45 citations · 48 across the 8 of their papers we have counts for
10 papers
CoCoNet: Convex Conformal Network for Multi-Dimensional Uncertainty Regions
Alireza Moradi, Thomas Bruys, Pascal Van Hentenryck +1
Conformal prediction (CP) provides distribution-free coverage guarantees under exchangeability, but the efficiency of its prediction regions depends critically on the choice of the…
Uncertainty-Aware Delivery Delay Duration Prediction via Multi-Task Deep Learning
Stefan Faulkner, Reza Zandehshahvar, Vahid Eghbal Akhlaghi +3
Accurate delivery delay prediction is critical for maintaining operational efficiency and customer satisfaction across modern supply chains. Yet the increasing complexity of logist…
CoCopula: Conformal Calibration and Copula Aggregation for Reliable Renewable Energy Forecasting
Alireza Moradi, Mathieu Tanneau, Reza Zandehshahvar +1
The rapid growth of renewable energy penetration has intensified the need for reliable probabilistic forecasts to support grid operations at aggregated (fleet or system) levels. In…
Enhanced Renewable Energy Forecasting using Context-Aware Conformal Prediction
Alireza Moradi, Mathieu Tanneau, Reza Zandehshahvar +1
Artificial intelligence (AI) is increasingly used to support renewable energy forecasting and grid operations. As renewable penetration grows, reliable probabilistic forecasting is…
CSI-4CAST: A Hybrid Deep Learning Model for CSI Prediction with Comprehensive Robustness and Generalization Testing
Sikai Cheng, Reza Zandehshahvar, Haoruo Zhao +4
Channel state information (CSI) prediction is a promising strategy for ensuring reliable and efficient operation of massive multiple-input multiple-output (mMIMO) systems by provid…
PROPEL: Supervised and Reinforcement Learning for Large-Scale Supply Chain Planning
Vahid Eghbal Akhlaghi, Reza Zandehshahvar, Pascal Van Hentenryck
This paper considers how to fuse Machine Learning (ML) and optimization to solve large-scale Supply Chain Planning (SCP) optimization problems. These problems can be formulated as…
Enhanced Renewable Energy Forecasting and Operations through Probabilistic Forecast Aggregation
Alireza Moradi, Mathieu Tanneau, Reza Zandehshahvar +1
Accurate and reliable forecasting of renewable energy generation is crucial for the efficient integration of renewable sources into the power grid. In particular, probabilistic for…
Agentic AI for Scaling Diagnosis and Care in Neurodegenerative Disease
Andrew G. Breithaupt, Michael Weiner, Alice Tang +14
United States healthcare systems are struggling to meet the growing demand for neurological care, particularly in Alzheimer's disease and related dementias (ADRD). Generative AI bu…
Confidence-Aware Deep Learning for Load Plan Adjustments in the Parcel Service Industry
Thomas Bruys, Reza Zandehshahvar, Amira Hijazi +1
This study develops a deep learning-based approach to automate inbound load plan adjustments for a large transportation and logistics company. It addresses a critical challenge for…
Weather-Informed Probabilistic Forecasting and Scenario Generation in Power Systems
Hanyu Zhang, Reza Zandehshahvar, Mathieu Tanneau +1
The integration of renewable energy sources (RES) into power grids presents significant challenges due to their intrinsic stochasticity and uncertainty, necessitating the developme…