learning, deep learning, construction management, and optimisation. In the AI-OPSE project, Ying leads the development of Artificial Intelligent models. Her goal is to build up an intelligent construction industry.
For more information on this project, please contact:
Professor Ioannis Brilakis
Phone: +44(0) 1223 332718
E-mail address: ib340@cam.ac.uk
Submitted by administrator on Mon, 23/09/2019
PhD student Eva Agapaki recognised by Award for Outstanding Student Contribution to Education
Congratulations to Eva Agapaki who has been highly commended by a new award set up by the Cambridge Centre for Teaching and Learning to recognise outstanding contributions to education by students at the University of Cambridge.
In 2019, the Cambridge Centre for Teaching and Learning (CCTL) announced a new award to recognise the outstanding contributions that students themselves make towards enhancing educational practices across Cambridge - the Outstanding Student Contribution to Education Award (OSCEAs).
Eva Agapaki - a PhD student in the Construction Information Technology Laboratory, Laing O’Rourke Centre for Construction Engineering and Technology - was awarded a ‘Highly Commended’ certificate in the category of student representation - Departments/Faculties.
The award received over 100 nominations from undergraduate and postgraduate students for activities ranging from peer support, the development of inclusive practices and resources, and student representation in colleges and departments/faculties. The selection panel were very impressed by the quality and variety of nominations describing student efforts to enhance the excellence of Cambridge education and to improve the learning and teaching experiences of their peers through their voluntary or extracurricular activities.
For further award details, see the OSCEA website, here.
Submitted by administrator on Wed, 17/07/2019
Cambridge author team wins the 2019 J. James R. Croes Medal from the American Society of Civil Engineers
Dr Juan M. D. Delgado, Dr Liam Butler, Dr Ioannis Brilakis, Dr Mohammed Elshafie and Professor Campbell R. Middleton received the 2019 J. James R. Croes Medal. The medal was awarded on 18 June in Atlanta, USA by the American Society of Civil Engineers (ASCE) for the article: "Structural Performance Monitoring Using a Data-Driven and Dynamic BIM Environment", published in the May 2018 edition of the ASCE Journal of Computing in Civil Engineering.
The article presents an approach to develop data-driven Digital Twin systems for monitoring the structural performance of infrastructure assets in a dynamic manner. The article demonstrated this approach in a case study in which a steel rail bridge was instrumented with fibre optics sensors and modelled into a geometric Digital Twin. The sensor time series data were integrated with the geometry and used to monitor the structural performance of the bridge when trains pass along it. The prototype provides a dynamic indication of the load capacity used when trains cross the bridge.
Submitted by administrator on Tue, 18/06/2019
Professor Ioannis Brilakis receives a Han Fischer Senior Fellowship for his research in the field of Simulation and the Digital Twin
Dr Ioannis Brilakis, Laing O’Rourke Reader in Construction Engineering, was elected to receive a Hans Fischer Senior Fellowship that carries a €60,000 cash prize by the Institute for Advanced Study (IAS) at the Technical University Munich (TUM).
The award was made in recognition of Dr Brilakis’ contributions to the area of “Digital Twin for the Built Environment”. His Construction IT group has made pioneering scientific accomplishments in “twinning” infrastructure scenes, i.e. extracting a rich digital copy (digital twin) of real world infrastructure scenes, such as a) buildings and industrial plants, b) bridges, c) tunnels, d) roads and e) railways, such that the digital twin can be used for managing, maintaining and retrofitting the modelled assets.
Dr Brilakis said: “It is possible to model existing building and infrastructure assets today, yet the process is rarely performed in practice. Less than 2% of buildings in developed countries have an updated digital copy and much less for horizontal infrastructure. The reason is that modelling/twinning is extremely labour-intensive with the software tools currently available in the market. A bridge model takes several weeks to complete on average, while a complicated industrial plant often means over 6 months of work for a team of 10 or more modellers. This makes the modelling cost prohibitive when compared to the perceived value of the resulting Digital Twin.”
Submitted by administrator on Mon, 18/03/2019
New Artificial Intelligence project underway
The University of Cambridge’s CIT Lab is pleased to announce a new research project in partnership with nPlan and Kier Infrastucture and Overseas Ltd, following a successful grant application to InnovateUK. The £846,753 grant for the project titled “AI-Optimised Pathways for Schedule Execution” is a result of their bid to the Sector Deal-sponsored CFP on “Increase productivity, performance and quality in UK construction”. The proposed project seeks to develop a novel automated 'schedule learning platform' that applies data science and machine learning to thousands of previous project schedules, offering a unique scalable solution for improved certainty and confidence in project planning for future projects. The solution is based on thousands of previous construction projects, allowing the platform to learn across projects what was planned to happen and what actually happened, thus reducing the effect of human bias, subjectivity and inaccuracy. Schedule data is analysed, similar tasks and relationships are automatically grouped, with patterns drawn using Artificial Intelligence, enabling the platform to predict the most likely outcome for every task and provide optimal paths/recommendations to mitigate risks/delays. For more details, please see our Research pages.
For more news about this project see:
Gov UK News
Submitted by administrator on Mon, 11/02/2019
Watch Professor Brilakis discuss how to virtualise buildings and infrastructure at MIT’S Computer Science Department
n November, Dr Brilakis presented a lecture on ‘Virtualizing Infrastructure’ at the Computer Science and Artificial Intelligence Lab at Massachusetts Institute of Technology’s campus in Boston, USA.
A link to a recording of the lecture can be found at: https://youtu.be/fe472OnxgBk or at: https://replay.csail.mit.edu/recordings/1072
See to follow the abstract for this lecture:
Vertical and horizontal infrastructure is comprised of large assets that need sizable budgets to design, construct and operate/maintain them. Cost reductions throughout their lifecycle can generate significant savings to all involved parties. Such reductions can be derived directly through productivity improvements or indirectly through safety and quality control improvements. Creating and maintaining an up-to-date electronic record of these assets in the form of rich Digital Twins can help generate such improvements. Research is being conducted at the University of Cambridge on inexpensive methods for generating object-oriented infrastructure geometry, detecting and mapping visible defects on the resulting Digital Twin, automatically extracting defect spatial measurements, and sensor and sensor data modelling. The results of these methods are further exploited through their application in design for manufacturing and assembly (DfMA), mixed-reality-enabled mobile inspection, and proactive asset protection from accidental damage. Virtualization methods can produce a reliable digital record of infrastructure and enable owners to reliably protect, monitor and maintain the condition of their asset.
Submitted by administrator on Tue, 15/01/2019