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Neng Fan

Associate Professor, Statistics-GIDP | Associate Professor, Systems and Industrial Engineering | Associate Professor, Applied Mathematics - GIDP | Member of the Graduate Faculty

Systems and Industrial Engr
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30+ Collaborators
$1.3M / $15.4M Funding
4+ Grants
60+ Publications
6+ Courses

About

Dr. Neng Fan is an associate professor at Department of Systems and Industrial Engineerin at the University of Arizona, Tucson, Arizona, and member of the Applied Mathematics-GIDP and Statistics-GIDP. He received his bachelor degree in computational mathematics from Wuhan University, and master degree in applied mathematics from Nankai University in China. He also received his master and PhD degrees from Department of Industrial and Systems Engineering at University of Florida. His research focuses on large-scale optimization, and its applications in energy systems, renewable energy integration, healthcare, sustainable agriculture, etc. His work has been supported by National Science Foundation, US Department of Energy, US Department of Agriculture, and local industrials. He is a member of INFORMS and a member of IISE.

Research Area

optimization, power systems, integer programming, renewable energy, scheduling, machine learning, stochastic optimization, graph theory, healthcare, reliability, energy management, support vector machines, pmu placement, reliability analysis, statistics, data analysis, risk management, agriculture, sustainability

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    Recent

    Optimal guayule harvest planning and machinery scheduling under drought scenarios in semi-arid farms

    2024
    agricultural management, drought response

    Multistage stochastic optimization for mid-term integrated generation and maintenance scheduling of cascaded hydroelectric system with renewable energy uncertainty

    2024
    stochastic optimization, hydroelectric system, renewable energy, generation scheduling, maintenance scheduling

    Multistage robust optimization for the day-ahead scheduling of hybrid thermal-hydro-wind-solar systems

    2024
    renewable energy, optimization, energy systems, forecasting, risk management

    Minimizing the influence spread over a network through node interception

    2024
    network security, social networks, graph theory, cybersecurity

    A hybrid robust-stochastic optimization approach for day-ahead scheduling of cascaded hydroelectric system in restructured electricity market

    2023

    Optimal design of guayule and guar supply chains for the American Southwest

    2023
    supply chains, agricultural, design, natural rubber, sustainable

    Novel SVM-based classification approaches for evaluating pancreatic carcinoma

    2023
    cancer, machine learning, pancreatic carcinoma, support vector machines, medical imaging

    Stochastic Day-ahead operation of cascaded hydropower systems with Bayesian neural network-based scenario generation: A Portland general electric system study

    2023
    hydropower, stochastic modeling, neural network, bayesian inference, electricity market

    Operations of data centers with onsite renewables considering greenhouse gas emissions

    2023
    renewable energy, data centers, greenhouse gas emissions, operations efficiency, sustainability

    N-1-1 contingency-constrained unit commitment with renewable integration and corrective actions

    2022
    power systems, renewable energy, unit commitment, contingency analysis, reliability

    Page 1 of 7

    • Survey of Optimization Methods

    • Deterministic Operations Research

    • Introduction to Engineering Probability and Statistics

    • Integer and Combinatorial Optimization

    • Nonlinear Optimization

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    Neng Fan | KMap Profile - Institutional Knowledge Map (KMap)