SPEAKER: Eduard Kamburjan, Assistant Professor at ITU. ABSTRACT: The Ontological Modeling Language (OML) is an ontology description language that stems from applying the principles of ontological modeling in the systems engineering[…]
SPEAKER: Oleg Jarma, PhD at ITU. ABSTRACT: The Cambridge Ellis Unit Summer School on Probabilistic Machine Learning took place at the University of Cambridge from July 13 to 17, 2026. It[…]
SPEAKER: Debasmita Lohar, Assistant Professor at ITU. ABSTRACT: Modern cyber-physical systems rely on feedback controllers that must execute efficiently on resource-constrained systems. Numerical precision creates a trade-off between control performance and[…]
SPEAKER: Usama Saqib, Postdoc at ITU. ABSTRACT: Localizing an autonomous underwater vehicle without pre-deployed seabed transponders, or direct access to onboard vehicle sensors remains a core challenge. We present a receiver-passive[…]
SPEAKERS: Raul Pardo, Associate Professor at ITU ABSTRACT: Free and Open Source Software (FOSS) communities’ sustainability, meaning to remain operational without signs of weakening or interruptions to its development, is fundamental[…]
SPEAKERS: Sehar Shafique, PhD Fellow at ITU ABSTRACT: “Knowledge graphs are increasingly constructed through declarative mapping languages, which allow users to define transformation rules from heterogeneous data sources into structured graph[…]
SPEAKERS: Victor, Stefan and Harshith, PhD Fellows. at ITU ABSTRACT: The Paris PhD School was an important milestone for the CAVECORE project, which aims to advance cognitive robotics and develop systematic[…]
SPEAKER: Peter Sestoft, Prof. at ITU ABSTRACT: For the last half year I have worked on the third edition of the book Programming Language Concepts (previous editions 2012 and 2017 published[…]
SPEAKER: Eduardo Kochenborger Duarte PhD fellow at ITU ABSTRACT: Ongoing work on testing methods for robot manipulation systems, explored through a proof-of-concept setup with a robot arm and Danfoss parts. The[…]
SPEAKER: Maja Aaslyng Dall, PhD fellow at ITU ABSTRACT: Bayesian probabilistic programs are good at hiding errors and bugs, which in turn has led to examples of published papers, where the[…]