Dr Abhirup Ghosh

School of Computer Science
Assistant Professor in Computer Science

Contact details

Email
a.ghosh.1@bham.ac.uk
View my research portal
Address
University of Birmingham
Edgbaston
Birmingham
B15 2TT
UK

Abhirup Ghosh is an Assistant Professor in the School of Computer Science.

He is broadly interested in machine learning and privacy preservation problems related to sensing data recorded in phones and wearables. In particular, building systems to collaboratively learn in a resource efficient and private way using Federated Learning and Fully Distributed Gossip Learning. These are applicable to various applications: graph analysis, mobile-health, and mobility.

For more information, please visit Abhirup Ghosh’s Google Scholar page.

Qualifications

  • PhD in “Machine Learning and Privacy-preserving Algorithms for Spatial and Temporal Sensing” from the School of Informatics, University of Edinburgh (2019)
  • M.Tech in Computer Science and Engineering from Indian Institute of Technology, Bombay (IITB), India (2011)
  • B.E. in Information Technology from Jadavpur University, India (2009)

Teaching

  • Building Usable Software (University of Birmingham – 2023)

Assisted in:

  • Mobile Health (University of Cambridge – 2023)
  • Social and Technological Networks (University of Edinburgh – 2016 to 2018)

Research

Current interests:

  • Broadly in privacy preserving machine learning for sensing data from edge devices.
  • Federated Learning and Fully Decentralized Gossip Learning
  • Mobile Health
  • Mobility data analysis

Publications

Recent publications

Article

Ghosh, A, Puthusseryppady, V, Chan, D, Mascolo, C & Hornberger, M 2022, 'Machine learning detects altered spatial navigation features in outdoor behaviour of Alzheimer’s disease patients', Scientific Reports, vol. 12, no. 1, 3160. https://doi.org/10.1038/s41598-022-06899-w

Wang, H, Ghosh, A, Ding, J, Sarkar, R & Gao, J 2021, 'Heterogeneous interventions reduce the spread of COVID-19 in simulations on real mobility data', Scientific Reports, vol. 11, no. 1, 7809. https://doi.org/10.1038/s41598-021-87034-z

Conference contribution

Xia, T, Han, J, Ghosh, A & Mascolo, C 2023, Cross-Device Federated Learning for Mobile Health Diagnostics: A First Study on COVID-19 Detection. in ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)., 10096427, Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, IEEE, 2023 IEEE International Conference on Acoustics, Speech and Signal Processing, Greece, 4/06/23. https://doi.org/10.1109/icassp49357.2023.10096427

Hasthanasombat, A, Ghosh, A, Spathis, D & Mascolo, C 2023, Investigating Domain-agnostic Performance in Activity Recognition using Accelerometer Data. in Proceedings of the 2022 ACM International Joint Conference on Pervasive and Ubiquitous Computing. Proceedings of UbiComp: Ubiquitous Computing, Association for Computing Machinery (ACM), New York, UbiComp/ISWC '22, Cambridge, United Kingdom, 11/09/22. https://doi.org/10.1145/3544793.3560398

Ghosh, A & Mascolo, C 2023, Modeling with Homophily Driven Heterogeneous Data in Gossip Learning. in E Elkind (ed.), Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence. IJCAI International Joint Conference on Artificial Intelligence, International Joint Conferences on Artificial Intelligence, pp. 3741-3749, 32nd International Joint Conference on Artificial Intelligence, IJCAI 2023, Macao, China, 19/08/23. https://doi.org/10.24963/ijcai.2023/416

Ding, J, Ghosh, A, Sarkar, R & Gao, J 2022, Publishing Asynchronous Event Times with Pufferfish Privacy. in L O’Conner (ed.), 2022 18th International Conference on Distributed Computing in Sensor Systems (DCOSS)., 9881735, International Conference on Distributed Computing in Sensor Systems and workshops, IEEE, pp. 53-60, 18th Annual International Conference on Distributed Computing in Sensor Systems (DCOSS 2022), Marina Del Rey, California, United States, 30/05/22. https://doi.org/10.1109/dcoss54816.2022.00020

Ghosh, A & Xia, T 2021, Mobility-based Individual POI Recommendation to Control the COVID-19 Spread. in Y Chen, H Ludwig, Y Tu, U Fayyad, X Zhu, X Hu, S Byna, X Liu, J Zhang, S Pan, V Papalexakis, J Wang, A Cuzzocrea & C Ordonez (eds), 2021 IEEE International Conference on Big Data (Big Data)., 9671794, IEEE International Conference on Big Data, IEEE, pp. 4356-4364, 2021 IEEE International Conference on Big Data (Big Data), 15/12/21. https://doi.org/10.1109/bigdata52589.2021.9671794

Ghosh, A, Rozemberczki, B, Ramamoorthy, S & Sarkar, R 2018, Topological signatures for fast mobility analysis. in Proceedings of the 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. https://doi.org/10.1145/3274895.3274952

Ghosh, A, Lucas, C & Sarkar, R 2017, Finding Periodic Discrete Events in Noisy Streams. in Proceedings of the 2017 ACM on Conference on Information and Knowledge Management. https://doi.org/10.1145/3132847.3132981

Review article

Dang, T, Spathis, D, Ghosh, A & Mascolo, C 2023, 'Human-centred artificial intelligence for mobile health sensing: challenges and opportunities', Royal Society Open Science, vol. 10, no. 11, 230806. https://doi.org/10.1098/rsos.230806

View all publications in research portal