Buildings, Energy and Environment Research Group
 

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Rob Shipman

Associate Professor, Faculty of Engineering

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Biography

Rob Shipman is an Associate Professor in the Faculty of Engineering, where his focus is on the research and development of technologies to support the current energy transition. His research activity includes the use of electric vehicle batteries to support vehicle-to-grid (V2G) and vehicle-to-building (V2B) applications; the development of smart energy communities; and demand-side response systems.

Prior to returning to academia, Rob spent a number of years in commercial roles at blue-chip companies including BT and E.ON. He has also been involved in several start-up companies in which he has held director-level positions and been a founder. A common theme throughout his commercial and academic work has been the use of data science and adaptive technologies such as artificial intelligence, complex systems, and evolutionary computation.

Rob Shipman is a part of the Buildings, Energy, & Environment Research group.

Research Summary

Rob's work at Nottingham centres on Energy Informatics in which he uses Internet of Things and machine learning technology to help address energy problems. He is also interested in applying these… read more

Selected Publications

Current Research

Rob's work at Nottingham centres on Energy Informatics in which he uses Internet of Things and machine learning technology to help address energy problems. He is also interested in applying these technologies for health applications.

Current projects include:

* Human Switch; researching machine learning approaches to pool a population of electric vehicle batteries to form a reliable storage resource that can be used to participate in grid services.

* Project SCENe; R&D of the IoT, cloud and analytics infrastructure for a community energy project in the Trent Basin area of Nottingham.

Past Research

His past work includes simulating consumer behaviour using artificial biochemistry, evolving telecommunications networks, developing adaptive data routing strategies, exploiting the properties of complex networks for improved search, evolving complex financial portfolios for 9 out of the world's top 10 investment banks and the development of a smart thermostat product for a "big-6" energy company.

