Scalable multivariate time series analysis 

Sample-efficient and robust neurosymbolic learning from demonstrations 

Sense and sensibility: statistical techniques for human energy expenditure estimation using kinematic sensors 

Data-driven multi-fidelity modeling for physical systems 

2D object recognition by adaptive feature extraction and dynamical link graph matching 

AI-driven experimental design for learning of process parameter models for robotic processing applications 

Large deviations approach to the bistable systems with fractal boundaries 

Towards data-intensive processing architectures for improving efficiency in graph processing 

Quantum computation in wireless networks 

Privacy-aware geo-marketplaces 

Human–building integration: machine learning–based and occupant eye pupil size–driven lighting control as an applicable visual comfort tool in the office environment 

Advances in understanding and leveraging structured data for knowledge-intensive tasks 

Optimal Signal Design For The Coherent Gaussian Channel 

Interaction and topology in distributed multi-agent coordination 

The complexity of functions 

Brain connectivity in epilepsy 

Scaling recommendation models with data-aware architectures and hardware efficient implementations 

Taking the temperature of the Common Era: statistics, patterns and dynamical insights 

Beyond genotypes: genealogy-based inference of population structure and demographic history 

Measuring functional connectivity of the brain 

Processor efficient parallel graph algorithms 

Tensor learning for large-scale spatiotemporal analysis 

Signal processing methods for brain connectivity 

Informative path planning for environmental monitoring 

Neuronal signal synchrony, rhythmicity, and rate variability in neuromuscular systems