Personal profile
Personal profile
Albert Bifet is Full Professor at LTCI, Telecom ParisTech, Head of the Data, Intelligence and Graphs (DIG) Group at Telecom ParisTech, and Scientific Collaborator at Ecole Polytechnique. His research focuses on Machine Learning for Data Streams, Big Data Machine Learning and Artificial Intelligence. Problems he investigate are motivated by large scale data, the Internet of Things (IoT), and Big Data Science. He is also co-leading the open source projects MOA Massive On-line Analysis and Apache SAMOA Scalable Advanced Massive Online Analysis.
Research interests
- Data Streams
- Big Data Machine Learning
- Artificial Intelligence
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Collaborations and top research areas from the last five years
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Machine Learning for Data Streams with CapyMOA
Sun, Y., Gomes, H. M., Lee, A., Gunasekara, N., Weigert Cassales, G., Liu, J. J., Heyden, M., Cerqueira, V., Bahri, M., Koh, Y. S., Pfahringer, B. & Bifet, A., 1 Jan 2026, Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track and Demo Track - European Conference, ECML PKDD 2025, Proceedings. Dutra, I., Jorge, A. M., Soares, C., Gama, J., Pechenizkiy, M., Cortez, P., Pashami, S., Pasquali, A., Moniz, N. & Abreu, P. H. (eds.). Springer Science and Business Media Deutschland GmbH, p. 438-443 6 p. (Lecture Notes in Computer Science; vol. 16022).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
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SLEADE: Disagreement-Based Semi-Supervised Learning for Sparsely Labeled Evolving Data Streams
Gomes, H. M., Read, J., Grzenda, M., Pfahringer, B. & Bifet, A., 1 Jan 2026, In: IEEE Transactions on Knowledge and Data Engineering. 38, 3, p. 1973-1985 13 p.Research output: Contribution to journal › Article › peer-review
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AA-RPN: Adaptive Anchor-Based Region Proposal Network for Remote Sensing Object Detection
Cheng, S., Shi, Q., Lim, N. J. S. & Bifet, A., 1 Jan 2025, Neural Information Processing - 31st International Conference, ICONIP 2024, Proceedings. Mahmud, M., Doborjeh, M., Wong, K., Leung, A. C. S., Doborjeh, Z. & Tanveer, M. (eds.). Springer Science and Business Media Deutschland GmbH, p. 138-152 15 p. (Lecture Notes in Computer Science; vol. 15293 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
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Accelerated Weka: GPU Machine Learning with Weka Workbench
Cassales, G. W., Liu, J. J. & Bifet, A., 14 Sept 2025, In: Neurocomputing. 646, 130432.Research output: Contribution to journal › Article › peer-review
Open Access -
A comparative study of four deep learning algorithms for predicting tree stem radius measured by dendrometer: A case study
Cassales, G., Salekin, S., Lim, N., Meason, D., Bifet, A., Pfahringer, B. & Frank, E., 1 May 2025, In: Ecological Informatics. 86, 103014.Research output: Contribution to journal › Article › peer-review
Open Access -
Adaptive Isolation Forest
Liu, J. J., Cassales, G. W., Liu, F. T., Pfahringer, B. & Bifet, A., 1 Jan 2025, Discovery Science - 28th International Conference, DS 2025, Proceedings. Džeroski, S., Levatic, J., Pio, G. & Simidjievski, N. (eds.). Springer Science and Business Media Deutschland GmbH, p. 363-378 16 p. (Lecture Notes in Computer Science; vol. 16090 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
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Ai-enabled automated common vulnerability scoring from common vulnerabilities and exposures descriptions
Zhang, Z., Kumar, V., Pfahringer, B. & Bifet, A., 1 Feb 2025, In: International Journal of Information Security. 24, 1, 16.Research output: Contribution to journal › Article › peer-review
Open Access -
A Retrospective of the Tutorial on Opportunities and Challenges of Online Deep Learning
Kulbach, C., Cazzonelli, L., Ngo, H. A., Le-Nguyen, M. H. & Bifet, A., 1 Jan 2025, Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2023, Revised Selected Papers. Meo, R. & Silvestri, F. (eds.). Springer Science and Business Media Deutschland GmbH, p. 359-372 14 p. (Communications in Computer and Information Science; vol. 2133 CCIS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
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ASML-REG: Automated Machine Learning for Data Stream Regression
Verma, N., Bifet, A., Pfahringer, B. & Bahri, M., 14 May 2025, 40th Annual ACM Symposium on Applied Computing, SAC 2025. Association for Computing Machinery, p. 440-447 8 p. (Proceedings of the ACM Symposium on Applied Computing).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
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Automatic species identification from images for Aotearoa
Wang, H., Schlumbom, P., Frank, E., Vetrova, V., Holmes, G., Pfahringer, B., Lim, N. & Bifet, A., 1 Jan 2025, In: Journal of the Royal Society of New Zealand. 55, 6, p. 2216-2232 17 p.Research output: Contribution to journal › Article › peer-review
Open Access