Author: Ivan
-
New preprint: generalizable image repair
Advanced GANs make short work of previously unseen image corruptions. Update: accepted to IROS 2025! Citation: Carson Sobolewski, Zhenjiang Mao, Kshitij Vejre, Ivan Ruchkin. Generalizable Image Repair for Robust Visual Autonomous Racing [Arxiv] [Poster] [Github] [Video]. Preprint, 2025.
-
New preprint: principles for interpretable world models
Our new paper articulates four key principles for physical interpretability of world models. We paint a broader picture on neuro-symbolic world models, beyond our recent preprint on a specific technique for physically interpretable world models for trajectory prediction. Update: accepted and presented at NeuS 2025! It also got publicized at ICRA. Citation:
-
New preprint: state-based conformal prediction
Our first collaborative paper on the NSF Neuro-Symbolic Bridge project with RPI is online! It develops a novel way to get tight conformal prediction bounds on perception error in order to improve the accuracy of reachability verification. Update: published and presented at NeuS’25! Citation:
-
TEA lab does double racing demos for Spring Visit
Great job to those who put together the demos for the ECE and MAE Spring Visits, particularly Zhongzheng and the F1/10 team!
-
New preprint: stratified neuro-symbolic architecture
Check out our nice and short position paper. The key idea is to intermingle neural components and symbolic knowledge at each level of the autonomy stack. Update: published in FSE’25! Citation:
-
Ivan co-chairs the poster/demo session at ICCPS 2025
The International Conference on Cyber-Physical Systems (ICCPS) 2025 is seeking poster and demo submissions for its 16th iteration, in Irvine, CA. Details can be found here.
-
Ivan co-chairs the poster/demo session at ICCPS 2025
The International Conference on Cyber-Physical Systems (ICCPS) 2025 is seeking poster and demo submissions for its 16th iteration, in Irvine, CA. Details can be found here.
-
New preprint: physically interpretable world models
Our recent preprint develops an architecture and a training method to give latent states physical meaning in the context of trajectory prediction:
-
MANY posters, demos, awards at NELMS IoT conference
Congratulations to many students from TEA lab presenting their work and getting recognition!
-
Two surveys: neuro-symbolic AIoT and CPS sustainability
Zhen Lu, Imran Afridi, Hong Jin Kang, Ivan Ruchkin, Xi Zheng. Surveying Neuro-Symbolic Approaches for Reliable Artificial Intelligence of Things [Springer]. In Springer Journal of Reliable Intelligent Environments (JRIE), 2024. Ankica Barišić, Jácome Cunha, Ivan Ruchkin, Ana Moreira, João Araújo, Moharram Challenger, Dušan Savić, Vasco Amaral. Modelling Sustainability in Cyber-Physical Systems: a Systematic Mapping Study [Elsevier]. In Elsevier Sustainable Computing:…