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Research & Innovation

Algorithms and Data Analysis

The research scope of the Algorithms and Data Analysis (ADA) group ranges from theoretical computational complexity to machine learning for computer vision and data-driven solutions for operational research, digital privacy and health. Particular emphasis is placed on developing algorithmic solutions and concrete implementations for various applications in sectors such as health, security, and finance.

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Members

Colin Cooper

Colin Cooper

Professor of Theoretical Computer Science

Costas Iliopoulos

Costas Iliopoulos

Professor of Algorithm Design

Dimitrios Letsios

Lecturer in Data Science

Grigorios Loukides

Grigorios Loukides

Senior Lecturer in Computer Science

Frederik Mallmann-Trenn

Lecturer

Tomasz Radzik

Tomasz Radzik

Professor in Computer Science

Miaojing Shi

Lecturer in Artificial Intelligence

Michael Spratling

Michael Spratling

Reader in Computational Neuroscience and Visual Cognition

Kathleen Steinhöfel

Kathleen Steinhöfel

Reader in Computer Science

Sophia Tsoka

Reader in Bioinformatics

Clustering sequence graphs
Zhong, H., Loukidis, G. & Pissis, S. P., 2 Jan 2022, In: DATA AND KNOWLEDGE ENGINEERING. Research output: Contribution to journal › Article › peer-review
A Machine Learning Model for Predicting Fetal Hemoglobin Levels in Sickle Cell Disease Patients
Oikonomou, K., Steinhöfel, K. & Menzel, S., 2022, Proceedings of 6th International Congress on Information and Communication Technology, ICICT 2021. Yang, X-S., Sherratt, S., Dey, N. & Joshi, A. (eds.). Springer Science and Business Media Deutschland GmbH, p. 79-91 13 p. (Lecture Notes in Networks and Systems; vol. 235). Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review. DOIs: https://doi.org/10.1007/978-981-16-2377-6_10
Genetic variation influencing DNA methylation provides insights into molecular mechanisms regulating genomic function
MuTHER Consortium, 2022, (Accepted/In press) In: Nature genetics. Research output: Contribution to journal › Article › peer-review. DOIs: https://doi.org/10.1038/s41588-021-00969-x
Online Page Migration with ML Advice
Indyk, P., Mallmann-Trenn, F., Mitrovic, S. & Rubinfeld, R., 2022, AISTATS 2022. Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review
Pattern Masking for Dictionary Matching
Charalampopoulos, P., Chen, H., Christen, P., Loukides, G., Pisanti, N., Pissis, S. P. & Radoszewski, J., 1 Dec 2021, 32nd International Symposium on Algorithms and Computation, ISAAC 2021. Ahn, H-K. & Sadakane, K. (eds.). Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing, 65. (Leibniz International Proceedings in Informatics, LIPIcs; vol. 212). Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review. DOIs: https://doi.org/10.4230/LIPIcs.ISAAC.2021.65
Training object detectors from few weakly-labeled and many unlabeled images
Yang, Z., Shi, M., Xu, C., Ferrari, V. & Avrithis, Y., Dec 2021, In: PATTERN RECOGNITION. 120, 108164. Research output: Contribution to journal › Article › peer-review. DOIs: https://doi.org/10.1016/j.patcog.2021.108164
Clustering demographics and sequences of diagnosis codes
Zhong, H., Loukides, G. & Pissis, S. P., 19 Nov 2021, (Accepted/In press) In: IEEE Journal of Biomedical and Health Informatics. Research output: Contribution to journal › Article › peer-review. DOIs: https://doi.org/10.1109/JBHI.2021.3129461
Sparse regression in cancer genomics: comparing variable selection and predictions in real world data
O'Shea, R., Tsoka, S., Cook, G. & Goh, V., 9 Oct 2021, (E-pub ahead of print) In: Cancer informatics. Research output: Contribution to journal › Article › peer-review
Bidirectional String Anchors: A New String Sampling Mechanism
Loukidis, G. & Pissis, S., 1 Sep 2021, In: 29th Annual European Symposium on Algorithms (ESA). Research output: Contribution to journal › Article › peer-review. DOIs: https://doi.org/10.4230/LIPIcs.ESA.2021.64
Cancer Grade Model: a multi-gene machine learning-based risk classification for improving prognosis in breast cancer
Amiri Souri, E., Chenoweth, A., Cheung, A., Karagiannis, S. N. & Tsoka, S., 31 Aug 2021, In: British Journal of Cancer; Nature Research. 125, 5, p. 748-758 11 p. Research output: Contribution to journal › Article › peer-review. DOIs: https://doi.org/10.1038/s41416-021-01455-1

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Seminars

Upcoming seminars and events will be listed here.

Current vacancies in the group will be listed here.

Group leads

Costas Iliopoulos

Costas Iliopoulos

Professor of Algorithm Design