19 citations · 20 across the 6 of their papers we have counts for
7 papers
From Non-Identifiability to Goal-Integrated Decision-Making in Parametric Inverse Optimization
Farzin Ahmadi, Fardin Ganjkhanloo, Kimia Ghobadi
Inverse optimization seeks to recover unknown objective parameters from observed decisions, yet fundamental questions about when recovery is possible have received limited formal t…
An interpretable data-driven approach to optimizing clinical fall risk assessment
Fardin Ganjkhanloo, Emmett Springer, Erik H. Hoyer +3
In this study, we aim to better align fall risk prediction from the Johns Hopkins Fall Risk Assessment Tool (JHFRAT) with additional clinically meaningful measures via a data-drive…
An interpretable data-driven approach to optimizing clinical fall risk assessment
Fardin Ganjkhanloo, Emmett Springer, Erik H. Hoyer +2
In this study we aim to better align fall risk prediction from the Johns Hopkins Fall Risk Assessment Tool (JHFRAT) with additional clinically meaningful measures via a data-driven…
Optimal Hospital Capacity Management During Demand Surges
Felix Parker, Fardin Ganjkhanloo, Diego A. Martínez +1
Effective hospital capacity management is pivotal for enhancing patient care quality, operational efficiency, and healthcare system resilience, notably during demand spikes like th…
Optimal Resource and Demand Redistribution for Healthcare Systems Under Stress from COVID-19
Felix Parker, Hamilton Sawczuk, Fardin Ganjkhanloo +2
When facing an extreme stressor, such as the COVID-19 pandemic, healthcare systems typically respond reactively by creating surge capacity at facilities that are at or approaching…
Inverse Learning: Solving Partially Known Models Using Inverse Optimization
Farzin Ahmadi, Fardin Ganjkhanloo, Kimia Ghobadi
We consider the problem of learning optimal solutions of a partially known linear optimization problem and recovering its underlying cost function where a set of past decisions and…
An Open-Source Dataset on Dietary Behaviors and DASH Eating Plan Optimization Constraints
Farzin Ahmadi, Fardin Ganjkhanloo, Kimia Ghobadi
Linear constrained optimization techniques have been applied to many real-world settings. In recent years, inferring the unknown parameters and functions inside an optimization mod…