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Afrooz Jalilzadeh

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

Systems and Industrial Engr
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10+ Collaborators
$307K / $307K Funding
20+ Publications

About

<p>span>Dr. Jalilzadeh is an assistant professor in the Department of Systems and Industrial Engineering at The University of Arizona. She is also a member of the Applied Mathematics GIDP and Statistics GIDP. She received her bachelor's degree in Mathematics from the University of Tehran and earned her Ph.D. in Industrial Engineering and Operations Research from Pennsylvania State University. Her research is focused on the design, analysis, and implementation of stochastic approximation methods for solving stochastic optimization and variational inequality problems, with applications in machine learning, game theory, and power systems. She leads the Optimization and Mathematical Analysis OPTIMA) lab at UofA https:sites.arizona.edu/afrooz<

Research Area

optimization, stochastic optimization, stochastic processes, constrained optimization, algorithms, variance reduction, stochastic approximation, convex optimization, machine learning, saddle point problems

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    Recent

    Optimizing Transition: Investigating the Influence of Operational Parameters on Production Scheduling Optimization for Mines Transitioning from Open Pit to Block Caving Methods

    2024
    optimization methods

    Convergence Analysis of Non-Strongly-Monotone Stochastic Quasi-Variational Inequalities

    2024
    stochastic optimization, convergence analysis, nonlinear optimization

    Variance-reduction for Variational Inequality Problems with Bregman Distance Function

    2024
    optimization, variance reduction

    Heuristic and Exact Approaches to Optimize the Production Scheduling of Mines Transitioning from the Open-Pit to Block Caving

    2024

    Optimized and Automated Secure IC Design Flow: A Defense-in-Depth Approach

    2024
    ic design, cybersecurity, automation, optimization

    Randomized Lagrangian stochastic approximation for large-scale constrained stochastic Nash games

    2024
    stochastic games, randomized methods, large-scale optimization, stochastic approximation, constrained optimization

    Accelerated Primal-dual Scheme for a Class of Stochastic Nonconvex-concave Saddle Point Problems

    2023
    stochastic optimization, primal-dual algorithms, nonconvex optimization, saddle point problems, stochastic processes

    A Stochastic Variance-reduced Accelerated Primal-dual Method for Finite-sum Saddle-point Problems

    2023
    stochastic optimization, variance reduction

    An Accelerated Asynchronous Distributed Method for Convex Constrained Optimization Problems

    2023
    distributed optimization, asynchronous algorithms, convex optimization, acceleration techniques, constrained optimization

    Projection-Free Methods for Solving Nonconvex-Concave Saddle Point Problems

    2023
    optimization, nonconvex, saddle point, projection-free, methods

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    • Research Assistant (PhD)

      Grant: 021279-00001

      A fully funded Ph.D. position is available for candidates interested in the interdisciplinary research project titled "Generalized Stochastic Nash Equilibrium Framework: Theory, Computation, and Application.", seeks a candidate with a strong background in mathematics, computer science, or related fields to develop theoretical frameworks, computational tools, and real-world applications for generalized stochastic Nash equilibria. The successful candidate will receive a competitive stipend and full tuition coverage.

    • Deterministic Operations Research

    • Optimization for Machine Learning

    • Stochastic Modeling I

    • Mathematical Foundations of Systems and Industrial Engineering

    Afrooz Jalilzadeh | KMap Profile - Institutional Knowledge Map (KMap)