Responsible AI Research for Human Benefit.
AI Research Lab
In addition to our strictly virtual network of global experts, we operate a small, packed, and wildly innovative AI Lab — a deep-tech cave located in the painfully-hip neighborhood of 1070 Vienna. With a combination of research workstations, walls of whiteboards, and extensive machinery for building things, it’s the ultimate geek-out haven for our team members and visiting international AI experts.
Note: The research showcased here reflects our work at the Machine Learning Research Group (Oxford University), separate from our endeavors at object_a. It illustrates the contributions of our team members to the field of AI & Data Science.
Oxford Engineering (2025) – Outperforming State-of-the-Art 3D Source Localization with Entropy-Based Algorithms
“Oxford research demonstrates that entropy-based algorithms can outperform leading 3D source localization technology in assessing Alzheimer’s Disease, marking a significant step toward widely accessible early detection using brainwave data.” Oxford Engineering reports on this pioneering data science study, published in the world’s highest-ranked neuroimaging journal by impact factor. Wolfgang Frühwirt, founder of object_a, is the lead researcher.
Data Science / Signal Processing / Neuroimaging / Medical AI
Oxford Engineering (2023) – AI: What Doctors Want and Researchers Need
“Oxford study applies AI to predict the future of work, aiming to equip policymakers with better, quantitative information to make evidence-based strategic decisions, shaping this future to the benefit of humanity.” Oxford Engineering reports on this pioneering AI study, published in the world’s highest-ranked tech forecasting journal by impact factor. Wolfgang Frühwirt, founder of object_a, is the lead researcher.
AI / Future of Work / Strategy / Organizational Development
Oxford Engineering (2022) – Future of Work: AI Predicts What Could and Should Be Automated in Healthcare
“Using artificial intelligence (AI), Oxford researchers have developed a tool to help policymakers and organizational leaders harness the positive power of AI while reducing its unwanted effects on jobs.” Oxford Engineering reports on this pioneering AI study, published in the world’s highest-ranked tech forecasting journal by impact factor. Wolfgang Frühwirt, founder of object_a, is the lead researcher.
AI / Future of Work / Strategy / Organizational Development
Note: The research showcased here reflects our work at the Machine Learning Research Group (Oxford University), separate from our endeavors at object_a. It illustrates the contributions of our team members to the field of AI & Data Science.
Bayesian Deep Neural Networks: Improving Non-Invasive Alzheimer Diagnosis
Presented at: The world’s most prestigious AI conference (NeurIPS, ML for Health Workshop)
Publication Title: Bayesian deep neural networks for low-cost neurophysiological markers of Alzheimer’s disease severity
Core Question: How to develop a predictor for Alzheimer’s disease severity using a wide range of quantitative EEG markers?
Methods: Bayesian Deep Neural Networks (Hamiltonian Monte Carlo, Monte Carlo Dropout)
AI / Neural Networks / Neuroscience / Bayesian AI
Crypto Bubbles: Wavelet Coherence to Investigate Instabilities in Complex Financial Systems
Published in: #1 Finance Journal by Impact Factor: Finance Research Letters (Elsevier)
Publication Title: Cumulation, crash, coherency: A cryptocurrency bubble wavelet analysis
Core Question: How does the burst of crypto bubbles change the structure of the market?
Methods: Wavelet Coherence, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimator (Newey-West)
Data Science / Quantitative Finance / Crypto / Neuroscience
Outperforming State-of-the-Art 3D Source Localization with Entropy-Based Methods
Published in: #1 Neuroimaging Journal by Impact Factor: NeuroImage (Elsevier)
Publication Title: Standardized low-resolution brain electromagnetic tomography does not improve EEG Alzheimer’s disease assessment
Core Question: Can 3D Brain Mapping be outperformed with more interpretable and quicker to compute surface markers?
Methods: Standardized Low-Resolution Brain Electromagnetic Tomography, Auto-Mutual Information, Granger Causality, Shannon Entropy
Data Science / Signal Processing / Neuroimaging / Medical AI
AI & Work Automation: Machine Learning to Determine What Tasks Could and Should be Automated
Published in: #1 Tech Forecasting Journal by Impact Factor: Technological Forecasting and Social Change (Elsevier)
Publication Title: Towards better healthcare: What could and should be automated?
Core Question: What work tasks could be automated using today’s technology and should be automated because the practitioners desire it?
Methods: Independent Bayesian Classifier Combination, Gaussian Process with Ordinal Likelihood Function
Future of Work / AI / Strategy / Tech Forecasting
AI & Riemannian Geometry: Affordable MRI Biomarker Alternatives for Brain Atrophy
Presented at: The world’s most prestigious AI conference (NeurIPS, ML for Health Workshop)
Publication Title: Riemannian tangent space mapping and elastic net regularization for cost-effective EEG markers of brain atrophy in Alzheimer’s disease
Core Question: Does the combination of AI methods with Riemannian Geometry improve low-cost detection of brain shrinkage (MRI) in Alzheimer’s patients?
Methods: Riemannian Tangent Space Mapping, Elastic Net Regularization
AI / Riemannian Geometry / MRI / Neuroscience
Weather Sensor Networks: Bayesian Machine Learning to Improve Quality
Presented at: The world’s most prestigious AI conference (NeurIPS, AI Developing World Workshop)
Publication Title: Sensor Selection and Random Field Reconstruction for Robust and Cost-effective Heterogeneous Weather Sensor Networks for the Developing World
Core Question: How can we select sensors and reconstruct spatial fields to create robust and cost-effective weather sensor networks in developing countries?
Methods: Gaussian Processes, Cross Entropy method for sensor set selection, Spatial Best Linear Unbiased Estimator (S-BLUE)
AI / DeepLearning / Neuroscience / BayesianAI