Prof Adam Barker

Professor

Researcher profile

Phone

+44 (0)1334 46 1621

Email

adam.barker@st-andrews.ac.uk

 

Biography

Adam Barker is a Professor of Computer Science at the University of St Andrews, where he works on distributed systems and cloud computing topics. He has spent large portions of his career in industry and has worked as a Research Scientist at Google on two separate occasions where he contributed to Borg and Google Cloud Platform (GCP).

Previously he held a Royal Society Industry Fellowship and was a Visiting Scholar at the University of California, Berkeley. Prior to obtaining a faculty position, he worked as a Research Fellow at the University of Oxford, the University of Melbourne, and the University of Edinburgh. Adam holds a PhD in Informatics from the University of Edinburgh.

Selected publications

• FoldFormer: sequence folding and seasonal attention for fine-grained long-term FaaS forecasting

  Darlow, L., Joosen, A., Asenov, M., Deng, Q., Wang, J. & Barker, A. D., 6 May 2023, EuroMLSys '23: proceedings of the 3rd workshop on machine learning and systems. Yoneki, E. & Nardi, L. (eds.). New York, NY: ACM, p. 71-77 7 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

• Open access

  Simcan2Cloud: a discrete-event-based simulator for modelling and simulating cloud computing infrastructures

  Cañizares, P. C., Núñez, A., Bernal, A., Cambronero, M. E. & Barker, A., 18 Sept 2023, In: Journal of Cloud Computing: Advances, Systems and Applications. 12

  Research output: Contribution to journal › Article › peer-review

• TSMix: time series data augmentation by mixing sources

  Darlow, L., Asenov, M., Joosen, A., Deng, Q., Wang, J. & Barker, A. D., 6 May 2023, EuroMLSys '23: proceedings of the 3rd workshop on machine learning and systems. Yoneki, E. & Nardi, L. (eds.). New York, NY: ACM, p. 109-114 6 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

• Adaptive brokerage framework for the cloud with functional testing

  Ceesay, S., Lin, Y. & Barker, A., 6 Dec 2021, UCC '21: Proceedings of the 14th IEEE/ACM International Conference on Utility and Cloud Computing Companion. New York: ACM, 6 p. 14

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

• Benchmarking and performance modelling of dataflow with cycles

  Ceesay, S., Lin, Y. & Barker, A., 6 Dec 2021, IEEE/ACM 8th International Conference on Big Data Computing, Applications and Technologies (BDCAT '21). ACM, p. 91–100 10 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

• A survey: benchmarking and performance modelling of data intensive applications

  Ceesay, S., Lin, Y. & Barker, A. D., 7 Dec 2020, 2020 IEEE/ACM International Conference on Big Data Computing, Applications and Technologies (BDCAT). IEEE, p. 67-76 10 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

• Open access

  Benchmarking and performance modelling of MapReduce communication pattern

  Ceesay, S., Barker, A. D. & Lin, Y., 27 Jan 2020, Proceedings 2019 IEEE International Conference on Cloud Computing Technology and Science (CloudCom 2019). Chen, J. & Yang, L. T. (eds.). IEEE Computer Society, p. 127-134 8 p. 8968864. (IEEE International Conference on Cloud Computing Technology and Science).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

• Open access

  Borg: the next generation

  Tirmazi, M., Barker, A., Deng, N., Haque, M. E., Qin, Z. G., Hand, S., Harchol-Balter, M. & Wilkes, J., 15 Apr 2020, Proceedings of the Fifteenth European Conference on Computer Systems (EuroSys '20). New York: ACM, p. 1-14 30

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

• Open access

  Exploring characteristics of inter-cluster machines and cloud applications on Google clusters

  Lin, Y., Barker, A. D. & Ceesay, S., 10 Dec 2020, The 4th Workshop on Benchmarking, Performance Tuning and Optimization for Big Data Applications (BPOD). IEEE Computer Society

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

• Open access

  FIFE: an Infrastructure-as-code based Framework for Evaluating VM instances from multiple clouds

  Lin, Y., Briggs, J. & Barker, A. D., 8 Dec 2020, 13th IEEE/ACM International Conferencce on Utility and Cloud Computing. IEEE Computer Society

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

 

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