Weijun Xie

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Assistant Professor

Georgia Institute of Technology

United States

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Weijun Xie is an Assistant Professor at the Georgia Institute of Technology, United States. His research primarily focuses on optimization methodologies and data-driven approaches, with recent work encompassing topics such as distributionally robust optimization, energy storage systems, and preventative maintenance strategies in various contexts. His contributions include advancements in algorithms for sparse principal component analysis and applications in post-disaster planning and telecommunications.

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CAREER: Favorable Optimization under Distributional Distortions: Frameworks, Algorithms, and Applications

Open Date: 2021-08-01

Close Date: 2026-07-31

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UNITED STATES

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Weijun Xie

Research Interests

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Contact this professor

About

Recent Grants

Articles (25)

Data-driven joint optimization of maintenance and spare parts provisioning: A distributionally robust approach

ALSO-X#: better convex approximations for distributionally robust chance constrained programs

D-Optimal Orienteering for Post-Earthquake Reconnaissance Planning

Regularized MIP Model for Integrating Energy Storage Systems and Its Application for Solving a Trilevel Interdiction Problem

Code and Data Repository for Regularized MIP Model for Integrating Energy Storage Systems and its Application for Solving a Trilevel Interdiction Problem

Condition-Based Maintenance for Wind Farms Using a Distributionally Robust Chance Constrained Program

On the Computation of Contextual Distributionally Robust Preventive Maintenance Intervals

Real-Time Scheduling for GAA Users’ Coexistence in CBRS Using O-RAN Architecture

Code and Data Repository for Exact and Approximation Algorithms for Sparse Principal Component Analysis

Exact and Approximation Algorithms for Sparse Principal Component Analysis

Code and Data Repository for The Terminator: An Integration of Inner and Outer Approximations for Solving Wasserstein Distributionally Robust Chance Constrained Programs via Variable Fixing

The Terminator: An Integration of Inner and Outer Approximations for Solving Wasserstein Distributionally Robust Chance Constrained Programs via Variable Fixing

Distributionally Favorable Optimization: A Framework for Data-Driven Decision-Making with Endogenous Outliers

A note on quadratic constraints with indicator variables: Convex hull description and perspective relaxation

D-Optimal Data Fusion: Exact and Approximation Algorithms

Distributionally Robust Fair Transit Resource Allocation During a Pandemic

Best Principal Submatrix Selection for the Maximum Entropy Sampling Problem: Scalable Algorithms and Performance Guarantees

Automated Vehicle Identification Based on Car-Following Data With Machine Learning

Beyond symmetry: best submatrix selection for the sparse truncated SVD

ALSO-X and ALSO-X+: Better Convex Approximations for Chance Constrained Programs

Distributionally robust bottleneck combinatorial problems: uncertainty quantification and robust decision making

On Cluster-Aware Supervised Learning: Frameworks, Convergent Algorithms, and Applications

Regret in the Newsvendor Model with Demand and Yield Randomness

Multiproduct Newsvendor Problem with Customer-Driven Demand Substitution: A Stochastic Integer Program Perspective

On distributionally robust chance constrained programs with Wasserstein distance

Collaborators (6)

Qianwen (Cami) Li

Handong Yao

Santanu Dey

Jon Lee

Xiaopeng Li

Nagi Gebraeel

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