Department of Industrial & Systems Engineering Lehigh University

Research

Data Science for Intelligent Systems Laboratory

We design cutting-edge data science and artificial intelligence methodologies to model, interpret, and optimize complex intelligent systems.

Overview

Research Vision

The DSIS Laboratory develops scalable, interpretable, and trustworthy AI algorithms that transform high-dimensional and multimodal data into actionable insights.

Our research lies at the intersection of Industrial Engineering, Machine Learning, and AI. We aim to bridge methodological innovation with real-world decision making by creating models that can support prediction, optimization, and intelligent system design.

DSIS Laboratory research vision

Research Directions

Current research themes

Tensor Analytics and Multimodal Learning

Many real-world systems naturally generate heterogeneous multiway data. We design tensor decomposition and tensor learning algorithms that preserve higher-order structures while enabling efficient downstream machine learning tasks.

  • Coupled tensor decomposition
  • Federated tensor learning
  • Dynamic tensor factorization
  • Multimodal representation learning
  • Self-supervised tensor learning
Tensor analytics and multimodal learning research diagram

AI for Healthcare

Healthcare data are increasingly complex and multimodal, combining electronic health records, medical imaging, genomics, wearable sensors, and clinical notes. We develop effective multimodal fusion approaches for clinical decision support.

  • Computational phenotyping
  • Disease subtyping
  • Clinical risk prediction
  • Precision medicine
  • Personalized treatment recommendation
AI for healthcare research diagram

Methods and Applications

Keywords

Artificial Intelligence Machine Learning Data Science Tensor Analytics Multimodal Learning High-Dimensional Data Modeling Operations Research Optimization Statistical Inference Federated Learning Healthcare Analytics Trustworthy AI Decision Support