  • SHIPMAN, R., ROBERTS, R., WALDRON, J., NAYLOR, S., PINCHIN, J., RODRIGUES, L. and GILLOTT, M., 2021. We got the power: Predicting available capacity for vehicle-to-grid services using a deep recurrent neural network: Energy Energy. 221,
  • SHIPMAN, R., WALDRON, J., NAYLOR, S., PINCHIN, J., RODRIGUES, L. and GILLOTT, M., 2020. Where will you park? Predicting vehicle locations for vehicle‐to‐grid: Energies Energies. 13(8),
  • RODRIGUES, L., GILLOTT, M., WALDRON, J., CAMERON, L., TUBELO, R., SHIPMAN, R., EBBS, N. and BRADSHAW-SMITH, C., 2020. User engagement in community energy schemes: A case study at the Trent Basin in Nottingham, UK: Sustainable Cities and Society Sustainable Cities and Society. 61, 15
  • SHIPMAN, R and GILLOTT, M, 2019. SCENe Things: IoT-based Monitoring of a Community Energy Scheme Future Cities and Environment. 5(1),
  • RODRIGUES, LUCELIA, GILLOTT, MARK, WALDRON, JULIE A, CAMERON, LEWIS, TUBELO, RENATA and SHIPMAN, ROB, 2019. Community Energy Networks in the Making: Project SCENe, Nottingham
  • SHIPMAN, ROB, NAYLOR, SOPHIE, PINCHIN, JAMES, GOUGH, REBECCA and GILLOTT, MARK, 2019. Learning capacity: predicting user decisions for vehicle-to-grid services Energy Informatics. 2(1), 1-22
  • WALDRON, JULIE, RODRIGUES, LUCELIA, GILLOTT, MARK, NAYLOR, SOPHIE and SHIPMAN, ROB, 2019. Towards an electric revolution: a review on vehicle-to-grid, smart charging and user behaviour
  • SHIPMAN, ROB and GILLOTT, MARK, 2018. A technology platform for monitoring homes within a community energy scheme: design and implementation challenges
  • SHIPMAN, R., GILLOTT, M. and NAGHIYEV, E., 2013. SWITCH: Case Studies in the Demand Side Management of Washing Appliances Original Research Article: Energy Procedia SWITCH: Case Studies in the Demand Side Management of Washing Appliances Original Research Article: Energy Procedia. 42, 153-162
  • GILLOTT, M. and SHIPMAN, R., 2013. A Wireless Sensor and Actuator Network for Domestic Automated Demand Response: 12th International Conference on Sustainable Energy technologies In: 12th International Conference on Sustainable Energy technologies.
  • SHIPMAN, R., GILLOTT, M. and NAGHIYEV, E., 2013. SWITCH: Case Studies in the Demand Side Management of Washing Appliances Original Research Article. International Conference on Sustainability in Energy and Buildings + Mediterranean Green Energy Forum In:
  • SHAO, LI, COLEMAN, MICHAEL, FOSTER, ROBERT, SHIPMAN, ROBERT, GILLOTT, M, HAO, Y, IRVINE, K and MUNOZ, MAX, 2013. Reduction of energy demand in buildings through optimal use of wireless behaviour information (Wi-be) systems In: International Conference on Applied Energy, ICAE, Pretoria, South Africa. 1-4
  • SHIPMAN, R, GILLOTT, M and NAGHIYEV, E, 2013. SWITCH: Case studies in the demand side Management of Washing Appliances Energy Procedia. 42, 153-162
  • SHIPMAN, ROBERT and GILLOTT, M, 2013. A Study of the Use of Wireless Behavior Systems to Encourage Energy Efficiency in Domestic Properties In: 12th international conference on sustainable energy technologies (SET-2013).
  • SHIPMAN, ROBERT A, 2011. Method and system for processing or searching user records
  • SHIPMAN, ROBERT A, 2010. Computer security system
  • SHIPMAN, ROBERT A, 2008. Design of communications networks
  • SHIPMAN, ROBERT A, 2008. Method and apparatus for routing data
  • SHIPMAN, ROBERT A, 2008. Method and apparatus for routing data with support for changing mobility requirements
  • BONSMA, E, KARUNATILLAKE, N, SHIPMAN, R, SHACKLETON, M and MORTIMORE, D, 2003. Evolving greenfield passive optical networks BT Technology Journal. 21(4), 44-49
  • SHIPMAN, ROB and SHACKLETON, MARK, 2002. Issues in designing a neutral genotype-phenotype mapping In: Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No. 02TH8600). 1360-1365
  • EBNER, MARC, LANGGUTH, PATRICK, ALBERT, JUERGEN, SHACKLETON, MARK and SHIPMAN, ROB, 2001. On neutral networks and evolvability In: Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No. 01TH8546). 1-8
  • UMRE, ASHISH, WAKEMAN, IAN, SHIPMAN, ROB and ROADKNIGHT, CHRIS, 2001. Biologically inspired algorithms and techniques in Ad-hoc networks
  • EBNER, MARC, SHACKLETON, MARK and SHIPMAN, ROB, 2001. How neutral networks influence evolvability Complexity. 7(2), 19-33
  • SHIPMAN, R., SHACKLETON, M. and HARVEY, I., 2000. The use of neutral genotype-phenotype mappings for improved evolutionary search BT Technology Journal. 18(4), 103-111
  • SHIPMAN, ROB, BOTHAM, PAUL and COKER, PAUL, 2000. Coupling developmental rules and evolution to aid in planning network growth BT Technology Journal. 18(4), 95-102
  • SHIPMAN, ROB, SHACKLETON, MARK, EBNER, MARC and WATSON, RICHARD, 2000. Neutral search spaces for artificial evolution: A lesson from life Artificial Life. 7, 162-169
  • SHACKLETON, MARK, SHIPMA, R and EBNER, MARC, 2000. An investigation of redundant genotype-phenotype mappings and their role in evolutionary search In: Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No. 00TH8512). 493-500
  • BONSMA, ERWIN, SHACKLETON, MARK and SHIPMAN, ROB, 2000. Eos�an evolutionary and ecosystem research platform BT Technology Journal. 18(4), 24-31
  • SHIPMAN, ROB, SHACKLETON, MARK and HARVEY, INMAN, 2000. The use of neutral genotype-phenotype mappings for improved evolutionary search BT Technology Journal. 18(4), 103-111
  • SHIPMAN, R., 1999. Genetic Redundancy: Desirable or Problematic for Evolutionary Adaptation? In: Artificial Neural Nets and Genetic Algorithms. 337-344
  • SHIPMAN, ROB, 1999. Genetic redundancy: Desirable or problematic for evolutionary adaptation? In: Artificial Neural Nets and Genetic Algorithms. 337-344
  • SHIPMAN, ROBERT, A Wireless Sensor and Actuator Network for Domestic Automated Demand

Buildings, Energy and Environment Research Groups

Faculty of Engineering
The University of Nottingham
University Park
Nottingham, NG7 2RD


telephone: +44 (0) 115 74 86257
email: BEE@nottingham.ac.uk