David Campos

He obtained a PhD Degree in the Data Engineering, Science, and Systems Group at Aalborg University, Denmark. With a background in Computer Science and Economics, he is enthusiastic about designing tools with a particular focus on efficiency.

His research has been focused on building methods that enable the deployment of lightweight machine learning models with an efficient use of data and computational resources.

His work has been published in venues such as VLDB and SIGMOD, and he is deeply interested in research that leads to applications with a direct impact on real-world problems.

Publications

D. Campos: Lightweight and Data-Efficient Learning for Time-Series Analytics. PhD Thesis. Aalborg University, 2025. [DOI]

D. Campos, B. Yang, T. Kieu, M. Zhang, C. Guo, and C. S. Jensen. QCore: Data-Efficient, On-Device Continual Calibration for Quantized Models. VLDB 2024 (Core A*, CCF A). [DOI]

D. Campos, M. Zhang, B. Yang, T. Kieu, C. Guo, and C. S. Jensen. LightTS: Lightweight Time Series Classification with Adaptive Ensemble Distillation. SIGMOD 2023 (Core A*, CCF A). [DOI]

M. Zhang, L. Wang, D. Campos, W. Huang, C. Guo, and B. Yang. Weighted Mutual Learning with Diversity-Driven Model Compression. NeurIPS 2022 (Core A*, CCF A). [PDF]

D. Campos, T. Kieu, C. Guo, F. Huang, K. Zheng, B. Yang, and C. S. Jensen. Unsupervised Time Series Outlier Detection with Diversity-Driven Convolutional Ensembles. VLDB 2022 (Core A*, CCF A), 15(3), pp. 611-623. [DOI]

As supervisor of bachelor students:

C. Hansen, H. Le, and D. Campos. Estimation of Psychosocial Work Environment Exposures Through Video Object Detection. iWOAR 2024. [DOI]

L. Andersen, L. Jacobsen, and D. Campos. Compressed, Real-Time Voice Activity Detection with Open Source Implementation for Small Devices. iWOAR 2023. [DOI]

As bachelor student:

D. Campos and E. Malinowski. Document Data Modeling: A Conceptual Perspective. ADBIS 2019 (Core B), pp. 19-27. [DOI]

I. Díaz-Oreiro, D. Campos, B. Aymerich, J. Guzman, G. Lopez, M. Genero, and A. Vizcaíno. Software development practices and frameworks used in Spain and Costa Rica: A survey and comparative analysis. PROFES 2019 (Core B), pp. 112–119. [DOI]

D. Campos and E. Malinowski. Orientando la toma de decisiones en el sector público. CLEI 2017 (Core B), pp. 136-145. [PDF]

Visits

January - March 2025. Technical University of Berlin advised by Prof. Sebastian Schelter

July - December 2024. Hong Kong University of Science and Technology advised by Prof. Lei Chen

Grants

MASSHINE Seed Funding, Aalborg University, 2025. DKK 70.000

Study abroad grant, Stibo-Fonden, 2024. DKK 40.000

Conference travel grant, Otto Mønsteds Fond, 2023. DKK 7.460

Academic Service

Journal Reviewer - GRSL, TCSVT, ISSI, Machine Learning, World Wide Web

External Reviewer - ICLR, KDD, SIGMOD, AAAI, ICDE, VLDB

Education

Aalborg University — PhD in Machine Learning and Data Mining, December 2025.

Aalborg University — Master Degree in Computer Science, June 2021.

University of Costa Rica — Computer Science Bachelor, June 2018.

University of Costa Rica — Economics Bachelor, June 2014.