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Alexandros Iosifidis

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Professor of Machine Learning

University of Tampere

Finland

Research Interests

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Recent Grants

Grant: Close

Multimodal Extreme Scale Data Analytics for Smart Cities Environments (MARVEL)

Open Date: 2021-01-01

Close Date: 2023-12-01

Grant: Close

Bayesian Neural Networks for Bridging the Gap Between Machine Learning and Econometrics (BBNmetrics)

Open Date: 2020-10-01

Close Date: 2022-09-01

Grant: Close

Open Deep Learning toolkit for Robotics (OpenDR)

Open Date: 2020-01-01

Close Date: 2023-12-01

Grant: Close

Data-Driven Inter-Stock Predictive Analytics

Open Date: 2019-10-01

Close Date: 2022-09-01

Grant: Close

Human Action Recognition in Dynamic Scenes

Open Date: 2016-09-09

Close Date: 2017-07-31

Articles (21)

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Collaborators (15)

Sajad Salavatidezfouli

Aarhus University

DENMARK

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Lukas Hedegaard

Aarhus University

DENMARK

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Konstantinos Tserpes

Faculty Member

National Technical University of Athens

GREECE

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Qi Zhang

Professor at Aarhus University

Aarhus University

DENMARK

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Ruben Pauwels

VIP, Associate Professor

Aarhus University

DENMARK

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Vijay Raghavan

Professor

University of Louisiana at Lafayette

UNITED STATES

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Georgios Bouloukakis

Dr. at Télécom SudParis

University of Patras

GREECE

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Mehmet Yamac

University of Tampere

FINLAND

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Hafiz Muhammad Junaid Malik

University of Tampere

FINLAND

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NAN LI

King's College London

UNITED KINGDOM

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Khuram Naveed

Aarhus University

DENMARK

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Juho Kanniainen

Professor at Tampere University

University of Tampere

FINLAND

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Pratik Kumar Mishra

University of Toronto

CANADA

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Jenni Raitoharju

Assistant Professor

University of Jyväskylä

FINLAND

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Fahad Sohrab

University of Tampere

FINLAND

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ApplyKite TwinLearns as you apply

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Alexandros Iosifidis

Research Interests

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Recent Grants

Articles (21)

Data-driven generative digital twins for wind-farm flows from highly sparse measurements

Impact of labelling inaccuracy and image noise on tooth segmentation in panoramic radiographs using federated, centralized, and local learning

Quasi black-box variational inference for Bayesian learning

Continual low-rank scaled dot-product attention

Classifying and clustering trading agents

Dual guidance: Reduced-order model-informed field reconstruction with generative models

Dynamic Semantic Compression for CNN Inference in Multi-Access Edge Computing: A Graph Reinforcement Learning-Based Autoencoder

Delay Bound Relaxation with Deep Learning-based Haptic Estimation for Tactile Internet

A multimodal stress detection dataset with facial expressions and physiological signals

Convolutional autoencoder-based multimodal one-class classification

Unlocking AIoT Efficiency in the Computing Continuum - the PANDORA framework

Multimodal subspace support vector data description

Multilinear Compressive Learning

CloudCast: A Satellite-Based Dataset and Baseline for Forecasting Clouds

Deep Multi-View Learning to Rank

Deep learning and computer vision will transform entomology

Exploiting heterogeneity in operational neural networks by synaptic plasticity

Forecasting Financial Time Series Using Robust Deep Adaptive Input Normalization

Graph-Embedded Multi-Layer Kernel Ridge Regression for One-Class Classification

Hypersphere-Based Weight Imprinting for Few-Shot Learning on Embedded Devices

INTEL-TAU: A Color Constancy Dataset

Collaborators (15)

Sajad Salavatidezfouli

Lukas Hedegaard

Konstantinos Tserpes

Qi Zhang

Ruben Pauwels

Vijay Raghavan

Georgios Bouloukakis

Mehmet Yamac

Hafiz Muhammad Junaid Malik

NAN LI

Khuram Naveed

Juho Kanniainen

Pratik Kumar Mishra

Jenni Raitoharju

Fahad Sohrab

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