RESEARCH
Applied Research
My current focus is on AI ML techniques applied to industry challenges. Key areas:
Ethical AI and Risk Mitigation: Methods to ensure AI systems are fair, transparent, safe, reliable, and accountable. This includes identifying and mitigating biases in data and models, as well as developing risk assessment frameworks and ethical guidelines for AI deployment. Applications: Responsible AI solution development, accurate diagnostic for minorities.
Predictive Models: Statistical techniques and machine learning models to analyze current and historical data and make predictions about future events. Applications: forecasting sales, business planning, customer churn.
Computer Vision: Systems that can interpret and make decisions based on visual data. Objectives of computer vision include segmentation, object detection, localization, and image recognition. Applications: Medical imaging diagnostics, autonomous vehicles, quality management.
Natural Language Processing (NLP): Algorithms and models to enable machines to understand, interpret, and respond to human language in a natural way. NLP includes chatbots, sentiment analysis, translation, and summarization tools. Applications: increase employee productivity (AI assistants), customer service automation, language translation services.
Automatic Speech Recognition and Synthesis: Systems that can accurately convert spoken language into text (speech recognition) and generate human-like speech from text (speech synthesis). Applications: Virtual assistants, transcription services, accessibility tools for visually impaired individuals.
Recommendation Systems: Designing algorithms that predict and suggest items of interest to users based on their past behaviors and preferences. Applications: E-commerce platforms, streaming services, social media feeds.
Personalization and User Modeling: Creating tailored experiences for users by understanding their behavior, preferences, and needs through data analysis and machine learning. Applications: Personalized marketing, adaptive learning platforms.
Academic Research
Key topics of my academic research:
Statistics and Probability: Stochastic modeling, Statistical inference, Stochastic differential equations (SDE), Regression analysis, Causality, Bayesian inference.
AI: Machine learning, Deep learning, Markov Chain Monte Carlo, Dimensionality Reduction, Feature extraction.
Signal Processing: Spectral analysis, Time-frequency analysis, Statistical signal processing.
Biomedical Applications: Brain-Computer Interfaces (BCI), Electroencephalography (EEG), Heart Rate Variability (HRV), Protein Folding.
Journal Papers
R. Anderson and M. Sandsten, “Time-frequency feature extraction for classification of episodic memory.” EURASIP Journal on Advances in Signal Processing, Vol. 19, 2020.
R. Anderson, P. Jönsson and M. Sandsten, “Stochastic Modeling and Optimal Spectral Estimation of Task-Related HRV”, Applied Sciences, Vol. 9, Iss. 23, 5154, 2019.
Conference Papers
M. Sandsten, R. Anderson, I. Reinhold, B. Bernhardsson, C. Bergeling, M. Johansson, “A Novel Multitaper Reassignment Method for Estimation of Phase Synchrony”, IEEE Proceedings of the 26th European Signal Processing Conference (EUSIPCO), 2021.
M. Sandsten, I. Reinhold, R. Anderson, “Parameter Estimation from the Cross-Spectrogram Reassignment Vectors”, IEEE Proceedings of the 26th EUSIPCO, 2021.
R. Anderson, M. Sandsten “Multitaper Spectral Granger Causality with Application to SSVEP”, IEEE Proceedings of the 45th International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2020.
M. Sandsten, R. Anderson, I. Reinhold and J. Brynolfsson, “The Matched Reassigned Cross-Spectrogram for Phase Estimation”, IEEE Proceedings of the 45th ICASSP, 2020.
M. Sandsten, I. Reinhold, and R. Anderson, “A Multitaper Reassigned Spectrogram for Increased Time-Frequency Localization Precision”, IEEE Proceedings of the 45th ICASSP, 2020.
R. Anderson and M. Sandsten, “Classification of EEG Signals Based on Mean-Square Error Optimal Time-Frequency Features”, IEEE Proceedings of the 23th EUSIPCO, 2018.
R. Anderson, P. Jönsson and M. Sandsten, “Insights on Spectral Measures for HRV Based on a Novel Approach for Data Acquisition”, IEEE Proceedings of the 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2018.
R. Anderson, P. Jönsson and M. Sandsten, “Effects of Age, BMI, Anxiety and Stress on the Parameters of a Stochastic Model for Heart Rate Variability Including Respiratory Information”, Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSIGNALS), 2018.
R. Anderson and M. Sandsten, “Stochastic Modelling and Optimal Spectral Estimation of EEG Signals”, Proceedings of the Joint EMBEC-NBC, 2017.
Posters
R. Anderson and M. Sandsten, “Classification of EEG Signals Based on Mean-Square Error Optimal Time-Frequency Features”, Essence conference, Lund, October 2019.
R. Anderson, P. Jönsson and M. Sandsten, “Modelling of Time-varying HRV using Locally Stationary Processes”, EMBEC-NBC 2017, IFMBE Proceedings, Vol. 65, Springer, Singapore, pp. 44. June 2017.
R. Anderson, M. Sandsten, “Covariance Modelling and Inference for Time-varying Signals using Locally Stationary Processes”, Essence conference, Lund, October 2016.
R. Anderson and M. Sandsten, “Estimation of parameters of Locally Stationary Processes”, 11th IMA International Conference on Mathematics in Signal Processing, Birmingham, UK, December 2016.
R. Anderson and U. Picchini, “Approximate MLE using data-cloning ABC: inference for multi-dimensional SDEs”, 30th European Meeting of Statisticians (EMS), Amsterdam, Netherlands, July 2015.
Presentations and Talks
04/2021 – Invited talk “Optimal time-frequency feature extraction for classification of EEG signals” at INDAM workshop, NonInvasive Mathematics, Genoa, Italy (virtual)
05/2020 – IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Barcelona, Spain (virtual)
10/2019 – Swedish e-Science Academy Conference (eSSENCE), Lund, Sweden
09/2018 – European Signal Processing Conference (EUSIPCO), Rome, Italy
07/2018 – 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Honolulu, HI, USA
01/2018 – 11th International Conference on Bio-inspired Systems and Signal Processing (BIOSIGNALS), Funchal, Madeira, Portugal
06/2017 – European Medical and Biological Engineering Conference (EMBEC) and Nordic-Baltic Conference on Biomedical Engineering and Medical Physics (NBC), Tampere, Finland
12/2016 – 11th IMA International Conference Mathematics in Signal Processing, Birmingham, UK
10/2016 – Swedish e-Science Academy Conference (eSSENCE), Lund, Sweden
07/2015 – 30th European Meeting of Statisticians (EMS), Amsterdam, Netherlands