Supervised learning

Reinforcement Learning

Large Language Models

Quantum Machine Learning

Applications in Networking, Transportation, Robotics, Manufacturing, Healthcare, Biomedical, and Climate

Digital-Industrial Strategy, Business and Financial Models

Resilient and Sustainable Manufacturing & Supply Chains

Production Systems, Operations Management, Enterprise Systems

Smart Manufacturing, Industry 4.0, AIoT

Digital transformation, Digital Twins

Energy Transition & Transportation

Innovation Commercialization & Go-to-Market @Scale

Carbon, water and material footprint of digitalization

Supply chain sustainability and resilience

Life cycle environmental impacts of emerging technology/system/service

System of systems (e.g., industry-agriculture-transportation-water-energy nexus)​

Integrated system modeling at different scales​

Applied Probability

Inference and Algorithms on Networks

Applied Probability

Random Graphs

Stochastic Processes

Complex Systems

High-dimensional streaming data

Monitoring and diagnosis

Adaptive sampling

Probabilistic graphical models

Complex Systems

Graph Theory and Network Science

Information Theory

Neuroimaging and Brain Connectomics

Operations and Supply Chain Strategy

Smart Manufacturing and Process Optimization

Digital Twin and Predictive Simulation (Discrete Events and System Dynamics

Engineering Learning Innovation and Pedagogy

Queueing Theory

Statistics and Game Theory

Stochastic optimization

Multi-objective optimization under uncertainty

Simulation modeling and analysis

Applied probability and statistics

Nonlinear Optimization

Nonsmooth Optimization

Stochastic Optimization

Data Science and Learning

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

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

Logistics and transportation planning

Supply chain analytics

System modeling and optimization

Robust and stochastic optimization

Machine learning for constrained optimization

Stochastic integer programming/ global optimization under uncertainty

Scheduling, resource allocation, and capacity planning in healthcare and supply chain applications

Computational modeling of disease and disease management

Computational image processing/ hyperspectral imaging/ compressive sensing

Interactions of optimization

Game theory and Industrial organization, with applications to model and analyze energy markets and environmental policy

Nonlinear optimization and its applications

Eigenvalue computation of large sparse matrices

Computational oncology

Soliton physics​

Distributed and Large-scale Optimization

Computational Game Theory

Variational Inequalities

Machine Learning

Big Data Analytics

Applications in Communications, Networking, Signal Processing, and Sensor Networks

Control systems

Machine learning

Networks

Energy

Transportation

Cyber-physical systems

Production system modeling and analysis

Queueing theory and applications

Reliability and probability theory

Scheduling and sequencing

Simulation methodology

Stochastic processes and modeling

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)

Spread of [potentially] pandemic diseases through populations (local to global scale); e.g., Zika, COVID-19

Spread of antigenically variable pathogens (local to global scale); e.g. Influenza H3N2

Deriving and optimizing vaccination distribution strategies/public health policies (including considering equity-related factors)

Influence of social media messaging on health policy acceptance​

Utilization of ML to aid in discovery of more effective policies

Use of network science to model and identify opportunities to improve trust in heterogeneous healthcare collaborative networks to improve services

Develop novel methodologies for analyzing fMRI data from network science perspective to discover cognitive differences and early decline signs among healthy, ageing, immuno-compromised populations

Strengths in network science, operations research, stochastic modeling, ML, algorithm design and analysis​

Stochastic Optimization

Data Science

Nonlinear Optimization

Machine Learning

Algorithms

Applications in Healthcare

Stochastic Optimization

Distributed Optimization

Machine Learning