3 papers
cs.LG2026
Giving Sensors a Voice: Multimodal JEPA for Semantic Time-Series Embeddings
Utsav Dutta, Gerardo Pastrana, Sina Khoshfetrat Pakazad +1
Transformer-based architectures have advanced sequence modeling in language and vision, yet general-purpose representation learning for heterogeneous multivariate time series remai…
cs.LG2025
Time to Embed: Unlocking Foundation Models for Time Series with Channel Descriptions
Utsav Dutta, Sina Khoshfetrat Pakazad, Henrik Ohlsson
Traditional time series models are task-specific and often depend on dataset-specific training and extensive feature engineering. While Transformer-based architectures have improve…
cs.AI2024
Liner Shipping Network Design with Reinforcement Learning
Utsav Dutta, Yifan Lin, Zhaoyang Larry Jin
This paper proposes a novel reinforcement learning framework to address the Liner Shipping Network Design Problem (LSNDP), a challenging combinatorial optimization problem focused…