Computational IE

Computational IE at Purdue

"Purdue IE is top notch, worldwide, and there are a lot of researchers with different backgrounds. With such diversity, collaboration can create great ideas that can solve real world challenges."

- Jun He, PhD Student

Learn more about operations research at Purdue's School of Industrial Engineering from a student perspective by watching this quick video. To find out more about the welcoming culture here at Purdue Industrial Engineering be sure to scroll down for more videos.

Computational IE Faculty

Vaneet Aggarwal
  • Supervised Learning
  • Reinforcement Learning
  • Large Language Models
  • Quantum Machine Learning
  • Applications in Networking, Transportation, Robotics, Manufacturing, Healthcare, Biomedical, and Climate.

Stephan Biller
  • Digital manufacturing and supply chain resiliency
  • Industrial Internet of Things (Industry 4.0)
  • Democratization of manufacturing
  • Implementing digital transformation

Hua Cai
  • Environmental implications of emerging technologies
  • Urban Sustainability
  • Industrial ecology
  • Complex adaptive systems

Souvik Dhara
  • Applied Probability
  • inference and algorithms on networks
  • Random graphs
  • Stochastic processes

Ana Maria Estrada Gomez
  • Complex systems
  • High-dimensional streaming data
  • Monitoring and diagnosis
  • Adaptive sampling
  • Probabilistic graphical models

Joaquin Goni Cortes
  • Complex systems
  • Graph theory and network science
  • Information theory
  • Neuroimaging and brain connectomics

Harsha Honnappa
  • Queueing theory
  • Applied probability
  • Statistics and game theory

Susan Hunter
  • Stochastic optimization
  • Multi-objective optimization under uncertainty
  • Simulation modeling and analysis
  • Applied probability and statistics

Liwei Jiang
  • Nonlinear Optimization
  • Nonsmooth Optimization
  • Stochastic Optimization
  • Data Science and Learning

David Johnson
  • Decision-making under uncertainty, applied to climate change adaptation and environmental policy
  • Flood risk modeling
  • Sustainable agriculture
  • Environmental risk communication and decision support tools
  • Multi-criteria tradeoff analysis

Charles Robert Kenley
  • Quantitative methods for systems engineering
  • Modeling and simulation methods for systems engineering
  • Programmatic risk management and risk analysis
  • Cost and schedule forecasting for technology development
  • Bayesian methods
  • Effectiveness of systems engineering management methods and processes

Reem Khir
  • Logistics and transportation planning
  • Supply chain analytics
  • System modeling and optimization
  • Robust and stochastic optimization
  • Machine learning for constrained optimization

Andrew Liu
  • Interactions of optimization
  • Game theory and Industrial organization, with applications to model and analyze energy markets and environmental policy

Nagabhushana Prabhu
  • Nonlinear optimization and its applications
  • Eigenvalue computation of large sparse matrices
  • Computational oncology
  • Soliton physics

Gesualdo Scutari
  • Distributed and Large-scale Optimization
  • Computational Game Theory
  • Variational Inequalities
  • Machine Learning
  • Big Data Analytics
  • Applications in Communications, Networking, Signal Processing, and Sensor Networks

Sivaranjani Seetharaman
  • Control systems
  • Machine learning
  • Networks
  • Energy
  • Transportation
  • Cyber-physical systems

J Shanthikumar
  • Production system modeling and analysis
  • Queueing theory and applications
  • Reliability and probability theory
  • Scheduling and sequencing
  • Simulation methodology
  • Stochastic processes and modeling

Young-Jun Son
  • Real-time Control of Smart Factory and Extended Enterprises via Digital-Twin
  • Modeling Human Decision-Making (Extended Belief-Desire-Intention Model)
  • Multi-paradigm Simulations (agent, discrete event, system dynamics, virtual reality)
  • Modeling and Control of Emerging Applications (Emergency Evacuation, Healthcare, UAV/UGV Coordination, Social Network)

Mario Ventresca
  • Approximation algorithms
  • Automated design and inference
  • Computational science and engineering
  • Discrete optimization
  • Machine learning
  • Medical operations research
  • Network science

Miaolan Xie
  • Stochastic Optimization
  • Data Science
  • Nonlinear Optimization
  • Machine Learning
  • Algorithms
  • Applications in Healthcare

Zhe "Jimmy" Zhang
  • Stochastic Optimization
  • Distributed Optimization
  • Machine Learning