Roman Vaculín

Roman Vaculín is a Researcher at IBM Research, focusing on interdisciplinary domains where artificial intelligence, blockchain technologies, and data-centric workflows converge. His work spans automated machine learning, time series analysis, and secure computation via cryptographic methods like homomorphic encryption.

• Affiliation: IBM Research
• Key research areas: Time Series Analysis, Blockchain, AI Explainability, Business Process Management

Across his publications, Vaculín explores:

• Time Series Modeling: Developing robust frameworks like TsSHAP and end-to-end architectures for forecasting and imputation.
• Blockchain Applications: Designing trusted AI systems, secure multi-party computation, and verifiable simulations.
• Automated Machine Learning: Creating toolkits for industrial AI explainability and automation.
• Privacy-preserving Techniques: Optimizing encrypted inference and secure decision tree protocols.

His methodology often integrates formal verification with practical implementations, emphasizing efficiency and interpretability in complex systems. While no formal awards or students are documented in the provided data, his collaborative publications with institutions like IBM Research and academic partners highlight his role in advancing applied AI research.