Projects per year
Organization profile
Organisation profile
The Machine Learning group conducts research in advancing machine learning methods and developing applications for a variety of signals and data, aiming to provide advanced AI solutions to real-world problems. The group focuses its research on learning theory and algorithms, deep learning, representation learning, learning from speech and multimodal data, and applications of machine learning.
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Network
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Profiles
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Peyman Aghabeyki
- The Technical Faculty of IT and Design - PhD Fellow
- Department of Electronic Systems - PhD Fellow
- Antennas, Propagation and Millimetre-Wave Systems - PhD Fellow
- Antennas
- Machine Learning
Person: VIP
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Lasse Borgholt
- The Technical Faculty of IT and Design - Industrial Postdoc
- Department of Electronic Systems - Industrial Postdoc
- Artificial Intelligence and Sound - Industrial Postdoc
- Machine Learning
Person: External
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Holger Severin Bovbjerg
- The Technical Faculty of IT and Design - PhD Fellow, Student Programme Counsellor
- Department of Electronic Systems - PhD Fellow, Student Programme Counsellor
- Artificial Intelligence and Sound - PhD Fellow, Student Programme Counsellor
- Machine Learning
Person: VIP, TAP
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Understanding the relation between work related sound environments and hearing aid benefit
01/05/2022 → 31/12/2023
Project: Research
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Machine Learning Assisted Metasurface Design and Optimization for High-Performance Millimeter-Wave Transmitarray/Reflectarray Antennas.
01/11/2020 → 01/11/2023
Project: PhD Project
Research output
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Adoption and outcome for adult hearing aid users one-year post fitting
Narayanan, S. K., Storbjerg Houmøller, S., Wolff, A., Hougaard, D. D., Gaihede, M., Schmidt, J. H. & Hammershøi, D., 5 May 2023.Research output: Contribution to conference without publisher/journal › Conference abstract for conference › Research
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A Dual-Polarized Reconfigurable Reflectarray with A Thin Liquid Crystal Layer and 2D Beam Scanning
Aghabeyki, P., Cai, Y., Deng, G., Tan, Z-H. & Zhang, S., Jan 2023, (Accepted/In press) In: I E E E Transactions on Antennas and Propagation.Research output: Contribution to journal › Journal article › Research › peer-review
Open AccessFile -
A family of split kernel adaptive filtering algorithms for nonlinear stereophonic acoustic echo cancellation
Burra, S., Sankar, S., Kar, A. & Østergaard, J., 2023, (E-pub ahead of print) In: Journal of Ambient Intelligence and Humanized Computing.Research output: Contribution to journal › Journal article › Research › peer-review
Datasets
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Can real-ear insertion gain deviations from generic fitting prescriptions predict self-reported outcomes?
Narayanan, S. K. (Creator), Rye, P. (Creator), Piechowiak, T. (Creator), Ravn, G. (Creator), Wolff, A. (Creator), Houmøller, S. S. (Creator), Schmidt, J. H. (Creator) & Hammershøi, D. (Creator), Taylor & Francis, 2022
DOI: 10.6084/m9.figshare.19538156.v1, https://tandf.figshare.com/articles/journal_contribution/Can_real-ear_insertion_gain_deviations_from_generic_fitting_prescriptions_predict_self-reported_outcomes_/19538156/1
Dataset: Supplementary material
Activities
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Menneskelig og kunstig intelligens i fremtidens vandsystemer
Jonas Falzarano Jessen (Organizer), Carsten Kallesøe (Organizer), Saruch Satishkumar Rathore (Organizer), Rafal Wisniewski (Organizer), Astrid Oberborbeck Andersen (Organizer), Pernille Christina Paulsen (Organizer), Andreas Brandt (Organizer), Ane Slot Sørensen (Organizer) & Kista Bianco Kjær (Organizer)
2 Feb 2023Activity: Attending an event › Organisation or participation in workshops, courses, or seminars
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Press/Media
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Samarbejder på tværs skal klæde os på til fremtidens smarte vandsystemer
Jonas Falzarano Jessen, Astrid Oberborbeck Andersen, Rafal Wisniewski, Saruch Satishkumar Rathore & Carsten Kallesøe
25/04/2023
2 Media contributions
Press/Media: Press / Media
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Algoritmer skal beskytte blandt andet vandnetværk mod hackerangreb
13/09/2022
1 item of Media coverage
Press/Media: Press / Media
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Sikre algoritmer skal beskytte samfundet
08/05/2022 → 13/06/2022
17 items of Media coverage
Press/Media: Press / Media