Responsible AI Research for Human Benefit.
AI Research Lab
In addition to our tidy office in the city center, we have 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 (Aug 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 author.
Future of Work / AI / Strategy / Tech Forecasting
Oxford Engineering (Jan 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 author.
Future of Work / AI / Strategy / Tech Forecasting
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.
Crypto Bubbles: Using Data Science to Better Understand 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)
Future of Work: How Can AI Help Organizations and Governments Make Better-Informed Decisions?
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
Alzheimer’s Disease: How Can AI Improve Non-Invasive Diagnosis
Presented at: 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 multivariate 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
Weather Sensor Networks in the Developing World: How Can AI Improve Quality?
Presented at: 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
AI and Riemannian Geometry: Creating Affordable Alternatives to MRI Biomarkers for Brain Atrophy
Presented at: 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: Can we combine AI methods with Riemannian Geometry to develop a low-cost way to detect brain shrinkage (MRI) in Alzheimer’s patients?
Methods: Riemannian Tangent Space Mapping, Elastic Net Regularization
AI / Riemannian Geometry / MRI / Neuroscience