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Dr. Jianqiang Cheng is an assistant professor in the Department of Systems and Industrial Engineerin at the University of Arizona (UA), Tucson, Arizona. He completed his Ph.D. in 2013 at the PARIS-SACLAY University. He received his B.S. Degree in Math and Applied Maths in Shanghai University. He is particularly interested in Stochastic Programming, Robust Optimization, Semi-definite programming, as well as their applications. Before joining UA, he worked at Sandia National Laboratories as a postdoctroal researcher.

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Courses
  • MFSIE
    Mathematical Foundations of Systems and Industrial Engineering

  • FO
    Fundamentals of Optimization

Grants
  • Funding agency logo
    CAREER: Risk-Averse Decision Making via Chance-Constrained Programming for Power Systems

    Principal Investigator (PI)

    2022

    $406.6K
    Active
  • Funding agency logo
    lll: Small: Learning to Hash Information Networks

    Co-Investigator (COI)

    2020

    $499.6K
    Active
  • Funding agency logo
    Conic Programming Reformulations and Relaxations for Quadratically Constrained and Quadratic Programs

    Principal Investigator (PI)

    2020

    $150.0K
    Active
  • Funding agency logo
    NITC 2016 Round 4 Conference Travel Funding

    Principal Investigator (PI)

    2020

    $3.0K
    Active
  • Funding agency logo
    NITC: Data-Driven Optimization for E-Scooter System Design

    Principal Investigator (PI)

    2020

    $67.6K
  • Funding agency logo
    UofA 2017 Bisgrove Scholar Program - Dr. Jianqiang Chen

    Co-Investigator (COI)

    2017

    $200.0K
News
  • UA Researchers Win Four of Five State Bisgrove Scholar Awards

    2017

Publications (41)
Recent
  • Submodule Capacitor Sizing for Cascaded H-Bridge STATCOM with Sum of Squares Formulation

    2022

  • Asymptotically Tight Conic Approximations for Chance-Constrained AC Optimal Power Flow

    2022

  • Data-Driven Chance-Constrained Planning for Distributed Generation: A Partial Sampling Approach

    2022

  • Chance-constrained optimization-based solar microgrid design and dispatch for radial distribution networks

    2021

  • Data-Driven Robust Optimization Using Scenario-Induced Uncertainty Sets

    2021

  • Computationally Efficient Approximations for Distributionally Robust Optimization under Moment and Wasserstein Ambiguity

    2021

  • Resilient NdFeB magnet recycling under the impacts of COVID-19 pandemic: Stochastic programming and Benders decomposition

    2021

  • A Framework for Solving Chance-Constrained Linear Matrix Inequality Programs

    2020

  • Computationally Efficient Approximations for Distributionally Robust Optimization

    2020

  • Data-driven planning for renewable distributed generation integration

    2020

  • Optimization of solar-driven systems for off-grid water nanofiltration and electrification

    2020

  • Partial sample average approximation method for chance constrained problems

    2019

  • A joint chance-constrained programming approach for the single-item capacitated lot-sizing problem with stochastic demand

    2018

  • Notoriously hard (mixed-) binary QPs: empirical evidence on new completely positive approaches

    2018

  • Distributionally Robust Optimization with Principal Component Analysis

    2018

  • Probabilistic-robust optimal control for uncertain linear time-delay systems by state feedback controllers with memory

    2018

  • Partial Sample Average Approximation Approach for Stochastic Lot-Sizing Problems

    2018

  • Chance-constrained economic dispatch with renewable energy and storage

    2018

  • A fresh CP look at mixed-binary QPs: new formulations and relaxations

    2017

  • New reformulations of distributionally robust shortest path problem

    2016

  • Stochastic nonlinear resource allocation problem

    2016

  • Random-payoff two-person zero-sum game with joint chance constraints

    2016

  • Chance constrained 0 ndash;1 quadratic programs using copulas

    2015

  • Chance constrained 0--1 quadratic programs using copulas

    2015

  • A Sampling Method to Chance-constrained Semidefinite Optimization

    2015

  • Maximum probability shortest path problem

    2015

  • Stochastic Semidefinite Optimization Using Sampling Methods

    2015

  • Solving a stochastic lot-sizing problem with a modified sample approximation approach.

    2014

  • Distributionally Robust Stochastic Knapsack Problem

    2014

  • A modified sample approximation method for chance constrained problems

    2014

  • A joint chance-constraint programming approach for a stochastic lot-sizing problem

    2014

  • Second-order cone programming approach for elliptically distributed joint probabilistic constraints with dependent rows

    2014

  • A modified sample approximation approach for chance-constrained problems

    2014

  • Distributionally robust stochastic shortest path problem

    2013

  • A completely positive representation of 0--1 linear programs with joint probabilistic constraints

    2013

  • STOCHASTIC SHORTEST PATH PROBLEM WITH UNCERTAIN DELAYS

    2012

  • A second-order cone programming approximation to joint chance-constrained linear programs

    2012

  • Stochastic Shortest Path Problem with Uncertain Delays.

    2012

  • A second-order cone programming approach for linear programs with joint probabilistic constraints

    2012

  • Improved estimator of the continuous-time kernel estimator

    2010

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