Dr Abhirup Ghosh

Dr Abhirup Ghosh

School of Computer Science
Assistant Professor in Computer Science

Contact details

Address
School of Computer Science
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-preserving methods for analyzing sensing data from phones and wearables.
Interests:

  • Federated learning
  • Domain adaptation
  • Multi-agent systems
  • Mobile health

Techniques:

  • Deep latent space geometry and topology
  • Graph theoretic algorithms
  • Differential privacy.

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 Systems
  • Mobile and Ubiquitous Computing

Postgraduate supervision

Get in touch via email if you are interested around AI/ML on edge devices. I’m always looking for interested students with a strong background in computing and mathematics.

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

Danilowski, M, Chatterjee, S & Ghosh, A 2026, BoTTA: Benchmarking on-device Test Time Adaptation. in ACM/IEEE International Conference on Embedded Artificial Intelligence and Sensing Systems (SenSys).

Murphy, A, Danilowski, M, Chatterjee, S & Ghosh, A 2026, NEO: No-Optimization Test-Time Adaptation through Latent Re-Centering. in The Fourteenth International Conference on Learning Representations (ICLR 2026). ICLR Proceedings, International Conference on Learning Representations, ICLR, Fourteenth International Conference on Learning Representations, Rio de Janeiro, Brazil, 23/04/26.

Dong, J, Jia, H, Chatterjee, S, Ghosh, A, Bailey, J & Dang, T 2025, E-BATS: Efficient Backpropagation-Free Test-Time Adaptation for Speech Foundation Models. in Advances in Neural Information Processing Systems 38 (NeurIPS 2025). Advances in Neural Information Processing Systems, vol. 38, NeurIPS, The Thirty-Ninth Annual Conference on Neural Information Processing Systems
, San Diego, California, United States, 2/12/25.

Xia, T, Ghosh, A, Qiu, X & Mascolo, C 2024, FLea: Addressing Data Scarcity and Label Skew in Federated Learning via Privacy-preserving Feature Augmentation. in KDD '24: Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. Proceedings of the International Conference on Knowledge Discovery and Data Mining, Association for Computing Machinery (ACM), pp. 3484-3494, 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Barcelona, Spain, 25/08/24. https://doi.org/10.1145/3637528.3671899

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